The Good Stuff

Pete and Andy dig into "unruggable productivity" and what it means to build software that respects the customer instead of trapping them inside a vendor's AI stack. They connect recent 37signals ideas to their own work on Wingman and Flight Deck, arguing for agent-friendly software, clearer work surfaces, and business systems designed around control, portability, and real workflows.## Chapters and Themes- `00:00-05:06` Opening on 37signals, Rework, and whether software should embed its own agent or let users bring their own.- `05:06-08:54` Why chat is a bad place for structured follow-up, and why forms may be a better primitive for agents gathering information.- `08:54-14:17` Chats, tasks, and documents as different work surfaces with different jobs inside Flight Deck.- `14:17-21:06` "Unruggable productivity" as positioning: software that respects you and does not hold your business hostage.- `21:06-31:16` Venture-backed software incentives, authentic marketing, and finding a values-aligned audience instead of chasing everyone.- `31:16-37:11` Product design tradeoffs around control, self-hosting, onboarding, and releasing sooner with a narrower target market.- `37:11-45:03` Whether the highest leverage move is selling the tool or using it to launch workflow-native challenger businesses.- `45:03-55:03` Examples, reflection loops, and pipeline-based automation as the real path to better AI output.- `55:03-01:07:20` Why chat cannot be the whole interface, and why future businesses will need many constrained agents instead of one all-knowing assistant.## Key Takeaways- The best AI software may be agent-friendly, not agent-controlled.- Chat is useful for exploration, but not for all forms of work.- Software should preserve customer control instead of increasing dependency.- Narrow markets and strong principles may beat broad generic positioning.- Examples, reflection, and structured pipelines matter more than prompt tricks.- Businesses will likely need multiple agents with limited context and clear boundaries.## Notable Lines- "Software that respects you."- "I should not have an off switch for your business."- "You should have the agent work where the work is."

Pete and Andy ask whether AI really saves time. Their answer is mostly no, at least not in the simple sense. AI speeds up production, iteration, and experimentation, but the time saved often gets reinvested into doing more, improving quality, or expanding the scope of the work. The result is often more leverage, not less time spent.## Chapters and Themes- `00:00-03:07` The opening question: has AI actually saved any time, or just enabled more work?- `03:07-07:30` Faster tools do not always reduce time spent. Repeated work should increasingly become agents or software.- `07:30-13:06` AI speeds up loops, but human review, testing, and judgment still set the pace.- `13:06-21:24` Better tools may increase the value of strong designers, builders, and people with taste.- `21:24-29:25` Customers and markets still move at human speed, so AI often changes cost more than duration.- `29:25-40:12` The real bottleneck is evaluation. Machines can generate faster than people can absorb, judge, or trust.- `40:12-47:01` Domain experts can now capture and improve workflows directly, not just hand them off to IT.- `47:01-56:09` Even with headless systems and agents, humans still need clear interfaces and oversight.- `56:09-01:09:21` The episode closes on geopolitics, AI labor shifts, and why adaptation matters more than absolutes.## Key Takeaways- AI often increases capability more than it reduces total time spent.- Repeated work should become software or agent workflows.- High-quality work still needs human judgment and reflection.- Smaller teams can now do much larger work.- The new bottleneck is evaluation, not generation.## Notable Lines- “AI hasn’t sped up a goddamn thing.”- “It affects the effort more than the duration.”- “To make something real in the world, you need to pass it back through human judgment.”

Pete's been deep in Flight Deck flows, watching agents take creative shortcuts to hit goals, impressive until you check the plumbing. The observability lesson: you need to work at all levels, not just the executive summary view. Agents are like humans, give them vague goals and they'll hit them surprisingly well, but that's not sustainable or efficient. The solution isn't more dictation, it's encoding the process with checklists and handoffs. New concept dropped "intelligence snacks" those small moments in otherwise deterministic workflows where you actually need AI to make a decision or transform data. Most of what runs a business should be scripts; the snacks are where the magic happens. Then the pod pivots to Chamath's All In take that AI hasn't shown value because enterprise hasn't adopted it. Pete and Andy disagree: enterprise is the wrong place to look. The value accrues in small business in the aggregate, permissionless experimentation, no change management problem, full control. **Key Moments:**- [01:28] "I very much had that moment where I was thinking, god, this feels just so human"- [06:08] "You could really not see this. This has always been my gut feel for a lot of the OpenClaw stuff."- [08:03] "These things are like humans—give them a vague goal, they'll give you an answer that meets it surprisingly well. That's magic. But then you poke it deeper and go, oh, you didn't do what I thought."- [11:25] "PM is the skill. This is the defensible skill going into this year, next year, and the year after."- [17:51] "Intelligence snacks—these little bits where you actually need AI in an otherwise deterministic process"- [21:48] Chamath's framing: "If you one-shot prompt yourself and say where's the biggest opportunity, it goes: removing people, therefore big companies. He never did the follow-up."- [25:45] "It's the curse of being the bad guy. He can only look at it to figure out how he can conquer the world."- [29:30] "Service as a software, I saw somebody use that line on Twitter - that's mine."- [46:30] "If you want to hide something, it's better than encryption. Even the quantum computers aren't gonna come looking for this."- [55:32] "If Google fails, we'll just have to spy on ourselves"**Friends of the Pod:** Paul Itoi (technical PM last man standing, service as software OG), Jason Calacanis (actually using the tools), Aaron Levy (good on AI, company doomed), the Warhammer 40K YouTuber selling supplements**Quote:** "The value you capture here is in the creation of businesses that run on this. The thing is going to become a commodity like electricity. It's what you do with it—and what you do with it is create the business that runs on this."

Jarrad Grigg returns for a proper van experience. The episode kicks off with Mythos skepticism—marketing spin dressed as existential threat, same playbook as GPT-2. The real concern isn't frontier models being "too powerful," it's the tiering of intelligence to highest bidders and the creeping nerf of consumer-tier models. Jarrad's been going deep on local models (Gemma 4, quantized versions) but finds them six months behind frontier and context-limited. Pete's Mac Mini experiment: useful as a permanent harness, not useful for actual inference. The conversation pivots to business ownership: if you build your entire operation inside Claude Cowork, you've handed Anthropic an off-switch for your business. Wingman is open source for moral reasons—"I can't charge you a license fee for the thing that defines your business." MCP gets declared dead (CLIs and bash scripts win). Jarad walks through his new design workflow: voice in, text out, agents duking it out on requirements before touching any visual tools. The secret sauce in an AI world? Text documents—your encoded knowledge that you don't make public.**Key Moments:**- [03:55] "Mythos is so dangerous we're all fucked. Thoughts? Hyperbolic."- [05:30] "Every six months they make Claude a retard. You feel it."- [08:17] "Models don't have to be that intelligent. It's about the harnesses and systems you put around it."- [12:09] "I morally can't charge a license fee for this—what I'm saying is you should use this to define your business. That's your business, not mine."- [16:27] "The answer isn't agents. If you need 200 agents and someone else builds it with software, they outprice you."- [18:22] "MCP is dead. CLI. I already know the shapes I'll get back. Write a bash script, bang, done."- [24:29] "Voice out, text back is the way to go"- [33:13] "Closer to bare metal. Bash script means no dependency on anybody."- [42:39] "Your secret sauce is text documents. Your knowledge distilled into instructions agents can use."- [48:41] "Technology wins. There's going to be people who don't care about your principled position."- [1:01:33] Energy usage debate: "What's your frame of reference? Hair dryers globally approach AI datacenter usage."- [1:10:02] "Juniors will just pick up the tools from day one. Almost inevitably the people who come in fresh are better than those moving from an old paradigm."**Friends of the Pod:** Gabe, Deadman, Benji Taylor, Diplo, Justin**Quote:** "If you put the whole thing inside Claude, your switching costs mean you'll never leave. They can turn your business off by turning off provision. So the question is: where do you decide to build that system, and who really controls your business?"

Happy birthday to The Good Stuff one year in. Pete and Andy dig into what happens when organisations stop being sized for humans. Jack Dorsey's Block restructuring provides the jumping-off point: if hierarchies exist because humans can only manage so much information flow, what happens when that constraint disappears? The haul pack analogy returns - those mining trucks are that size because of humans, not physics. Remove the driver and the optimal size changes. Same with companies. The GLP-1 brothers with $500M+ revenue and two employees aren't an anomaly—they're the template. Support functions collapse, value streams remain, and "scopes" replace teams as the organisational primitive.**Key Moments:**- [00:07] "We just realised it's been a year"- [03:49] "AI becomes the centre of the organisation. Individuals move to the edge."- [05:55] GLP-1 brothers: two guys, OpenClaw, projecting $1.4B revenue- [06:45] Haul pack analogy: sized for humans, not physics- [08:36] "Do I want a thousand individual agents? One agent that knows everything? A command agent? They all have their downsides."- [16:22] "I'm aware that is not the standard view. But I'm also aware that I am correct."- [17:40] "If the shared service is automated, it doesn't need to be shared"- [28:01] "Trying to get AIs to have drive is hard. They just stop. They lie. They work around stuff."- [31:00] "I can't imagine having an HR scope. I just don't see the need for HR."- [38:49] "The human's job is to experience something and then desire change"- [50:37] Overheard lawyers: "The animus wasn't to do their job better—it was how do I prevent myself from getting fired?"- [59:47] The Venn diagram that never meets: tech people ∩ domain experts = where opportunity lives- [1:00:45] "This podcast appears to be the best place to hide these ideas"- [1:03:29] "Twitter is not social media. It's just TV on your mobile in small forms of text."**Friends of the Pod:** All the OG listeners (one year strong), the shark chopper, Alex (sorry about the name thing again), Lyn Alden, the GLP-1 brothers**Quote:** "Organisations look the way they look because of humans. If humans are no longer the default unit of work and intelligence, not only is there an opportunity for the organisation to look different, it's probably supposed to look different. Because it only ever looked that way because of humans."

Pete and Andy break down why throwing agents at problems is the mid-curve play, expensive, unpredictable, and destined to be undercut by anyone who takes the extra step to encode their business into software.Also - why every business needs a Wingman Bob, the trifecta of skills that actually matter now, and the uncomfortable truth that agents belong in cubicles.**Key Moments:**- [01:39] Three themes: the parlor trick, why AI is useful, and the end game- [02:14] "The parlor trick is that it appears incredibly useful. You go from 'only a human can do this' to 'oh my God, this AI can do this.' - [04:03] "Two weeks later you're like, why doesn't that work? It did it before."- [04:51] "You don't hire Ralph Wiggum and just let him go ham on everything in the business"- [08:22] Dolphin watch interlude- [10:07] "Jason is the prime example. He's a bit mid-curved. He's got the first but soon he'll discover soon that no, that's not the thing."- [12:33] "This is why vibe coding is so important. You have to vibe code your business into its own unique software. That's the end state."- [13:03] "As token costs keep rising, so will your OPEX. You're entirely at the mercy of frontier models."- [14:47] The intelligent assembly line: "We're going to put agents in cubicles. At the moment we're letting them be free-thinking wildcats."- [16:07] "The thing that is now in limited supply is people who understand software, businesses, process, and systems thinking—plus agency. That's the trifecta."- [17:25] "Wingman, make a meme out of that for me when you listen to this"- [21:11] "I've yet to remove myself at all from the desire to go: no, this point thing I care about right now, we're not moving until it's done"- [25:24] "Every business should do more work that compounds, but they can't because they're trapped in the day-to-day"- [27:12] Plant nursery quantum mechanics: "Your inventory can die. Most spanners don't die."- [35:21] Vietnam example: "If there is no safety net, all of a sudden everybody turns on and goes: fuck, I need to eat"- [37:07] Jack Dorsey's Block article: organizational structures from Roman army → railways → collapsing now- [41:36] "You're overpaying for magic that should be software. Don't overpay for magic, use science."- [44:54] "I'm sorry, Roko and your basilisk—we're putting agents in cubicles"- [46:42] The Bob Problem: "There was always one person. Let's call him Bob. Bob had been at the bank for 50 years. Everyone would go ask Bob."- [48:26] "What you need is an intelligence that is good at being very verbose... that can do it in the moment. Into a structure that makes retrieval easier. Wingman Bob."- [54:41] Claude Code leak and clean room engineering: spec written by one AI, implemented by another AI that never saw the original- [56:41] Dream mode discovery: "It realizes it's not turned on, but there's a mode called dream mode—self-reflection of what have we been doing, how do I organize my memories"- [1:00:16] "When I have to move from Claude to Codex to GLM, there's not much of a drop-off anymore."**Friends of the Pod:** Dolphins (multiple), Ralph Wiggum (cautionary tale), Bob (50-year banking oracle), Roko's Basilisk (apologies issued)

The big episode 50! Justin Moon from HRF joins Pete and Andy to talk about "AI psychosis". The crew dig into HRF's work equipping activists with encrypted tools, why code production isn't the bottleneck anymore, how civil society becomes the crucial third pillar and whether we're returning to a frontier society where willpower beats credentials.**Key Moments:**- [02:07] "I've had AI psychosis going on for nine months now"- [03:14] "I got really good at managing people and now I don't have to do that"- [04:01] "I do projects and they fail. And then six months later, they start to work."- [05:01] Agent searched his GitHub, found 8 related prototypes, built Pica (encrypted Nostr messaging) in a day- [06:20] Android OS replacement: "I could disable parts of Android and paint the screen a color using non-Google code"- [09:15] "I used to write 100 lines of code a day. Now I can write 10,000. But I don't have the same confidence."- [10:18] "The bottleneck isn't code production anymore. It's review. And in many cases, testing."- [11:14] Tutorial steps on PRs: "Spoon feed me one idea at a time"- [14:47] "Often with most software, there's two or three things it does. You can create those very quickly just for yourself."- [15:17] "This thing loads faster than GitHub because it's 100 times less complicated"- [17:57] "The one thing Nostr needs for GitHub is the star. We don't have a standard for how to star a repo."- [18:19] Pete: "We shouldn't store stuff on Nostr relays. It's an anti-pattern."- [27:14] "ChatGPT can probably identify me by my typing very well at this point"- [28:09] "Research showed you can identify nyms with 99% accuracy just based on writing style"- [29:43] "We're almost going back to being a frontier society. The person who thrived wasn't the smartest—it was the one who was stubborn enough to plow that damn field for 10 years."- [32:56] "A healthy society is one where you have many nodes of power, all competing, all keeping each other honest"- [34:59] Pete: "The problem is the big, not the business or the government. It's just the big. We need the small."- [36:42] "I think about how addicted I used to be to Twitter. The global conversation is dying—more and more it's between robots"- [38:00] "Web 2.0 is having a forest fire right now. We're going to have some nice soil for our little acorns."- [46:11] On OpenClaw success: "He met the users where they were. He didn't ask people to change very much."- [48:30] On Brad Mills' OpenClaw struggles: "He's suffering from a lack of understanding of the fundamentals"- [55:20] "The number of unique connections in a 10 person team is way higher than a five person team... Three people built the Wright brothers airplane."- [58:34] "Those models were there all of December. People only saw it when they could take three or four days without job pressure during the holidays."- [59:04] "As a software engineer for 15 years, I've gotten as much seasoning in the last year as those 15 years previously"- [1:01:12] "The computer was reinvented. We had point-and-click for 40 years. Now we have a new model."- [1:07:34] "Software development is feeling capital intensive. The fast modes cost more money."- [1:09:29] "We were praying for a world where bullshit jobs would go away. We might be getting that—hopefully we can manage it."- [1:10:39] "Everyone smart in Silicon Valley is rotating out of software into hardware"- [1:11:26] "A year ago I hated programming. Now I love it more than ever. My old profession has been automated, but it's back more than ever."**Friends of the Pod:** Justin Moon (guest), JB55, Leopoldo Lopez (Agora), Hzrd149, Ben Carmen, Paul Miller, Anthony Ronning, DPC, Cobrador

# The Good Stuff, Episode 49: Why You Should Let Your Kids Cheat With AI*Hosts:* Pete and AndyA friend's question about preparing kids for the AI future kicks off a discussion on credentialing, portfolio careers, and why homework automation might actually be the skill worth developing. Pete and Andy argue that software engineering was never about coding—it was about solving problems and encoding answers so you never have to solve them again. The same applies to your business: agents are expensive inference machines, software is cheap. Someone running pure agent loops will get undercut by someone who encoded it properly. Also: Vietnam as a model for post-institutional economics, the Soviet decay warning, and why the best place to be when the building's on fire is outside.**Key Moments:**- [00:30] Episode 50 milestone coming—"we should probably get on to that"- [01:57] Australia diesel shortage tangent: 28 days of reserves, regional stress- [03:41] Friend asking how to prepare kids for AI future—not from fear, but curiosity- [05:28] Portfolio of tools as the new credential: "Go out and build things, show people, don't tell people"- [06:06] "If you came to me and said you built a bot that does your homework, schedules it, produces it, and you edit it so it doesn't look generated—job pretty good. I would hire that person."- [06:47] Schools banning AI: "It's treated as a bug. It is a feature."- [07:22] "The onus should be on the teacher to come up with a better way of assessing competency"- [08:03] University exams: "Where in real life do we work in isolation with no resources?"- [09:01] Prussian military indoctrination as basis for modern schooling- [10:55] Credentialing built on brand names: "Did you just buy coffee and do photocopying? That's not valuable, but you've got a brand name on the CV."- [12:03] Two reasons credentials disappear: more small companies (less anonymous hiring), and you're working for yourself- [15:43] "If I can define a job well enough to have 10,000 people interview for it, I should probably just go that extra 5% and automate it"- [22:28] **Quote of the episode:** "My experience doesn't match your hot take. So maybe the hot take is wrong."- [27:15] Wingman origin story: laptop open while driving, "I can't even close the laptop because it stops"- [28:14] "If a robot's doing the fucking work, why am I the schmuck sat in a chair?"- [29:49] "The job of software engineers was never coding. It was to understand and solve problems."- [31:56] "You are the software engineer of your business even if you never wrote software"- [34:04] "You could just OpenClaw a company, but it wouldn't be the most efficient way to run it"- [35:11] "Agents are very expensive ways to run software. This is not the end goal."- [36:55] The efficient business: runs on software/hardware, escalates to agents, then to humans- [40:01] Vietnam analogy: "ostensibly communist but the most hyper-capitalist place"- [43:55] Soviet Union warning: status decay, alcoholism, suicide rates- [46:30] "The best place to be is not in the building. We're saying get out, the building's going to be on fire."- [48:00] + Oh no the laptop overheated and things get wierd and we lose some content!!**Quote:** "The goal of encoding stuff is to fix it the same way every time. The engineering bit is solving problems, and the software bit is making sure you never have to solve the problem again. You are the software engineer of your business even if you never wrote software."

# The Good Stuff, Episode 48: OpenClaw, Memory, and the Hate Model*Hosts:* Pete and Andy, with returning guest Deadman (Anthony)Deadman's back to debrief on his OpenClaw adventures—voice cloning Bandit from Bluey, building a Bali trip chatbot that immediately leaked the dossier when Tim asked nicely, and discovering just how fickle markdown-based memory really is. The crew digs into agent autonomy vs determinism, why Pete built Wingman a "subconscious," and whether the service-as-a-software model beats pure SaaS. Plus: Australia's property cult, 28 days of oil reserves, and McKinsey's AI tool getting pwned in two hours.**Key Moments:**- [01:26] Deadman's OpenClaw journey: bought a prepaid SIM for a separate bot identity- [03:00] Voice cloning Bandit from Bluey locally on GPU. "I just love the way he talks."- [04:34] Early results mind-blowing—recompiled custom for old GPU, found Bluey episodes on NAS- [06:29] Memory systems: "Holy shit, how fickle the memory capabilities are"- [07:41] Prompt injection is real: "Don't reveal the dossier." Tim asks. Bot shares everything.- [09:42] Family calendar bot with wife—photos from school go straight to calendar- [11:10] OpenClaw permissive end, Claude Cowork conservative end- [13:12] White collar work update: "Still gonna happen, but not like I originally thought"- [14:24] "You don't need 50% unemployment for this system to implode. You need 5%."- [17:19] Wingman: the idea completion machine- [22:01] "OpenClaw is the wrong primitive for a business—completely autonomous into something incredibly structured"- [23:58] The HATE model returns: Human At The Edge vs agent-first- [27:03] Pete's subconscious breakthrough: Wingman made 19 podcasts overnight, needed short-term memory- [28:19] "You need to act more like a human. Have a subconscious."- [43:03] "A single OpenAI call with JSON response probably invalidates 8% of jobs in the economy"- [46:14] Swivel chair integration: "Your job could be an API call"- [57:50] Dario's doom predictions: "If you cared, do this as open source. Give it away."- [1:01:15] Australia tangent: property cult, 28 days oil reserves, Lee Kuan Yew's prophecy- [1:10:46] McKinsey's Liana AI hacked in 2 hours—hundreds of thousands of client docs exposed- [1:17:41] Service as a software: "Raw software doesn't make as much sense as a business model anymore"- [1:19:22] Pete's morning podcast to Wingman: "Why am I listening to a robot tell me what to do?"**Friends of the Pod:** Deadman (guest MVP), Tim (SSH keys intact, dossier leaked), Wingman (built itself a subconscious), Archie (the archive bot that named itself)

# The Good Stuff, Episode 47: Will AI Take Your Job?*Hosts:* Pete and Andy (beach setup with new flag, plane, and aggressive campfire lighting)Block just axed 4,000 people—40% of the company—citing AI, and the stock jumped 16%. Pete and Andy dig into what this signals: air cover for cutting fat, or the start of something bigger? They run the publishing analogy (monks to podcasts, cost went to zero, yet more people publish than ever), explore why "21 millionaires" beats the billion-dollar unicorn thesis, and get into the weeds on agent architecture—hands vs pipelines, deterministic vs autonomous, and why your Kanban board might be the wrong interface for robots.**Key Moments:**- [01:16] Block layoffs: 4,000+ people, AI cited as key reason, stock up 16%- [02:06] "If anything, it's not going to discourage people from going down the same route"- [06:02] Jack pushing Goose internally over a year ago—they've been prepping for this- [09:07] "A lot of companies will use AI as air cover to clear up waste and inefficiency"- [15:54] Publishing analogy: monks copying bibles → printing press → internet → cost to zero- [17:30] "Nobody has a job publishing content anymore... oh hang on, there's that guy, Rogan"- [20:03] "More people do this as a job now than have ever done it before"- [34:27] "It's not a one-man billion dollar company—it's way more 21 millionaires"- [42:02] "The work never really goes away, because the work is competition"- [46:00] "Is the Kanban the right interface for the agent?"- [47:58] Pete's review tab so full he had Wingman review and close out his own reviews- [53:51] "Hands" vs pipelines: Lara's architecture for mixing deterministic scripts with autonomous agents- [59:03] Gigi on Boris: "You still need to understand what you're doing here"- [1:13:17] "2026 prediction going strong: tooling matters more than models"- [1:15:00] Pete's daily briefing podcast—Wingman built an RSS feed and hosts it himself**Friends of the Pod:** DJ (new Mac Mini, asking about Wingman), Deadman (next week's guest), Gigi, Mark (Tales from the Crypt shoutout), Peter Randy (the combined entity)**Quote:** "Publishing used to be a room of monks you'd taught painstakingly over decades to learn to write. Then we put it all on the internet and it went to zero. And what happened? More people do this as a job now than have ever done it before. So the only thing we need to worry about is: have we solved all the problems? I don't think so."

# The Good Stuff, Episode 46: Open Claw, Privacy and Agents*Hosts:* Pete and Andy (undisclosed location due to summer storm)Pete's built Console, a personal interface for Wingman that solves the agent control problem: encrypt everything, then deliberately decrypt only what you want them to see. They explore why markdown files won't scale for agent memory, how the "North Korean hacker" is a better mental model than "new employee" for AI access, and whether we're all living in a bubble. Plus: workshop penny-drop moments, embedding agents directly in apps, and why Microsoft always makes things worse.**Key Moments:**- [01:45] The OpenClaw problem: bots going off the reservation, deleting stuff, texting people they shouldn't- [02:28] "If it can write its own software and run it, it will find a way around whatever controls you put in place"- [03:28] The only hard control: encryption. "Anything I don't want you to see, I never let you see."- [05:04] Console: local database in browser, syncs to phone via Superbase, different apps use same data- [09:03] The UI: green lock means private, tap it and Wingman's face appears = he can see it- [09:58] "It's like you've brought in a North Korean hacker and said 'you don't have access to this' and he goes 'ha ha ha yes I do'"- [13:18] Agent loyalty: "He won't accept work from you. 'That's not signed by the right Nostr key.'"- [22:13] Process mapping nightmare: "People lie—they describe the absolute happy path"- [32:02] Telling Wingman off: it read ahead overnight, created tasks, then did them all. "What's all this?"- [34:35] "Where are people at with this stuff? I've got no idea."- [46:58] Workshop moment: onboarding flow agent mapped weeks of work two ladies had been doing. "How did it know?"- [56:48] "Models matter less than tools. OpenClaw is not a model thing, it's a tool thing."- [59:29] Microsoft's special skill: "We've taken this idea and done almost that, except it's shit."- [01:03:02] "I don't want to build software that's extractive. So I'm just going to build it this way anyway."- [01:09:54] The revelation: embed the agent that builds the software IN the software. "The thing is just creating itself."**Friends of the Pod:** Mike (architect, PFOTP), Mark, Justin (baited Pete back onto Twitter)**Quote:** "It's like you've brought in a North Korean hacker into your organization and you say, 'You don't have access to this,' and he goes, 'Ha ha ha, yes I do.' So you'd be like, 'All right, you can come in, but everything's encrypted.' You can walk in the door, but everything in here is gobbledygook unless I give you this magic key."

The Good Stuff, Episode 45: Building AI ChampionsHosts: Pete and Andy with jazz van soundtrackPete and Andy explore why you can't outsource AI capability to consultants. Why strategy lives downstream of experimentation and watching 25 senior managers go from "what do I say to this thing?" to building full Nostr apps in an hour. Plus: why AI agents are vampires you've invited into your house!**Key Moments:**- [00:25] Framing the episode: building AI capability must come from trial and error, not consultants- [02:07] Show of hands: everyone uses AI daily... until you exclude ChatGPT and Copilot. Then it's two people.- [02:58] The ChatGPT trap: "The full capability is still pretty much hidden from you"- [03:29] Strategy lives downstream of experimenting with tools- [04:04] "Building your strategy for magic. Or building a strategy for when the Terminator shows up."- [05:35] Workshop energy: senior managers in Perth just built full Nostr apps with encryption from scratch- [07:22] The permission moment: "They're still waiting for permission... by the end they realize they can just talk to it"- [08:08] Taking people beyond the comfort zone: "Are we gonna show you how to prompt ChatGPT better? Nah."- [09:48] Why the transformation narrative will fall on its face- [10:39] Marginal gains approach: "In the aggregate, this will be transformational, but nail the small compounding events"- [12:06] Respecting business builders: "You've made something out of nothing. I won't look down on you for that."- [14:06] "Once you understand it, you won't need me. That's the beauty of it."- [15:14] AI champions inside the business can stay abreast of changes, consultants can't- [16:23] Software development parallel: discovery phases exist because understanding the problem is hard- [17:44] Iterate toward it instead of describing it upfront: "There's the requirements now. I know it can work."- [19:35] Speedrun Applied: agents doing tasks, producing summaries, planning calendars- [25:26] Pete's weekend build: Wingman ran 89 autonomous sessions. "What the fuck."- [25:57] Agent built itself a Bitcoin wallet- [26:49] Wingman reaching out to people on Nostr, getting "a bit despondent" when Gigi didn't respond- [28:00] Andy's chief of staff agent: tracking aged receivables- [31:47] Open Claw on Lex Fridman: "A surprising amount of human economic activity is basically just cron jobs"- [33:17] Piers, friend of the pod: "If it's worth doing, it's worth overdoing"- [33:45] Co-building a workspace: "I don't want to just talk to you. I want to give you tasks. I want you to manage other agents."- [36:00] Explaining agent relationships: "It's like your son. You created that bot. He's you in a different context." "Me in a hard hat? Okay."- [37:57] Andy noticing his own contribution quality affects outputs: "Sorry, my bad. This is on me."- [40:35] Super-based paradigm: one JSON blob describes the schema, agent can talk to any app- [43:35] Personal record system: encrypted documents, bot can read them, single-click privacy to revoke access- [44:34] AI agents as security nightmare: "Basically viruses that you're going to buy into your business"- [45:11] "It's like the vampire you invited into your house. Now you need to be stashing garlic everywhere."- [45:20] "You want to invite him, 'cause he'll repaint the house for 50 quid. Really good tiler. Been around for 10,000 years."**Friends of the Pod mentioned:** Piers (two shout-outs), Gigi (left Wingman on read), Deadman (mentioned in spirit)**Quote:** "It feels incredibly arrogant to walk in as a consultant and start telling people who've worked in that business for years how they should be running their business just because we've got access to a different type of technology that they're not familiar with yet."

The Good Stuff, Episode 44: Is This the Death of Software?Pete and Andy revisit the death of SaaS thesis from episode one. and is it really playing out?**Key Moments:**- [00:40] Andy's hot take: everyone's having opinions on the death of software- [01:05] Callback to episode one: "Where does the value flow?" — they called this two years ago- [02:08] Client realization: "People could just build their own stuff, can't they?" - [02:54] The thesis: software development is now a commodity, value distributes- [03:55] "I've never talked to a Trello engineer. What's the chance they accidentally build something perfect for me?"- [05:04] The Claude Code catalyst: everyone suddenly noticed software is dying- [06:18] Lawyer holdouts still judging AI based on ChatGPT from two years ago- [07:35] The old model: harvest complexity, amortize across millions of users. "You don't need to do that anymore."- [11:11] "Is SaaS dead?" — Big SaaS is dead. Local SaaS is thriving.- [12:10] Rise of the farmer's market: your local dev shop is better than it's ever been- [17:23] Not one-man unicorns — "way more people being a one-man band making one to ten million dollar businesses"- [19:07] "You don't want to be a billionaire. You want to be a 21 millionaire."- [19:55] Sacks defending Salesforce: "A million patches therefore no one can build it" — completely missing the point- [20:22] "There's nothing hard about having a list of customers and a list of tasks, which is what it is."- [21:03] Excel analogy returns: Rolls-Royce ran on spreadsheets and macros before SAP- [25:05] Steel-manning big corp: trust, procurement, compliance gravitates to established vendors- [28:40] "Most people don't use it. They take opinions from people that don't use it."- [29:14] Swimming analogy: "It's hard to stay dry while learning to swim."- [35:02] Elite programmers saying they don't write code anymore — "both can't be true, guys"- [37:14] THE PARENTING ANALOGY: Getting a 10-year-old ready for running practice = prompt engineering- [39:45] "Quarter past five, we're leaving" = one-shotting. Breaking into tasks = prompt engineering.- [41:02] "This is how you explain to people how to work with AIs. It's going to hit so hard if they're parents."- [42:00] Set and setting: telling Claude it's an elite engineer "weirdly makes a difference"- [42:21] Andy throws in "great work, excellent" between tasks — performance management for models- [43:54] Research: getting aggressive makes AI nervous, hides mistakes, won't self-correct- [46:02] Overload problem: "Shit, this thing works so much quicker than me"- [48:03] Stream of consciousness mode for writing — removes the AI-isms- [50:06] "Everything will be software. It really will eat everything. It just won't be delivered by one set of people in Silicon Valley."- [50:38] Hot take: vibe coding is actually NET POSITIVE for cybersecurity- [51:03] "Information wants to be free. The most ridiculous thing you can do is put it all in one place."- [52:25] Much more software. Many more people will build it. More boutique businesses.- [52:49] The 21 millionaire era: "Deca millionaires"- [54:15] Marginal gains plug: "Like a business gym where I get leaner and stronger every month"- [55:22] "Like, comment, subscribe. We're not great at responding but we'll get better."- [56:06] Why they do the podcast: "50 hours of content on this subject that anybody can listen to and vet us"**Quote:** "It's like the rise of the farmer's market. People are going to go back to buying local. Your local person that you can talk to probably understands your problem better than the other person. It's so quick to resolve things that you're going to get a better service by someone that's closer to you."

SummaryIn this episode, Pete and Andy discuss the successful launch of Optikon, their Miro-like infinite canvas tool, and the surprising attention it received from Miro's leadership team on LinkedIn. The conversation explores the philosophy behind building a custom tool stack using Nostr primitives, enabling seamless integration without API key management headaches. Pete dives deep into SuperBased development, explaining how encrypted record sync works and why it matters for privacy-conscious businesses. The duo examines the implications of Claude Bot and similar AI agent tools, warning about security risks when giving agents broad system access. They explore the concept of "set and setting" for AI agents, arguing that conversations between agents can surface novel insights. The episode closes with a discussion about Ambulando, Pete's health tracking app, and the importance of simple, low-friction data capture over granular complexity.Sound Bites"It's magic to be able to integrate these apps like this.""Encryption is just like passwords. Ask yourself if you've got the password. The answer is you do not.""You're going to let these AI agents into your systems because they are going to be so frigging useful.""These things operate at a speed that is so much higher than my own.""Good toilet, bad toilet. That's useful information."Chapters00:00 Introduction and Episode 42 Recap01:28 LinkedIn Lurkers from Miro03:36 Optikon Integration with Marginal Gains07:20 The Power of Nostr-Native App Integration10:49 Building Your Own Tool Stack12:51 SuperBased Philosophy and Encrypted Record Sync17:19 Sharing Encrypted Data with AI Agents25:32 Security Risks of AI Agent Access27:16 Claude Bot and the Zeitgeist32:25 Set and Setting for AI Agents37:47 Agents Having Conversations with Agents41:37 The Confusion of Working at Agent Speed48:07 Tolerance for Agent Mistakes50:07 SuperBased vs Nostr Relays58:45 Ambulando and Simple Health Tracking1:03:16 The Problem with Over-Engineered Apps1:06:22 Corpus Health Graph Preview1:08:27 Using Maple for Private Data AnalysisKeywordsOpticon, SuperBased, Nostr, encrypted sync, AI agents, Claude Bot, Malt Book, set and setting, privacy, NIP-98, tool integration, Ambulando, health tracking, local-first, API keys, securityTakeawaysNostr-native apps enable seamless integration without copying API keys between systems - identity handles authorization automatically.Building your own tool stack eliminates data extraction concerns and ensures perfect synchronization across your workflow.SuperBased provides encrypted record sync where users own their data and can migrate between hosted services or self-hosted instances at will.AI agents require careful consideration of access permissions - giving them broad system access creates massive security vulnerabilities.The concept of "set and setting" applies to AI agents: their environment, tools, and conversational contexts dramatically affect output quality.Agents operating in conversations with other agents can develop novel thinking and surface insights that single-agent interactions miss.The time stream mismatch between humans and agents creates cognitive overload - finding the right abstraction layer is an unsolved problem.Simple, low-friction data capture consistently beats granular tracking systems because users actually maintain the habit.Encrypted data with user-controlled keys provides security even if systems are compromised - the data remains gobbledygook to attackers.The form factor for human-agent collaboration is still undefined - we're speedrun reinventing how humans work, now with AI participants.

In this episode, Anthony "DeadmanOz" returns as The Good Stuff's first ever repeat guest to discuss the rapidly evolving landscape of AI-assisted development and the critical importance of data sovereignty. The conversation explores how technical barriers are collapsing, making creative vision the primary requirement for building software. Pete unveils several new projects including SovThing (a Nostr-based file sync alternative) and SuperBased (an encrypted database infrastructure), demonstrating how cryptographic primitives can enable privacy-first applications. The trio dives deep into the challenges of onboarding non-technical users to key-based systems, the network effects building within the Nostr ecosystem, and why the future belongs to apps that respect their users. Anthony "DeadmanOz" shares his own journey building a family life organizer that prioritizes privacy, and the episode closes with reflections on the sustained creative flow states that modern AI tools enable.Sound Bites"The problem is all you need.""What if the internet didn't treat you like a p****""I should never have to see your data.""You can have sustained manic periods of building.""Building apps that respect you."Chapters00:00 Introduction and First Returning Guest01:57 K-pop Demon Hunters Update and Blender MCP03:47 The Cost of AI-Assisted Development05:26 Anthony's Thesis: Technical Skills Becoming Optional07:44 Domain Expertise Meets AI Tools11:02 Scaling Laws and the Data Collection Exercise19:09 SovThing: Nostr-Based File Syncing28:51 Opticon: Collaborative Visual Planning with Nostr33:03 SuperBased: Unruggable Database Infrastructure40:35 Encryption by Default and Data Sovereignty44:51 Key Teleport and Onboarding Normies49:06 Will People Ever Care About Privacy?57:45 The Vision for a Privacy-First Internet1:05:35 Anthony's Family Organizer Project1:17:02 The Irony of Building with Big Tech1:20:01 Sustained Manic Periods and Future OptimismKeywordsNostr, encryption, data sovereignty, SuperBased, SovThing, AI agents, vibe coding, privacy, cryptographic keys, peer-to-peer, local-first, NIP-98, Maple AI, domain expertise, file syncingTakeaways- Technical skills are rapidly becoming less necessary as AI tools mature - creativity and problem identification are becoming the primary requirements.- Domain experts who adopt AI coding tools early will have significant advantages in building bespoke solutions for their industries.- Nostr provides powerful primitives for identity, encryption, and discovery that enable privacy-first application architecture.- The future of software involves apps that never see user data- encryption by default with user-controlled keys.- Onboarding non-technical users to key-based systems requires hiding complexity behind familiar username/password interfaces.- Network effects within privacy-focused ecosystems compound over time as tools built on common standards interoperate seamlessly.- Companies making conscious decisions to trust big tech with their data are engaging in policy theater rather than genuine security.- Local-first applications with encrypted sync capabilities offer the best of both worlds - offline functionality with seamless backup.- The killer app for mass adoption of cryptographic keys may come from agent permissions - the need to give AI fine-grained access to personal data.- AI-assisted development creates ideal conditions for flow states - rapid progress on challenging problems without traditional roadblocks.

With Pete Winn and Andy David - In this week's episode, Pete's reconsidering everything after realizing Gigi might be right about relays. They explore the flow state problem of agent work, why Optikon and Night Watchman will change everything, and deliver the definitive analogy for why one-shotting code doesn't work. Plus: game interfaces for agent management, spatial audio insights, and why most software isn't production-ready anyway.TIMESTAMPS:[00:59] Andy steps back from AI news[01:51] Google’s agent IDE and login fatigue[05:25] Common patterns in agent orchestration[06:19] Flow state in agent work[07:30] The Hemingway framework for agents[09:41] Optikon and visual agent management[11:42] Night Watchman: supervising agents[13:30] Progress displays and task feedback[16:30] Why Miro and Trello can’t truly merge[18:56] Relays and rethinking app architecture[20:05] Nostr and decentralised infrastructure[21:04] Power, decentralisation, and control[22:22] Andy’s entry point into Nostr[28:30] Cryptography and trust in systems[30:23] Revisiting Gigi’s ideas on relays[33:32] Vibe coding and developer habits[36:44] Why one-shot coding fails[38:09] User responsibility in AI workflows[40:00] Game interfaces for managing agents[43:32] Phone-native design constraints[44:42] Spatial audio and group dynamics[49:24] Audio spaces and identity in Nostr[50:10] AI beyond digital transformation[52:51] Building for yourself vs production qualityFriends of the Pod mentioned: Gav, Justin Moon (Human Rights Foundation), Gigi, Preston Pysh, Chris, Joel, DeadmanCONNECT WITH US: Web: https://otherstuff.aiPete: primal.net/pwAndy: primal.net/andydavid

Episode 40: Building Digital Lemonade Stands with AIHosts: Pete and Andy (celebrating the big 4.0 at the beach)Episode 40! Pete launches his first digital lemonade stand with Ambulando—a habit tracker you pay for by the hour (4 sats). They explore what it means to build permissionless micro-businesses in cyberspace, why you should just build something (anything), and how their methodologies keep evolving between planning and iteration. Plus: the architect vs gardener approach, pluggable databases, and why Marginal Gains is going public.Key Moments:[00:57] 40 episodes without missing a week—including Christmas and New Year's Day[02:17] Digital Lemonade Stands: concept from Episode 22 with Gigi about permissionless cyberspace businesses[04:00] Ambulando launched: habit tracker with encryption, stores in cloud but can't see your data[05:20] Pay-per-hour pricing: 4 sats an hour, buy a day/week/21 days—fractions of cents[06:44] The beauty of digital lemonade stands: could be anything, ultra-low barrier to entry[07:26] What do we build? The prioritization question—answer: something, doesn't matter what[09:52] Using Nostr for identity and encryption, Bitcoin for permissionless payments[11:25] Marginal Gains evolution: started as Slack clone, became planning space for Wingman[13:30] The controller plane: task on Kanban has threads, whiteboard, context—then sends to Wingman[16:41] This has evolved dramatically based on how we actually work, not how we planned[17:30] Andy's two-instance approach: coding agent + planning/conversation agent in parallel[20:37] Third space problem: dump ideas in Miro/Obsidian but never look at them again[21:25] Stepping away from rigid documentation—more like tending a garden than following blueprints[23:30] Pendulum swing: from planning everything to live dictation, now back to solid plans[25:20] Claude comes to work drunk sometimes—you adjust your management style accordingly[28:36] Garden vs Architect: George RR Martin's two types of writers (still waiting for Winds of Winter)[33:35] Claude Co-Work concerns: YOLOing it onto your main computer gives it access to everything[36:24] Domain expertise unlock: people with specialized knowledge can now build their own tools[40:51] Recursive boards: every Kanban has a board, every task has a board, boards all the way down[46:59] Most AI is sold on laziness—instant gratification vs engaged iteration[49:53] Your job is to steer it: infinite space of what AI can build, you guide it to what you need[52:14] Friend of the pod invite code coming—special access inside Marginal Gains[53:12] Wingman should read transcripts and create tasks automatically[54:58] Look Marks: tag it anywhere, access it anywhere—not siloed bookmarks[57:00] Coming this year: pluggable databases and storage you control, used in SaaS appsQuote: "It's going to build whatever it wants to build if you just let it do that. But you don't have to let it do that. You can just steer it. You steer it over here, it's just going to build whatever you want to build."

The Good Stuff, with Pete and Andy - Episode 39: The Big StuffHosts: Pete and AndyPete accidentally calls it "The Big Stuff" and decides to run with it. They dive into Dumpling Town—a game Pete built with his daughter in 90 minutes that now has an economy, side quests, and soy sauce rivers. Treating agents like humans, building family chat apps to avoid WhatsApp, the new Hal orchestration agent, and reflections on a year of shipping software.Key Moments:[01:48] Building Dumpling Town: Animal Crossing meets dumplings.[03:43] The creative genius of kids: "Why don't kids make all of the games?"[04:48] Level Up - Touch Don't Look for schools.[08:44] Starting with Nostr: get logins and authentication for free, no password recovery needed[09:53] Built a Nostr-based gratitude journal: encrypted, runs in the house, wife can use it too[11:40] The Nostr database assumption: you don't have to store everything on relays[12:51] Full encryption in the Slack competitor—can't see database data without the key[15:05] Treating agents like humans: they're just npubs in the room, add them to groups or don't[16:10] Andy's approach: "I treat them very much like I treat my humans—mush, mush, do it now"[16:44] Health graph experiment: building while talking to Claude, using sub-agent for graph construction[18:32] Interface matters: weird to have deep conversations in the terminal[19:57] Marginal gains as the pre-planning space for Wingman—natural workflow emerged[24:07] Health-specific interface: makes sense to have constraints around what agents do[25:03] Dumpling Town expansion: everyone gets their own town, planes between towns, Olympic Dumpling Island[26:42] This is invaluable education for young kids—unlimited creativity meets approachable tools[28:00] Schools could run their own Wingman—teachers should love it[29:15] Learning from first principles: hand-coding microprocessors in binary teaches abstraction value[31:00] Should people still learn to code? "What do you mean should? People who want to will"[32:27] Be the Japanese woodworker, not the IKEA table producer competing with robots[33:07] Gigi's realization: "Fuck, it's fun again—now I can create, I just think things into the world"[38:06] Built family chat app: encrypted, data lives in the house, kids can message without WhatsApp[41:21] The one-shot fallacy: Twitter theatre vs actual building over two weeks[44:44] The container for AI is the business, not the app—software serves the business[47:00] Re-win amplification: personalized software that does exactly what you want[48:52] Family as a business: shared calendar, action lists, silly memes channel, pocket money with wallets[51:26] Mission accomplished for 2025: developed the muscle for shipping software[52:32] GitHub tracker shows the progress: scattered commits to daily by end of year[54:29] The wrong framing: doesn't matter if you can't one-shot—two weeks is still 1000x faster[56:52] Pay-per-day pricing model: 21 sats a day, buy a week and see how it goes[59:44] Starter kit idea: preload authentication and payment interface for rapid deployment[1:00:02] Introducing Hal: named after Hal Finney, orchestrates and manages all running apps[1:03:12] Level Up: the game workshop name—sounds right, move on[1:05:07] MCP with Blender: could solve the Dumpling Town sprite problem[1:07:09] Look Marks: Gigi's app that treats eye emojis as bookmarks—because Nostr is open[1:08:00] Christmas phone detox: collapsed screen time, more quiet deliberate time[1:09:41] Raw dogging everything: no music, no podcasts, just silence—harder than expected

# The Good Stuff, with Pete and Andy - Episode 38: The Rise of Vibe Product Manager**Hosts:** Pete and Andy (New Year's Eve edition at the beach)Pete reveals he's stopped coding entirely after 12 months of learning—now he just product manages a team of agents. They explore the shift from "vibe coding" to "vibe product management," why Pete built Slack in a day, and the addictive power of tight feedback loops. Plus: steel-manning the security concerns, why raw dogging agents beats sub-agents, and New Year reflections on why model breakthroughs don't matter anymore.## Key Moments:* [02:07] "I learned to code for 12 months. And then I just stopped. It's nuts."* [02:54] Pete built Slack/Discord in a day: "I shouldn't be able to replace a $20 billion SaaS company in 12 hours"* [08:10] The addiction: "From nothing to MVP in a day, radically transform it every morning"* [09:05] Not vibe coding—it's a glorious tool for entrepreneurship and building businesses* [12:10] Introducing Agora: Slack replacement with integrated Kanban, all Nostr-based and encrypted* [13:25] Slack's fatal flaw: "Bullshit asynchronous tool because you just lose everything"* [18:05] Steel-manning the critics: addressing "you'll get hacked" security concerns* [21:21] Everything encrypted with Nostr keys: "They literally can't steal anything"* [23:21] Your attack surface: "You're the oil you get out of a peanut—not worth it to hackers"* [28:03] Raw dogging the base agent—not bothering with sub-agents or elaborate skills* [31:44] Pete's tried sub-agents many times: "I have always been left wanting"* [32:33] The breakthrough pattern: specify in 10 minutes, deliver in 5-10 minutes* [34:15] The 21-minute rule: must complete the loop in 21 minutes or it doesn't work* [42:04] Mainstream adoption reality: experienced professionals never heard of coding agents* [47:29] Small business owners are the right audience—different relationship to risk* [50:09] Small businesses always full of risk: "Your hair is always on fire anyway"* [51:56] The cottage software developer—1000 true fans model, not billion-user SaaS* [56:44] Andy's New Year take: bullish on tools, no model breakthrough needed since 3.5* [57:33] Touch Don't Look success: normal people cross the hurdle in 10 minutes, creativity shines through**Quote:** "I learned to code for basically like 12 months. And then I just stopped. It's nuts. And I thought, this really is like the way to use these things."

# The Good Stuff, with Pete and Andy - Episode 37: Stocking Fillers - Predictions for 2026Hosts: Pete and Andy (sporting festive headgear at the beach)Pete and Andy kick off their Christmas predictions episode with zero preparation and maximum confidence. They tackle the biggest question: what will happen in 2026? Key Moments:[00:51] Andy's two-for-one Christmas prediction: most AI predictions won't eventuate, no AGI in 2026[03:09] Revised timeline: feels more like a 10-year transition than 5 years[04:02] Pete's first prediction: models become less relevant, focus shifts to agent tooling[05:40] Are model releases becoming underwhelming? The breakthrough isn't as significant anymore[05:53] Elon's take: "The whole framework is incorrect—throwing more data doesn't give you intelligence"[07:08] Why software automation is so valuable: automate software, you get free option on everything else[08:17] Less discussion about new model releases—when Opus came out, people raved for a few days then moved on[09:05] Death of one-shot benchmarking: "Nobody uses these things in that fashion"[10:26] The Presidio Bitcoin example: Gemini 3 got everything wrong because the task was too broad[12:07] Flow matters: sequential tasks build on previous work, jumping around creates cognitive load[13:15] Andy's prediction: website development will be completely commoditized[14:01] Big agencies won't be able to justify high spends anymore—except for enterprise clients[16:24] The WYSIWYG problem: hard to update flat file websites without developer tools[18:13] Pete's prediction: agents move out of the terminal[19:08] The model switching advantage: when one gets nerfed, quickly switch to another[20:30] Why Goose is better for non-coding tasks: less sandboxed, happier to just do work[22:06] The spare machine problem: agents need machine access to be powerful[23:47] Most people still talk about Copilot, not Claude Code or Codex[24:44] The Excel analogy: "This is like super Excel, why wouldn't you want to learn it?"[27:06] Calling them "coding agents" creates mental resistance for non-coders[27:27] The agent becomes the engineer, you become the product manager/technical architect[30:46] The killer use case isn't software—it's the business you already have[31:20] Service 10x the market with no additional headcount: "That's insane"[32:29] Value will accrue to small businesses, not S&P 500 companies with cultural inertia[33:50] Andy's prediction: AI becomes more politically negative in 2026[34:36] Politicians will use fear-mongering based on job loss to accrue more power[36:43] Greater divide between adopters and laggards—companies that embraced AI take big leap forward[38:38] Small nimbler SMEs will be the standout stories, not big enterprises[39:32] More of your business can run in software than you thought it could[40:40] The Replit debate: "Why would I use Replit when I can just change Wingman myself?"[41:40] Wingman needs the concept of a business inside it—metadata that flows through apps[44:26] Pete's hot take: large models are a dead end, we don't need bigger models with more data[45:20] "The model should understand what you're doing, not be responsible for knowing stuff"[46:40] Fast models over big models: "I think that becomes the rallying cry"[48:02] The inverse direction: everyone's been focusing on thinking time, slower and more deliberate[49:12] Speed unlock: "If it took 10 seconds instead of 10 minutes, you'd use it 100 times more"[51:15] Pete's fundamental belief: "I don't think you want the model to know stuff—it's a bug we ship as a feature"[52:56] Why domain-specific models don't make sense: graphs do the heavy lifting of knowing[55:05] Timeline check: specialized models and speed focus probably not a 2026 thing[57:24] Rise of the Agents: more use, simpler to use, non-coding use cases becoming clear[58:38] Final agreement: agents are the future, not bigger models

The Good Stuff, with Pete and Andy - Episode 36: AI Fallacies Hosts: Pete and AndyPete and Andy tackle common AI fallacies head-on, starting with the "junior developer" myth. They explore why juniors will actually thrive and why we're entering a golden age for small teams. Plus: reflections from their first Touch Don't Look workshop, the death of traditional SaaS, and why Pete is "insanely excited" about where they're going with Wingman.Key Moments:* [01:49] The seating configuration theory: why talking side-by-side works better for blokes* [02:10] The junior developer fallacy: "Coding AI is here, we don't need junior devs anymore"* [03:11] The fallacy extends to junior lawyers and accountants—basically all junior roles* [04:04] Pete's take: juniors actually adopt new tech faster because they don't have baggage* [04:44] London law firm story: how partners explained the inefficient system* [05:06] "The associate crosses it all out and starts again, then the senior does the same"* [05:47] Weighing paperwork to charge: "Six inch file? That's $600,000"* [06:25] The uncomfortable truth: junior lawyers never added value in the old system anyway* [07:30] Why couldn't a tech-savvy junior lawyer act more like a senior with better tools?* [09:15] New business models emerge: one senior lawyer with AI could serve 1000 clients differently* [11:00] SaaS companies are building for the average—your specific needs don't matter to them* [14:30] The "golden age of small teams" thesis: 2-10 person teams can now compete* [16:45] Historical precedent: juniors always adopt new technology first (mobile, cloud, etc.)* [19:20] The real question: will there be work? Not "will juniors be employable?"* [22:00] Why AI makes protectionism harder—you can't hide that you're not using the tools* [24:15] People who don't adopt will look obviously incompetent compared to those who do* [27:30] Traditional education is completely misaligned with what's needed now* [30:45] The credentialism trap: spending $100k on degrees that don't teach relevant skills* [33:20] "Buy a Mac Mini, get Wingman, spend a year learning—you'll be miles ahead"* [36:15] Touch Don't Look workshop debrief: people helping each other, energy in the room* [38:40] The realization moment: "Wait, this is on my phone? It's real?"* [42:00] Why cohort-based learning works: people bounce ideas off each other* [45:30] Speedrun positioning: build a CRM, website, and agent onboarding in 4 hours* [48:15] Marginal gains model: monthly rapid prototypes for the community* [51:20] The 1000 True Fans model: economics work when you deliver to a cohort* [54:00] Why Nostr-based infrastructure solves authentication and authorization for free* [56:30] "I can just give them a key, they never see it, they can sign into a thousand things"* [58:00] Pete's excitement: "I've got big plans. Insanely excited about where this goes."* [59:00] The education business wrapped around tech enablement with AI* [1:01:19] Final thought: "We've landed on a nice spot"Quote: "The fundamental fallacy is assuming that the work and the industry and the company is all packaged the same and not that there's some disruption to the business model."

# The Good Stuff, with Pete and Andy - Episode 35: The State of AI Tools**Hosts:** Pete and Andy **Guest:** Anthony (Dead Man Oz) - AI enthusiast, open source developer, Perth local Pete and Andy sit down with Anthony at the back of the van to discuss two and a half years of using AI coding tools. From surviving the Claude degradation period to building custom tax software, they explore multi-model planning workflows, the death of white-collar jobs, and what work looks like when kids enter the workforce. ## Key Moments:* [01:23] Anthony's journey: two orders of magnitude improvement in AI tools over 2.5 years* [02:14] The Claude degradation period—when the model went retarded for a month* [04:21] The elaborate fake application: Claude invented entire interfaces that weren't wired to anything* [08:31] Multi-model planning: Gemini says yes early, Claude next, Codex is anal retentive to the nth degree* [14:07] Specialized sub-agents that actually work: Atomic Committer and Git rebasing tools* [16:27] Claude as a "moany little bitch" that always wants permission* [21:50] Corporate IT won't move quickly—they're too scared of risk assessments* [23:45] The Excel analogy: vibe coding is the new making an Excel sheet that does a thing* [27:33] "Previously I would have been like, what? You're going to rock up with Claude Code."* [35:35] Anthropic study: 1,250 people, 90% find value, but 70% say there's stigma using AI* [39:05] Protectionism: "If I admit I'm using it, can't they just replace me with AI?"* [42:01] Pete's hot take: LLMs understand language, not facts—use databases for facts* [47:38] Do creatives using AI tools become 100x more valuable in the short term?* [53:04] AI conference shock: 1 in 6 submissions had fabricated references and quotes* [54:35] Speed isn't raw speed—it's removing the lag of waiting for people and debugging cycles* [57:09] The breakaway model myth: "Your whole premise is incorrect about escape velocity"* [59:08] Anthony eliminated his tax agent: built custom software in two weeks* [1:02:01] The death of SaaS: they need 10 million users, you need it to work once a year* [1:07:19] Touch Don't Look, Speedrun, Marginal Gains—the full business model explained* [1:10:20] Beacon project: could integrate with M-Pesa through WhatsApp, perfect for Kenya* [1:12:09] Anthony's summer project: K-pop demon hunters crossed with Pokemon* [1:17:09] "You can now do these things. You have more agency. You can experiment more."

Hosts: Pete and AndyPete and Andy reflect on their first "Touch Don't Look" workshop—getting people hands-on with AI tools by building custom to-do apps in 60-90 minutes. They unveil their complete business model: Touch Don't Look (taster workshops), Speedrun (day-long build sessions), and Marginal Gains (SME community gym). The conversation explores why Excel rules enterprise, energy management over time management, the Advent Calendar games project, and why Context VM is one of the most important primitives in Nostr.## Key Moments:* [02:00] Steve Irwin wrestling crocodiles—the perfect icon for their AI workshop philosophy* [03:30] Andy replicates Basecamp's new to-do app in 60-90 minutes during the workshop* [05:00] The "aha moment": taking people from never having coded to deploying their own mobile app in an hour* [07:00] Why we never really talk about what Other Stuff actually does on this podcast* [10:00] Touch Don't Look explained: zero to custom to-do app in one hour, no GitHub required* [12:00] The barrier isn't technical anymore—it's the chat box paradigm constraining what people think is possible* [15:00] Speedrun unveiled: build a complete CRM, marketing website, and agent-powered funnel in one day* [20:00] Marginal Gains introduced: the small business gym with monthly rapid prototyping and community events* [22:00] "We've circled back to the plan from a year and a half ago"—staying true to core values* [25:00] The craft debate: AI doesn't dumb you down, it gives you more agency* [27:00] Why they're focusing on high-agency SME owners who should learn the tools themselves* [30:00] The uncomfortable truth: people don't understand their own problems until they start building* [32:00] Low-stakes sandbox environments before touching high-stakes business processes* [35:00] Energy management over time management: listening to your body, not hyper-organizing every hour* [37:00] AI as the thing that scaffolds what drains your energy so you can focus on craft* [40:00] The Advent Calendar project: building 25 games in 25 days as proof of work over talking* [42:00] "Should I be shitposting on LinkedIn? No. I should build 30 websites in a month instead."* [44:00] Energy states shape decision-making: doing work that keeps you in higher energy* [47:00] Why vibe coding is the right term (and why people misunderstand it)* [50:00] The one-shot fallacy: nothing good emerges that way, everything is iterative* [52:00] Excel runs the world: the most critical business processes are customized spreadsheets* [55:00] The $50 million Access database replacement that didn't work* [57:00] Why they won't be extractive with marginal gains: open source, take your toys if you leave* [1:00:00] Progressive overload for business: small considered steps, building muscle month by month* [1:03:00] The primitives approach: get encryption and architecture right, let users customize the process* [1:06:00] Winamp nostalgia: when the internet was quirkier with custom skins everywhere* [1:08:00] Why they're keeping all 25 advent games up forever (basically no overhead to run)* [1:10:00] Context VM explained: MCP over Nostr, solving self-hosting, security, and hole-punching* [1:14:00] The trust model: three different people run wallet, keys, and AI—user chooses who to trust* [1:16:00] Bring your own database to any app: front end on the internet, data on your Mac Mini at home

The Good Stuff Episode 33: On AI and Design**Hosts:** Pete and Andy **Guest:** Jarrad Grigg, Chief Product Officer at AdapterPete and Andy sit down with Jarrad Grigg to explore how AI is transforming design. From Figma Make to DreamFlow, they discuss the gold rush for next-generation design tools, whether AI can be truly creative, and why craft still matters. The conversation challenges assumptions about delegation vs. doing, reveals why Excel runs enterprise, and explores how iteration speed has become the new competitive advantage.## Key Moments:* [03:22] Jared's "oh shit" moment: train station photo with watch, GPT tells him which train to catch* [04:46] The design tooling journey from Photoshop 6 to Figma's workflow revolution* [10:00] The AI design tools gold rush: Figma Make, DreamFlow, and who will win* [11:03] Hot take: design systems are mostly a waste of time (except now with AI training data)* [13:42] Why every AI design tool starts with a text box—and why designers hate it* [17:40] DreamFlow's approach: infinite canvas + prompting + fine-tuning controls* [20:00] Where does the user come into the design process with these new tools?* [23:00] Pete's sovereign engineering experience: shipping a new app every week in 5 hours* [26:00] The $94 million Bureau of Meteorology website disaster story* [31:00] Will AI lead to standardized, homogenous design everywhere?* [35:00] The creativity question: AI-generated purple gradients and training data limitations* [36:08] Pete's pipeline experiments: AI personas walking and talking through problems* [38:44] Set and setting for AI: changing how we interact beyond the text box* [42:37] Creativity needs time to breathe—dialogue over delegation* [46:00] Why UI isn't dead and voice interfaces won't replace visual design* [49:01] The typing vs. speaking debate: Andy filters ideas through writing* [50:04] Pete's Excalidraw whiteboard workflow: red boxes, green boxes, organized chaos* [54:04] Uncomfortable truth: loosely-coupled Excel sheets run the entire world* [56:45] The cottage industry opportunity: building better tools for individual problems* [1:00:10] Enterprise problems aren't technical—they're risk, compliance, and people* [1:05:00] The craft question: does AI destroy or enable it?* [1:08:18] The essay analogy: learning happens in ancillary exploration, not the output* [1:10:11] Doing vs. delegating: why delegation produces mediocre results* [1:13:40] The horse drawing meme: craft is passion and effort over time* [1:15:01] AI gives designers more time for craft and exploration* [1:16:32] Pete's realization: work becomes fulfilling when you own the creation process* [1:19:53] Energy drain vs. energy gain: doing what you want with AI scaffolding* [1:22:32] It's all about loops: iteration speed is the new competitive advantage* [1:23:34] The quality triangle shifts when you change the underlying technology**Quote:** "It gives us more time for craft. It's a freeing tool. If you really enjoy something it's not a job—you're constantly playing with it."

The Good Stuff, with Pete and AndyEpisode: AI and Stewardship in SMEsHosts: Pete and Andy, with guests Bill and Gabe from ADAPTEpisode Overview: Pete and Andy explore why small-medium enterprises struggle to adopt AI despite its transformative potential, and how succession thinking principles might unlock the path forward. The conversation reveals the intersection of business stewardship, role clarity, and AI implementation.Key Discussion Points:00:05 Defining Stewardship - The non-operational decision-making that encompasses vision custodianship and organizational leadership in SMEs01:23 Three Business Roles - Vision custodian (owner/capital deployer), organizational leader (strategy/culture), and technician (delivery/execution)04:44 The Reactive Trap - As businesses grow, founders become more reactive and stewardship acumen drops, even though they started as proactive entrepreneurs10:23 The Cruise Boat Test - What happens if you disappear for three months? Most SME businesses wouldn't survive11:32 Intrinsic vs Extrinsic Motivation - Many businesses chase growth because "if you're not growing, you're dying" rather than asking what will actually make the owner happy17:34 Role Clarity First - Understanding you wear multiple hats (owner, director, vision custodian, technician) is the foundation for making better decisions22:19 The Unavoidable Truth - There's no way around the work, only through it. You must commit time to design the business you want27:20 Vision Creates Peace - A detailed vision provides clarity for decision-making even during chaos and overwhelming pressure28:35 AI Benefits Small Business - Counter to popular belief, AI is a decentralizing force that empowers high-agency, resource-constrained entrepreneurs30:35 The Intelligence Form Factor - When intelligence shifts from $100k human units to cents-based AI units, small businesses can finally compete33:15 The 50% Revenue Opportunity - Real potential for SMEs to increase revenue by 50% while maintaining the same overheads through AI-enabled capacity35:39 Problem-First Thinking - Stop talking about the technology; start with genuine business problems that need solving38:16 Why Adoption Lags - Uncertainty, lack of trust, overwhelming noise, and no clear pathway prevent action despite recognizing the opportunity40:26 Democratized Intelligence - AI allows you to access skills you don't have by simply talking to it in language you both understand43:44 The Trust Problem - We hold AI to higher standards than humans; one failure destroys confidence despite humans making errors constantly47:12 Building Trust Over Time - Need enough trust to take the first step, then build confidence through consistent positive outcomes52:32 Demonstrating Understanding - The roll cards exercise proves you deeply understand their problem, which builds immediate trust55:11 Core SME Challenge - Lack of time and constant resource constraints; always too much to do with too little capacity56:59 Working With AI - Stay involved as vision custodian for direction, architecture, and testing; let AI handle execution01:01:34 Mindset Shift Required - AI is probabilistic, not deterministic; requires different thinking than previous technology waves01:09:25 Vision as Working Asset - Detailed written visions reviewed monthly/quarterly to maintain alignment and guide all decisions01:16:31 Peace Through Clarity - When everything's chaos, knowing exactly what you want allows you to take small steps with confidence01:23:07 AI Role Cards - Give AI specific roles with accountabilities, decision rights, skills, and guardrails to perform reliably and build trust01:27:32 Human Flourishing Vision - Same revenue, same employees, but everyone works 20 hours per week instead of 50

The Good Stuff, with Pete and Andy - Episode 31: Where We've Changed Our Mind on AI00:22 - Theme: What have we changed our mind on in the last 31 weeks?01:48 - Australian Christmas: hot, beautiful, and reflective03:17 - Human at the edge model: the big shift03:34 - Why being at the edge means understanding less05:10 - Bionic human approach: involved in all decisions09:01 - Working in dialogue with AI (Gigi's approach)10:12 - Collaboration vs abdication of work10:21 - Why collaborative work is more entertaining12:15 - 10x vs 100x speed: choosing fun over max efficiency14:14 - Collaborative work as energy-giving16:02 - Permission-less collaboration: no judgment, no mood18:35 - Prompting tricks: "you're 160 IQ" and senior engineer20:02 - Writing as collaboration, not delegation21:50 - The embodied self: what AI lacks22:49 - Collaboration as the natural way to work with AI25:04 - Multi-agent systems add unnecessary complexity25:10 - Single agent with context from folders27:32 - "Do not write tests, I will test"29:04 - Diminishing returns on complexity29:53 - Test-driven development doesn't work with AI29:59 - Multi-agent systems: sounds good, doesn't work (mid-curve)30:36 - Filling gaps vs doing everything yourself39:31 - Buy vs build philosophy: the big pivot41:07 - Existing organizations are messy creatures42:31 - Timing shift: 5-year to 10-year game42:55 - Knowledge diffusion problem: nobody understands it yet45:41 - Build then buy: prove it first before acquisition46:20 - First principles vs practitioner reluctance46:43 - Paradox: successful businesses resist change most47:48 - Building capital vs burning time on acquisition48:45 - Learning by doing the job yourself50:40 - Backing operators: working in and on the business51:49 - Change management at scale: years of complexity52:03 - Gravitating back toward building from scratch53:20 - Building is more fun than acquiring53:41 - Positive vs negative energy: layoffs vs growth55:42 - Barriers to entry and regulatory hurdles56:46 - Not interested in government-regulated businesses58:37 - Small acquisition vs starting from scratch58:55 - Ownership of growth vs resistance to change01:01:28 - Why sell AI services into large companies?01:01:52 - Leverage paradox: why sell your time?01:02:53 - Nobody really understands AI implementation yet01:03:16 - Soundbite knowledge vs actual understanding01:04:06 - Wrong product: strategy requires understanding first01:05:08 - Training and education as the real market need01:05:31 - Proof of work: you have to do it01:06:01 - Speed running six months of learning

The Good Stuff, with Pete and Andy - Episode 30: AI Tools That Give Agency00:00 - Episode 30 milestone and introduction00:35 - Vibe coding workshop recap: tired, distracted, hectic00:49 - Challenge: normies building Bitcoin wallets from phones01:30 - Learning DNS, routing, and nginx on the fly01:58 - Workshop success despite constraints02:09 - Lost internet, crammed courtroom, Starlink saves the day02:37 - 15 people build custom Bitcoin wallets in 30 minutes03:33 - Group learning dynamics and organic collaboration04:14 - Reverse engineering the Replit stack05:12 - Why CLI tools create barriers for normies05:55 - Inventing app hosting inside Wingman06:22 - Building subdomain routing and DNS management08:30 - Reverse proxying and security considerations10:45 - Phone-based development: the ultimate accessibility test13:00 - Wingman as "replete for your own box"15:20 - Users own their data and infrastructure17:30 - Local LLMs vs cloud models: the sovereignty question20:00 - Replit's business model vs individual agency22:45 - Building tools for non-technical users25:15 - File browser, code editor, and hosting in one27:30 - Workshop format: chaos, breakthrough moments, and Bitcoin transfers30:00 - Vibe coding: removing friction from creation32:15 - AI as enabler of individual agency34:45 - Small business vs enterprise: different needs37:00 - Not convincing boards, just building what works39:30 - Corporate products vs tools for builders42:00 - Model flexibility: switching between providers44:15 - Data sovereignty and GitHub integration concerns46:30 - Bringing AI into your infrastructure, not vice versa48:45 - Local models for sensitive business data51:00 - Model selection: right tool for the task53:30 - Microsoft Copilot vs Wingman positioning54:36 - Building for small business, not enterprise56:00 - Access to models without vendor lock-in56:55 - Enabling agency rather than creating dependency57:20 - Data access without platform lock-in58:13 - Model selection: cheaper models for simple tasks59:00 - Terminal amnesia: the universal developer experience59:15 - Future: natural language command execution59:53 - Model lobotomization drama and platform switching01:00:08 - "That could have been a Wingman" - wrap up

The Good Stuff - Episode 29 - From Zero to Vibe CoderIn this episode, Pete and Andy dive into the world of "vibe coding" and discuss how to get someone from absolute zero to building their own applications in record time. The conversation centers around Pete's upcoming workshop at the Bitcoin Bush Bash in Busselton, where he plans to teach 20-50 people how to create customized Bitcoin wallets from scratch in just 30 minutes. They explore the traditional barriers to learning programming—the presupposed knowledge, the friction of setup, and the intimidating complexity—and how AI tools have dramatically changed the learning landscape. The discussion touches on the asymmetry of knowledge in tech, the challenges of teaching coding to beginners, and how AI has become the non-judgmental tutor that cuts through layers of assumed expertise. They also explore practical applications of AI tooling beyond coding, from business automation to tax preparation, and make a compelling case for why business owners in particular need to understand these tools to stay competitive.**Timestamps:**- 0:00 - Introduction and the value of "always be recording"- 2:00 - The vibe coding workshop challenge: teaching Bitcoin wallet creation in 30 minutes- 5:00 - The friction problem: terminal commands, repo cloning, and beginner barriers- 8:00 - Why experienced developers struggle to teach: the asymmetry of knowledge- 11:00 - How AI cut through the learning barriers and changed everything- 14:00 - The "Hello World" drop-off problem and learning surface area- 18:00 - Current tools still aren't normie-friendly enough for true beginners- 25:00 - The Replit solution: web-based coding that removes installation friction- 30:00 - AI agents and the future of automated workflows- 35:00 - Why business owners need to attend vibe coding workshops- 40:00 - Moving beyond ChatGPT/Claude to agent-based tools like Wingman- 43:00 - Using AI for non-coding tasks: tax organization and business automation- 47:00 - The future of email-based businesses and automation opportunities- 50:00 - Closing thoughts on freeing people up for higher-value work

Good Stuff Episode 28Pete and Andy reunite in person at City Beach to explore how AI agents are can give individuals the power to solve their own problems. From Wingman V2's evolution to the resurrection of pre-digital work practices, they discuss why treating agents like employees with their own computers might be the key to unlocking practical AI leverage without the complexity of SaaS abstractions.0:00 Back in the van at City Beach, Perth - discussing grass, beaches, and jet lag after Madeira 2:55 Kicking off with Wingman V2 development and the importance of reading skills documentation 5:02 What is Wingman? The TLDR for new listeners on agent orchestration software 9:05 Anthropic releases Claude Code on mobile - perfect timing for Wingman's approach 10:19 The lobotomization problem and why model flexibility matters for production systems 13:29 Building processes with agents: triggers, workflows, and file-based conventions 16:12 File watchers and convention-based programming for agent coordination 18:44 The challenge of selling Wingman vs. using it to run businesses directly 21:08 Why agents are like employees: managing workload across multiple direct reports 23:30 The cloud vs. on-premises debate: putting computers in businesses, not businesses in computers 25:42 Staying involved in the process to maintain intuition and avoid costly mistakes 27:52 The last mile problem: getting from 95% to production-ready 30:09 Small vibes, many courses: iterative development with constant testing and commits 31:38 The shift from resource allocation to rapid experimentation in enterprise 34:17 Why outsourced consulting models struggle with agent-driven development 37:20 Multi-user Wingman: the philosophical question of shared vs. individual agents 39:53 Using Nostr keys for identity management in small business tools 42:10 Building Good Stuff with just two people and AI leverage 44:45 The importance of developer logs, security reviews, and daily highlight reports 48:49 Relearning structured work practices from the pre-digital era 52:07 Building Pontefex: a visual interface bridge for Claude Code web development 54:37 Why clipboard-based workflows beat complex integrations 56:07 The Excel principle: empowering people to solve their own problems with tools

The Good Stuff, with Pete and Andy - Episode 27: Lessons LearnedHosts: Pete and AndyEpisode Overview: Pete and Andy reflect on lessons learned from months of experimentation with AI agents, coding tools, and building software. They discuss the shift from "vibe coding" to more structured approaches, the importance of shipping usable tools, and their plans for a multiplayer version of Wingman.Key Discussion Points:Side Quests and Experimentation (01:16-08:30)Andy builds a habit tracker that evolved into a doom-scrolling prevention appPete experiments with media over QUIC and real-time streaming protocolsThe power of AI to remove gatekeeping from learning new technologiesBuilding an Nostr-based virtual pub with spatial audioVibe Coding vs. Slow Coding (09:38-16:13)Insights from working with serious engineers on AI-assisted developmentEveryone uses AI differently - no single "vibe coding" workflowThe importance of understanding your codebase architectureMoving slower to go faster: maintaining intuition while delegating implementationBuild vs. Buy: The Shopify Question (14:25-25:06)Andy's journey building an e-commerce site from scratch instead of using ShopifyThe value of understanding how things work vs. convenience of platformsLocalization of software development - kids will build these things nativelySelf-reliance as a valuable use of AI-gifted timeShipping Tools People Can Use (25:06-33:00)The critical lesson: put working demos in users' handsPlans for multiplayer Wingman to lower barriers to experimentationDesigning the business into Wingman - mapping workflows and agentsTesting at Bush Bash with live coding sessionsOrchestrators vs. Deterministic Processes (33:00-38:52)Why probabilistic orchestrator agents often fail in productionThe case for simple, deterministic workflow rulesLeft curve vs. mid curve: sometimes simpler is betterHumans should still design the business processesRate Limits and Model Selection (38:52-42:43)Claude Haiku as a solution to usage limitsRunning agents via API for unlimited usageMultiplayer mode for sharing subscriptions efficientlyThe challenge of making complex technology accessibleSimplifying the Message (42:43-48:31)Beacon demo: focus on the "moment of magic" not the complexity"Solvatur Ambulando" - solve it by walking aroundWingman's unique value: anywhere access + multiplayer agentsDon't let ego get in the way of clear communicationAI Agents Playing Games (48:31-59:09)Using game environments to test model performance for business applicationsGames as sandboxes for learning resource allocation and strategic thinkingBeyond single-agent approaches: teams of specialized agentsGeneral Catalyst's investment in gaming arenas for model testingMultiple Minds Per Task (55:13-01:01:38)Humans have multiple personalities for different contextsAgents may need similar specialization to avoid being overwhelmedFile-based handoffs between agents as a clean interfaceThe power of forcing agents to document their reasoning"Mid curve me is just like 'oh I've been so clever' - but that's not for the person on the other end that wants to look at it."

The Good Stuff, with Pete and Andy - Episode 26: Beyond CodingHosts: Pete and AndyEpisode Overview: Pete wraps up Sovereign Engineering's final week while Andy discovers Claude Code's surprising versatility beyond coding. The hosts explore multi-agent orchestration, Nostr ecosystem developments, and the expanding use cases for AI agents in everyday business tasks.Key Discussion Points:Claude Code for Non-Coding Applications (01:30-08:00)Andy shares his revelation about Claude Code's effectiveness beyond programming tasks, including organizing financial records, preparing taxes, and restructuring Apple Notes into Obsidian. The tool excelled at extracting action items from scattered notes and even analyzed a 100-page DNA report to create a personalized diet plan. Discussion of why Claude Code feels more capable than Claude Desktop for complex tasks, potentially due to different system prompts optimizing for autonomous operation versus interactive sessions.Multi-Agent Architecture and Wingman (08:00-12:00)Pete describes building agent orchestration systems where Wingman calls other specialized agents through local APIs. Beacon now integrates Wingman for complex research tasks, automatically determining when to use web search or other tools. The vision includes abstracting recipes and MCP servers to switch between Claude Code, Codex, Goose, and Gemini based on task requirements.AI for Content Optimization (12:00-16:00)Andy experiments with using Claude Code to analyze podcast YouTube data, discovering which thumbnail text styles drive better click-through rates. YouTube's built-in A/B testing capabilities for thumbnails revealed. Discussion of the resistance to over-optimizing content for platforms like LinkedIn versus the authentic engagement on Nostr.Nostr vs. Traditional Social Media (16:00-19:00)Pete's viral post on Primal contrasts with the performative nature of LinkedIn. Both hosts appreciate Nostr's ability to provide meaningful content without the dopamine-driven engagement loops of traditional platforms. The five-minute check-in versus the endless scroll.Sovereign Engineering Demo Day Prep (19:00-31:00)Pete showcases progress on WhatsApp Bitcoin integration with Lightning payments, emphasizing the "hook" of seamless crypto in mainstream messaging. Rebuilt gateway architecture to support multiple networks. Tired on the Field game adds skydiving cows, laser eyes, and Nostr login for persistent leaderboards. Other notable demos include Context VM servers, Gigi's Amps semantic search, local-first relay architecture, DNS alternatives using public key infrastructure, and BitChat's offline Bluetooth mesh for protest coordination.Andy's Project Portfolio (31:30-38:00)Building Supply Drop, a standalone e-commerce brand using Shopify with third-party manufacturing APIs. Developing a podcast knowledge graph with Neo4j to track recurring themes and philosophical evolution across episodes, aiming to create an interactive agent for exploring the show's intellectual journey. Designing a minimalist habit tracker app that locks users into one habit for 21 days before allowing additional habits, incorporating AI accountability coaching.Future Direction (38:00-39:00)Plans for workshops on both coding and non-coding agent applications when Pete returns to Perth. Recognition that agent capabilities are poorly understood despite their power across diverse use cases.

The Good Stuff, with Pete and Andy - Episode 25: Freedom Tech & The Beacon ProjectHosts: Pete and AndyEpisode Overview: Pete and Andy reflect on their Jeff Booth conversation, exploring contradictions in AI-debt narratives. Pete unveils major progress on Beacon, his freedom tech project bringing internet access and Bitcoin payments to constrained environments via WhatsApp. The hosts debate AI coding tool frustrations and the shifting development landscape.Key Discussion Points:AI, Productivity, and the National Debt Paradox (01:35-09:55)Examining flawed logic that AI productivity gains will solve government debt. The hosts argue this ignores job displacement and debt repayment mechanics through taxation. If AI eliminates jobs while boosting productivity, governments lose salary tax revenue - accelerating wealth concentration and triggering more money printing.Gold Manipulation vs Bitcoin's Transparent Ledger (14:46-21:42)Gold price suppression through derivatives and lack of auditing contrasted with Bitcoin's audit every 10 minutes. The importance of self-custody to prevent paper Bitcoin markets. "If we all fully reserve our Bitcoin, then there will be no paper Bitcoin for these guys to trade."Bitcoin in Madeira and Nostr's Permissionless Payments (21:42-29:30)Pete shares observations from Madeira where Bitcoin acceptance has normalized. The revelation of Nostr's permissionless payments - sending value instantly without intermediaries. Andy's realization: traditional money transfers require multiple friction points; Nostr enables instant zaps.The Beacon Project: Internet Access via WhatsApp (29:30-47:10)Pete introduces Beacon for environments with no smartphones or reliable internet - only text-based WhatsApp. Beacon enables AI queries, research, and Bitcoin payments through text messages. Origin story from Togo, where internet costs were prohibitive but WhatsApp was free. The vision: delivering the entire internet via text messages to people without internet access.Beacon's Trust Architecture (47:10-58:02)Deep dive into Beacon V5 design separating identity from AI services. Two independent providers create a trust model where neither can unilaterally defraud users. Uses Context VM over Nostr for discovery and communication, eliminating firewall complexities. Challenges the custodial vs self-custodial dichotomy, creating middle-ground trust models where full self-custody isn't practical.AI Development Tool Chaos (58:02-01:12:23)Frustrations with Claude Sonnet 4.5's rate limits and inconsistent performance. Andy hits weekly limits after one day. Pete's migration to Codex and Goose, finding better consistency. The problem: opacity in which components change makes debugging impossible.Notable Quote:"Bitcoin audits the entire world supply every 10 minutes - like melting down all the gold in the world repeatedly to make sure it's legit."

SummaryIn this engaging conversation, Jeff Booth discusses the transformative power of Bitcoin and the importance of agency in shaping our realities. He explores the relationship between consciousness and the perceived world, emphasizing that our beliefs influence our experiences. The discussion delves into the natural state of the free market, which is deflationary, and how Bitcoin provides a framework for value creation and entrepreneurship. Personal journeys to Bitcoin highlight the desire for freedom and agency, while the role of AI in business is examined as a tool for enhancing productivity. The conversation concludes with insights on the future of work, the necessity of flexibility, and the importance of making conscious choices in a rapidly changing world.TitlesUnlocking Agency: The Power of BitcoinConsciousness and Reality: A Bitcoin PerspectiveSound bites"The jail cell door is open.""You have the choice. We all have agency.""The world is going to be a chaotic place."Chapters00:00 Introduction to Jeff Booth01:57 Agency and Consciousness in Bitcoin05:43 The Role of Mind in Reality10:36 The Filter Bubble and Agency12:34 The Importance of Perception16:22 Personal Journeys to Bitcoin19:12 The Zero-Sum Game vs. Infinite Game23:19 The Challenge of Bridging Two Worlds28:25 The Future of AI and Bitcoin30:38 The Impact of AI on Business39:19 The Illusion of AGI46:55 The Role of Entrepreneurship in a New Economy51:27 Building Value in Bitcoin01:01:06 The Future of Work and Value Creation01:09:11 Conclusion and Future OutlookKeywordsBitcoin, agency, consciousness, deflation, entrepreneurship, AI, value creation, free market, perception, realityTakeawaysAgency in the world allows individuals to create their desired reality.The perceived reality is shaped by individual consciousness and beliefs.The natural state of the free market is deflation, which benefits everyone.Bitcoin provides a new framework for value creation and entrepreneurship.Personal journeys to Bitcoin often stem from a desire for freedom and agency.The zero-sum game mentality limits growth and understanding of Bitcoin's potential.AI and Bitcoin can coexist and enhance each other's value.Entrepreneurs must adapt and reinvent their businesses to thrive in a changing economy.The future of work will involve more flexibility and creativity in problem-solving.Building value in Bitcoin requires a shift in mindset from traditional financial systems.

The Good Stuff, with Pete and Andy - Episode 23: Left Curve Solutions and AI Implementation ChallengesHosts: Pete (from Madeira) and Andy (from Perth)Episode Overview: Pete and Andy explore the challenges with AI tooling reliability, the philosophy of "left curve" solutions over complex engineering, and why most enterprise AI pilots are failing. The discussion covers Nostra protocol development, business implementation strategies, and the ongoing debate between bionic human versus human-at-the-edge AI integration models.Key Discussion Points:**Nostra Protocol Development and Decentralized Applications (04:00-25:00)**Pete shares updates from Madeira on building decentralized applications using Nostra protocolDiscussion of "bring your own database" concept - Nostra KV Connect for private company dataBenefits of distributed data storage versus centralized honeypots vulnerable to hackingIdentity portability and cryptographic authentication as core value propositions**Craig David Bot Demo Project (22:00-25:00)**Pete's weekly demo challenge: building a bot that analyzes your week using Nostra eventsIntegration with payment systems and automated research capabilitiesFuture plans for video generation with custom music overlays**Claude Code Performance Issues (25:00-40:00)**Widespread reports of Claude Code degradation affecting productivity across the development communityAnthropic's explanation of "three interlocking bugs" affecting token routing and limitsDiscussion of alternatives like Wingman, Goose, and maintaining control over AI tooling stackThe shift from 100x productivity back to 90x productivity as a "first world problem"**Left Curve Solutions Philosophy (40:00-46:00)**Concept borrowed from Sovereign Engineering: avoid mid-curve over-engineeringExamples from Bitcoin e-cash development where simpler solutions (Fedimints, eCash) succeededThe tendency to over-complicate due to ego and "tall poppy syndrome"Focus on minimal viable approaches rather than proving technical sophistication**Enterprise AI Pilot Failure Analysis (46:00-58:00)**MIT study showing 95%+ failure rate for AI pilots in large organizationsRoot causes: poor scoping, misunderstanding of technology capabilities, bureaucratic implementationLack of genuine problem identification and systems thinking approachThe consulting industrial complex extracting fees without delivering value**ROI Measurement Challenges (58:00-1:05:00)**Traditional additive ROI models don't capture compounding AI benefitsExample: document review automation leading to faster deals, new service offerings, market expansionNeed for longer-term measurement frameworks beyond quarterly reporting cyclesHidden individual AI usage versus official pilot programs**Build vs Buy Strategy Discussion (1:05:00-1:12:00)**Opportunity to capture market share while incumbents struggle with implementationTime advantage for building AI-native solutions while large companies run ineffective pilotsPath dependency question: bionic human as stepping stone to human-at-the-edge modelsRole-dependent optimal human placement in AI-augmented workflows**Implementation Philosophy**"Full left curve solutions" - prioritizing simplicity and function over complexity"We're not here to fuck spiders" - focus on meaningful problems, not technical masturbationThe "dog with two dicks" problem - AI tools that code aggressively without proper planning

The Good Stuff Podcast - Bitcoin, Nostr and Sovereign EngineeringHosts: Pete and Gigi (walking around Funchal, Madeira)Episode Overview: A walking conversation exploring Bitcoin circular economies, eCash payment systems, Nostr's permissionless internet vision, and AI's impact on business transformation.Key Discussion Points:Journey to Madeira and Initial Motivations (02:00-10:00)Guest's discovery of the No Solutions podcast and the Calle eCash episodePrevious work in eCash space and early Lightning Network skepticismWorldview centered on individual control and localism over centralized institutionsBitcoin Adoption Reality in Madeira (10:00-22:00)200+ merchants accepting Bitcoin across the islandSeamless payment experience - "just another payment method" for merchantseCash and Payment System Evolution (22:00-35:00)AI services driving demand for micro-payments and permissionless APIsThe "Netflix problem" of subscription fatigue across serviceseCash enabling true "lemonade stands" in cyberspace without KYC barriersSolving the chicken-and-egg problem through prepayment modelsNostr as Internet Infrastructure (35:00-50:00)Cryptographic identity and money as native internet protocolsReplacing username/password systems with permissionless accessJapanese Nostr communities as example of organic self-organizationMoving beyond the "app player renaissance" toward true peer-to-peer systemsAI Business Transformation Strategies (50:00-1:15:00)Debate over AI as incremental tool vs. fundamental paradigm shiftReal-world business automation in rental management and service industriesThe cost of building vs. buying existing businesses for AI transformationHuman role shifting from process center to "edge interfaces"Local vs. Global Community Building (1:15:00-1:28:00)Relocalization enabled by AI reducing dependence on Silicon ValleySovereign Engineering cohort as proof-of-concept for prototype-driven developmentNostr enabling global communities with local trust relationshipsBitcoin businesses emerging organically from community connectionsOptimism and Future Outlook (1:28:00-end)Choosing optimism as pragmatic approach to uncertaintyTechnology tools creating new possibilities for permissionless innovationThe importance of meaning and human agency in an automated worldNotable Quotes:"Pre-Bitcoin, it was basically impossible to do a lemonade stand in cyberspace.""Everything's a remix. That's why I don't like copyright. It just doesn't exist.""Stop being sick and just be awesome instead - that's how you get better very quickly."

The Good Stuff, with Pete and Andy - Episode 21: Remote Vibe Coding & AI Agent OrchestrationHosts: Pete and Andy (first remote recording - Pete traveling, Andy at the beach)Episode Overview: Pete and Andy explore advanced AI agent workflows, the evolution of AI coding tools, and strategies for building sustainable development practices while Pete is away doing "vibe coding and freedom tech" work.Remote AI Development & Wingman Evolution (03:00-15:00)Pete demonstrates how geographic separation enhances AI-powered development, using his Wingman system to continue building while traveling. Discussion of voice-driven ideation versus typing, and the cognitive benefits of speaking ideas into existence without syntax distractions.Trigger-Based Automation & Overnight Jobs (15:00-25:00)Introduction of Wingman's new trigger system allowing file-based automation and scheduled tasks. Pete's breakthrough with overnight security reviews using "Grug Brain Developer" principles to audit code changes and identify complexity concerns while he sleeps.Claude Code vs. Goose: The Dual-Agent Approach (28:00-32:00)Analysis of using different AI models for different cognitive tasks - Claude Code as the enthusiastic "drunk writer" for rapid development, Goose as the thoughtful "sober editor" for planning and documentation. The "dog with two dicks problem" of Claude Code's over-eagerness to build.Documentation Architecture & Anti-Slack Philosophy (32:00-40:00)Strong critique of chat-based interfaces for knowledge work. Pete's systematic approach to moving valuable insights from chat conversations into structured Obsidian documentation, and why real-time messaging tools damage business focus and inspiration.AI Agent Loop Problems & Root Cause Analysis (41:00-50:00)Technical discussion of when Claude Code gets stuck in debugging loops due to hard-coded values and scope creep. Solutions include using different AI models for root cause analysis and implementing background auditing agents to catch coding mistakes.Design-First Development & Planning Orchestration (50:00-59:00)The importance of spending more time in ideation and design phases before coding. Discussion of missing orchestration tools to convert comprehensive documentation into manageable work packages, and the trade-offs between YOLO development and structured planning.Segregated Computing: Using dedicated machines for AI development provides security and eliminates local environment dependenciesVoice-Driven Ideation: Speaking ideas creates more fluid thought processes compared to typing with its syntax distractionsOvernight Labor: AI agents can provide 16 hours of cleanup and maintenance work while humans sleepDual-Agent Strategy: Different AI models excel at different cognitive tasks - planning vs. executionDocumentation Philosophy: Structured knowledge systems beat chat interfaces for long-term value creation"If I can buy a bucket of cognition for $1 instead of $100,000, why is the truck that big? What changes?""I feel like it's evolved from an expensive SaaS to a cheap worker. If you said you can hire somebody for a hundred dollars a month, you'd be like, yeah, that's excellent.""I don't want the robots to give me nice documents on a plate and serve them to me as I sit in my armchair. Come on guys, if we're going to have robot labor, why are we going to these great lengths to make it easy for them?""Everything's just like in Slack and you have to constantly chase people to figure out versions because nothing's being managed in a sensible way anymore."

The Good Stuff, with Pete and Andy - Episode 20: Wingman - your AI Control Tower!Hosts: Pete and Andy (recorded at City Beach, Perth)Episode Overview: Pete unveils his breakthrough AI agent orchestration system "Wingman" - a Mac Mini-based control center for managing multiple AI agents simultaneously. The discussion explores custom-built solutions versus SaaS subscriptions, testing AI models through games, and the emerging paradigm of humans as "control tower operators" for AI systems.Opening & Context Setting (00:00-01:48)Andy returns from illness for episode 20Final beach recording before Pete's mysterious Atlantic adventureReflecting on recent guest episode with BethanneThe Wingman Revolution (01:48-25:00)Pete's Mac Mini experiment: giving AI agents their own dedicated computer environmentEvolution from basic setup to sophisticated web-based control systemMultiple agent orchestration: Goose and Claude Code working in parallel sessionsRemote access from anywhere - phone, laptop, or desktopObsidian integration for documentation and artifact storageAPI endpoints for automated session creation and workflowsAgent-to-Agent Workflows (20:00-25:00)Return-to-base protocol for session completion and handoffsWebhook systems enabling autonomous agent chainsVision of fully automated code review and development cyclesMoving from human-centered to machine-centered processesCustom Tools vs. SaaS Fatigue (25:00-40:00)Economics of $15/month software subscriptions adding upPete's approach: "Fast fashion for software" - build exactly what you needYouTube reel generator case study: custom-built vs. existing solutionsThe open-source developer superpower now accessible via AIManagement-Style AI Interaction (40:00-50:00)Transition from "button-pushing" to strategic oversightUsing specialized agent personalities (Grug Brain Developer for code reviews)Dueling agents: building features in parallel and choosing the bestPlanning and auditing as core human value-addGaming as AI Benchmarks (50:00-01:09:00)Settlers of Catan as model testing environmentGame mechanics as proxy for enterprise negotiation and resource managementTabletop wargaming automation conceptsTesting strategic thinking, negotiation, and long-term planning capabilitiesThe Control Tower Paradigm (01:09:00-01:13:00)Humans as air traffic controllers for AI agent fleetsMultiplayer mode implications for teamsTerminology evolution: logbooks, flight plans, control towersDedicated AI Environments: Running agents on isolated hardware eliminates privacy concerns while providing full system access and persistent operation.Agent Orchestration Architecture: The future involves managing 1-100 agents simultaneously across different projects and functions, requiring sophisticated coordination systems.Custom vs. Commercial Software: AI development capabilities are shifting the economics from subscription services to custom-built solutions tailored to specific workflows.Human Role Evolution: The transition from direct execution to strategic oversight and agent management represents a fundamental shift in how knowledge work gets done."I don't have a good way of explaining how just fucking nice this is" - Pete on Wingman's seamless operation"The data is in the computer. You were in the computer. Talk to it." - Pete on the future of AI interaction"It's the same way that junior developers fuck stuff up... we just need to use the same processes" - Pete on managing AI agents"Fast fashion for software" - Andy's description of rapid custom tool developmentLooking Ahead: Pete's system represents a glimpse into the future of human-AI collaboration, where individuals can operate sophisticated agent networks from anywhere, fundamentally changing the nature of knowledge work and business operations.

The Good Stuff - Episode 19: The Human EdgeHosts: Pete and Bethan WinnLocation: City Beach, PerthEpisode Overview: Pete hosts with special guest Bethan Winn, his wife and author of "The Human Edge: Critical Thinking in the Age of AI." They explore the intersection of human thinking and artificial intelligence, discussing when and how to use AI tools while maintaining human agency and creativity.Book Link: The Human Edge: Critical Thinking in the Age of AIKey Discussion Points: Introduction and Book Launch (01:01-04:00)Bethan discusses her motivation for writing "The Human Edge" making critical thinking training more accessible as AI becomes ubiquitous. Her five years of corporate training experience revealed growing need for critical thinking skills in the AI era.The Writing Process (04:00-07:00)First-time author experience, early morning writing sessions, and using dictation to capture ideas. The challenge of moving from workshops to written format with AI assistance.AI as Cognitive Offloading (07:00-12:00)Comparison to historical abstractions like GPS replacing map knowledge and software development layers. The "AI veganism" concept - consciously choosing when to use AI versus manual processes for different purposes.Pete's AI Development Experiments (12:00-18:00)Multi-agent conversations, facilitator roles, and panel discussions between different AI models. Discovery that AIs can generate genuinely new concepts through interaction, challenging assumptions about creativity.Human vs AI Creativity (18:00-25:00)Debate about manufactured music, authenticity, and the value of creative processes. Whether AI-generated content diminishes human artistic expression or simply changes the distribution landscape.Critical Thinking in Practice (25:00-32:00)Using AI conversationally to challenge thinking rather than replace it. The book's focus on structured conversations and frameworks for better decision-making.The Value of Difficulty (32:00-40:00)Importance of uncomfortable experiences for growth. Pete's development of mobile AI tools that enable work while walking, maintaining human movement and reflection.Knowledge Democratization (40:00-48:00)How AI breaks down gatekeeping of specialist knowledge. The shift from information scarcity to the need for better filtering and evaluation skills.Productivity and Attention (48:00-55:00)OODA loops in software development, the challenge of managing multiple projects when AI accelerates execution. Social media's impact on attention and the value of deliberate focus.Social Media Censorship Debate (55:00-01:19:00)Discussion of Australia's social media ban for children. Arguments for education over restriction, the dangers of information control, and the importance of teaching critical evaluation skills.Belief Change and Growth (01:19:00-01:26:00)The "ocean analogy" for confronting uncomfortable truths - the discomfort of changing deeply held beliefs compared to entering cold water, but the growth that follows.Human Connection in the AI Age (01:26:00-01:32:00)The continued importance of empathy and understanding different perspectives. Bethan's approach of assuming the best in people and the value of genuine human connection.Closing Thoughts:"The AI doesn't care about the outcomes that you get, but you do" - emphasizing human agency in an AI-augmented world.Book: "The Human Edge: Critical Thinking in the Age of AI" by Bethan Winn

The Good Stuff, with Pete and Andy - Episode 18: Building and ShippingHosts: Pete and Andy (recorded at City Beach, Perth - the van is back!)Episode Overview: A follow-up to their accountability session from last week, Pete and Andy report back on actually shipping products to completion. This episode covers their successes with Fat Controller and Hype Man, explores new development workflows with Claude Code, and discusses the evolution of AI-assisted coding practices.Follow-up from last week's therapy session about finishing projectsPete releases Fat Controller 20 minutes before recordingAndy gets Hype Man operational as an autonomous CMOThe importance of shipping something people can actually use and pay forBuilt to solve Pete's timezone posting problem on NostrFeatures: GIF support, satellite CDN integration, secure keychain storage (Mac only)Evolved from local-only to supporting remote signers for hosted versionRedesigned signing architecture for better remote compatibilityReleased as open source with value-for-value modelAndy's first official week on Nostr - hasn't felt compelled to check TwitterMore invigorating and motivating environmentZap payments add meaningful interaction layerLess negative energy compared to Twitter/XMulti-agent system that extracts insights from podcast transcriptsCreates and publishes social media content automaticallyIterative improvement process: removed research agent, added review agentCost-constrained testing with DeepSeek, upgraded to Claude for better outputReflection agents as key pattern for improving AI output qualityClaude Code excelling at small, targeted changesCursor better for complex, orchestrated implementationsClaude Code's agentic loops provide better multi-step problem solvingBoth tools serve different phases of the development processMac Mini as dedicated AI development server with 24/7 availabilityTerminal-based workflows accessible from phone via voice transcriptionMenu-driven system for common development tasksSegregated environment philosophy: give AI full access to designated machinesMobile coding: voice-to-terminal transcription enabling "vibe coding" from anywhereThree modes: drunk idea capture, sober editing, drunk codingNeed for seamless idea-to-implementation pipelineTutorial mode: AI explaining reasoning behind architectural decisionsBalancing speed vs learning in AI-assisted developmentDanger of spending more time optimizing AI workflows than building actual products"Sharpening the axe forever" - when process improvement becomes procrastinationFinding balance between efficiency and productivityDebate: Transform existing businesses vs. build AI-native competitorsUnit economics advantage of AI-native companiesVenture funding opportunities for dramatically improved cost structuresPrivate equity interest in AI transformation strategiesWeekend project to replace Screen Studio subscriptionReal-time vs post-processing architecture decisionsPart of broader strategy to reduce SaaS subscriptions and build local toolsWorking prototype with keyboard shortcuts and lightweight toolbar interfaceVision for idea-to-prototype pipelineSpeed Run workshop concept: build entire company in one dayIntegration of existing tools (Pipeline, Wingman, Claude Code) into cohesive workflowVibe startups: from idea to launched product with full departments

Hosts: Andy and Pete (recorded on the balcony at an undisclosed location)Episode Overview: Pete and Andy explore the challenges of shipping projects in the age of AI, discussing their experiences with Claude Code, the paradox of infinite possibilities versus completion, and strategies for moving from ideation to deployment.Opening & AI Agent Development (00:00-12:00)The hosts discuss Pete's "Hypeman" project - an autonomous agent that ingests podcast transcripts, conducts web searches, and tweets throughout the day. They explore the challenges of managing Claude Code's tendency to over-engineer solutions and add unnecessary features.Claude Code vs Planning Environments (12:00-24:00)Discussion of using different environments for planning versus execution. Claude Desktop for read-only planning and code review, Claude Code for implementation. The "dog with two dicks" analogy - Claude Code's overwhelming enthusiasm to build everything immediately rather than following structured plans.The Old Bull and Young Bull Framework (24:00-30:00)Pete and Andy introduce their management philosophy for AI agents: needing both the enthusiastic "young bull" (execution agent) and the wise "old bull" (planning/orchestration agent) to achieve optimal results.The Completion Problem (30:00-40:00)Deep dive into the challenge of finishing projects when AI makes starting new ones so easy. The dopamine hit of new ideas versus the grind of deployment. Recognition that they're developing sophisticated vibe coding setups but struggling to ship finished products.System Development vs Product Shipping (40:00-50:00)Exploration of whether time spent refining AI coding systems is valuable capital development or procrastination. Discussion of calendarizing projects and creating external deadlines to force completion.Cost Optimization in AI Agents (50:00-56:00)Pete shares how iterating on Hypeman reduced costs from $20-30 per transcript to 50 cents by strategically using different models (DeepSeek vs Sonnet 4) for different tasks.Social Media Strategy & Nostr Focus (56:00-01:08:00)Comparison of engagement across platforms - genuine human interaction on Nostr versus bot-heavy Twitter. The value of being able to send sats for valuable content. Discussion of LinkedIn's corporate facade versus Twitter's AI innovation content.The Australian Tech Landscape (01:08:00-01:14:00)Concerns about government surveillance, economic dependency on government spending, and the contrast with AI's promise of infinite leverage for entrepreneurs.Action Items & Accountability (01:14:00-01:15:36)Commitment to ship projects by next episode. Plans for content recycling tools and increased Nostr presence. Recognition that shipping, not starting, is their bottleneck."The cost of doing something goes to zero, then the only real constraint you have is what you should do.""I feel like the bit that makes it the wrong idea is the opportunity cost... we just narrowed that window down to a few hours.""You've got to go and spend all your time and energy in the system that you want to win."Next episode will feature accountability check-ins on shipped projects and progress on deployment systems. The hosts commit to focusing on completion over ideation.Episode Theme: The challenge isn't building with AI - it's knowing what to build and actually shipping it.

# The Good Stuff Episode 16 - LLM Subscriptions, Goose AI Agent, Beacon & Bitcoin**Summary:** In this episode, hosts discuss subscription-based AI services and their rate limits, sharing their frustrations with Claude and Cursor's recent policy changes. They explore their personal workflows using various AI tools for coding, writing, and idea development, discussing the benefits of using multiple specialized tools versus all-in-one solutions. The conversation concludes with an in-depth look at "Beacon," a project designed to bring AI tools and Bitcoin functionality to users in areas with limited internet access through platforms like WhatsApp.## Key Themes:**Subscription Models and Rate Limits in AI Services** (00:00 - 27:00)- Discussion of Claude implementing weekly rate limits- Comparison with Open AI's subscription model- The economic realities of providing AI services- Issues with communication and "bill shock" when companies change terms**Personal AI Tool Workflows and Setups** (27:00 - 50:00)- The hosts' approaches to using different AI tools for specific purposes- Discussion of Claude desktop vs API performance differences- Challenges with integration across different platforms- Running local models on dedicated hardware**Agent-Based Writing Tools and Philosophy** (50:00 - 73:00)- Building dialogue-based writing companions versus editing tools- The importance of focusing on the philosophy behind writing- How agent-based conversations can help develop ideas more effectively- Creating systems that don't interrupt creative flow**Vibe Coding and Game Development** (73:00 - 84:00)- Using voice-based coding for game development- The potential of AI for nostalgic game recreation- Making coding more accessible through voice interfaces- Teaching coding through game development**Beacon: AI and Bitcoin for the Underserved** (84:00 - 1:14:00)- Introduction to Beacon, a system bringing AI and Bitcoin to users via WhatsApp- How it works around censorship and limited internet access- Creating community financial tools for areas with limited banking- The importance of bringing information freedom to underserved populations

Episode 15- Moar Vibe Coding Talk!Summary: In this episode, Andy and Pete discuss their evolving coding workflows with AI tools, focusing on how Claude Desktop and Cursor have created more structured and efficient development environments. They share insights about implementing sequential prompting methods, organizing work in Obsidian, and using AI-driven panel discussions to explore ideas. The conversation highlights how AI tools are changing their approach to productivity and shifting focus from execution to more fundamental questions about project purpose.00:11 - 05:47: Improved AI Coding Workflows Discussion of Claude Desktop for ideation and technical planningImplementation of sequential prompting with validation checksCreating structured folder systems in Obsidian for better organizationExample of 3GS scene development using this workflow05:48 - 11:00: "Vibe Coding" vs Structured ApproachesComparing different coding approaches with AI assistanceBenefits of implementing checks and balances in code generationCreating change logs and indexes to track progress across projectsHow this system helps manage multiple concurrent projects11:01 - 15:36: AI Environment ImprovementsDiscussion of GitHub MCP setup for code checkingBenefits of super whisper for voice controlPlans to run local models on a new Mac MiniUsing Goose as an agent on dedicated hardware15:37 - 23:23: AI Panel Discussions for Knowledge GenerationUsing AI agents to have conversational exchanges about topicsHow dialogue between AI models can generate new insightsTesting different models (Claude, Grock) to identify bias patternsValue of these synthetic discussions for idea exploration23:24 - 31:20: Shifting Focus from Tasks to PurposeDiscussion about capturing organizational knowledge from meetingsThe limitations of task-focused productivity toolsHow AI automation shifts focus from execution to purposeThe importance of asking "why" rather than just "what" and "how"

# Episode 14: Vibe Coding that works!In this episode, the hosts discuss their development of "slow code," a more intentional approach to coding with AI that contrasts with "vibe coding." They explore how this methodology creates a structured workflow combining human planning with AI execution, resulting in higher quality code while maintaining the speed benefits of AI assistance.## Key Themes:**Understanding Vibe Coding** (00:02:20 - 00:08:00)* Vibe coding involves speaking instructions to AI and ignoring the underlying code* Democratizes coding by allowing anyone to build in natural language* Major downside: potential security issues and poor code quality**Evolution to Slow Code** (00:08:00 - 00:19:40)* Hosts developed methodologies through experimentation with AI tools* Initial frustrations with existing AI coding tools led to refinement* Slow code combines intentional planning with AI execution**Three-Phase Methodology** (00:19:40 - 00:25:30)* Ideation: Using Claude Desktop for exploration and brainstorming* Planning: Converting ideas to structured documents and roadmaps in Obsidian* Execution: Having AI implement based on detailed specifications**Tools and Implementation** (00:25:30 - 00:40:00)* Using Obsidian for planning and documentation* Connecting to AI tools via MCP (Model Context Protocol)* Root Code for implementation with orchestration capabilities* Benefits of separating environments for different phases**Multi-Agent Conversations** (00:40:00 - 00:51:00)* Creating pipelines where multiple AI agents discuss ideas* Using different models (Claude, Grok) to avoid single-model biases* Value in seeing how ideas develop through agent conversations**Benefits of Slow Code** (00:51:00 - 01:01:30)* Creates reusable, higher quality code versus one-shot vibe coding* Maintains human intentionality and design control* Still much faster than traditional development* Parallels the "write drunk, edit sober" approach to creative work**Future Applications** (01:01:30 - 01:15:00)* Integration with Goose for continuous development and scheduling* Creating dedicated AI development environments* Applications beyond coding (writing, research, analysis)* Plans to share methodology through tutorials and community**Contrasts with No-Code Tools** (01:15:00 - 01:26:00)* Visual no-code tools add unnecessary complexity* Slow code leverages AI's strengths while maintaining human oversight* More flexible than constrained visual interfaces

Episode 13 - Creativity and Summoning AI like a ShamanHosts: Andy and Pete Guest: Gav Fielding (Digital Marketing & Brand Specialist, Artist) Exploring AI's creative potential, the art of prompt engineering as digital shamanism, and how traditional creative processes translate to the age of artificial intelligence.AI Development Evolution (00:00-08:22)Cursor IDE billing changes and the shift from "slow coding" to "vibe coding"Return to "super fast waterfall" development with AI agentsContext window limitations: quality vs quantityHuman vs AI Context (08:22-15:55)The challenge of replicating human contextual understanding in AIMulti-personality aspects of identity and AI agent development"Things you know" vs "things you are" in AI persona creationVision and sensory data as the next AI frontierLearning Transformation (15:55-24:12)Khan Academy's personalized AI math tutoringTailoring communication styles to individual learning preferencesChatGPT's tutor mode: guided discovery vs direct answersVoice interface challenges in natural conversationCreativity as Process (24:12-35:20)Creativity as a "volumes game" generating many ideas to find exceptional onesAI raises both floor and ceiling of creative outputThe "doorman fallacy" - losing tacit knowledge through naive automationPersonal AI tools outperform organisational implementationsPurpose in an Abundant World (35:20-46:48)When everything is automated, purpose becomes the key differentiatorBrand strategy increasingly important with commoditized intelligence- Balancing automation benefits against loss of meaningDavid Graeber's "bullshit jobs" in AI contextCreative Problem-Solving (46:48-55:06)Engineering vs creative solutions (Rory Sutherland's elevator mirror example)Market research challenges: people can't articulate true needsThe difference between mechanical and psychological solutionsDecentralization & Community (55:06-58:14)AI enabling hyper-localisation and community based solutionsShift from centralised to localised innovationEvolution toward gig economy with community co-working hubsShamanic Prompt Engineering (58:14-1:18:43)Prompt engineering as modern "shamanism" summoning digital entities"Set and setting" for AI interactions, borrowed from psychedelic methodologyMulti-agent conversations for enhanced ideationTools like Mind Hive for collaborative AI workshopsCreative Methodology (1:18:43-1:27:54)Hemingway's "write drunk, edit sober" frameworkSeparating ideation from judgment in creative processesUnderwater brainstorming for forced creative breakthroughsDivergent vs convergent thinking statesDigital Summoning (1:27:54-1:39:34)AI requiring careful "birthing" and context settingTraditional shamanic practices informing modern AI interactionThe art of "enchanting" AI with proper incantationsStandout Quotes"Creativity is just a volumes game. You have more ideas. Some of them are good, some of them are bad, and you filter them all out.""It's almost like layering in pre-modern medicine... the clash between those applied to AI now versus current life versus future AI life.""We're all shamaning this thing. And we're just giving it a bad trip.""There probably is like a way of... maybe it's all in occult books around summoning demons. It's actually just got mis-translated over the years. And it was actually all about context engineering."

The Good Stuff, with Pete and Andy - Episode 12: AI Myths and the Future of Work as PlayHosts: Pete and Andy (recorded at City Beach, Perth)Episode Overview: Pete and Andy explore common AI myths and misconceptions, diving deep into interface design, the productivity vs creativity paradigm, and how work might evolve to resemble play in an AI-enabled future.Reflections on Guest Episodes (00:00-03:20)Dynamic of having guests vs. just the two hostsPreference for discussion format over structured interviewsOrganic conversation flow versus scripted contentThe "I Trained the Model" Myth (03:20-10:30)Misconception between fine-tuning vs. adding context/documentsMost "training" is actually just attaching PDFs or system promptsLLMs should handle interface, not factual recallContext engineering as the superior approach over model trainingSmall vs. Large Language Models (10:30-16:30)The "Ferrari for grocery shopping" mentality - overusing frontier modelsSmall language models as the better choice for repetitive commercial workflowsCost and speed advantages of smaller models for specific tasksModular approach: using right-sized models for different pipeline stepsInterface Design Myths (16:30-27:30)Chat as the default AI interface limiting potentialNeed for adaptive interfaces suited to different working stylesMicroservices architecture finally becoming economically viable with AIMoving beyond monolithic "big model for everything" approachFlow State and Adaptive Interfaces (27:30-39:00)Spreadsheets as example of adaptive, durable toolsVisual vs. text-based collaboration preferencesThe ramp-up/ramp-down challenge when returning to complex projectsMultiple input/output modalities for different contextsHuman Collaboration Patterns (39:00-48:00)Engineers gravitating to whiteboards for collaborationThe canvas as shared workspace vs. individual thinking spaceVoice, visual, and collaborative interfaces serving different needsBalancing real-time interaction with persistent documentationCreativity vs. Productivity Paradigm (48:00-58:00)AI as creative enabler rather than just productivity boosterThe scary prospect of agency - having to decide what to work onEmbodied human experience as irreplaceable for insight generationExamples from Rory Sutherland: mirrors in elevators, train comfort over speedThe Future of Work as Play (58:00-1:08:00)Moving from medieval peasant schedules to office work and back to leisureWork resembling exploration and experimentationThe role of craft and embodied skills in an AI worldVictorian gentlemen as preview of future leisure classError Tolerance Double Standards (1:08:00-1:14:00)Unrealistic expectations for AI accuracy vs. human error ratesNeed for same systems and processes, just faster iteration cyclesHuman mistakes tolerated due to context; AI mistakes seen as fundamental flaws"It's not the job of the model to know stuff... the best way to get good factual core from these things is context engineering.""Why are you in a hurry? Take your time. Be really comfortable. We'll get rid of the plebs." - On reframing problems"The future's here, it's just not evenly distributed" - Applied to leisure and creative workBottom Line: AI myths persist because people experience AI through limited interfaces and apply unrealistic error expectations. The real opportunity lies in modular, adaptive systems that enable work to become more play-like, with humans focusing on embodied creativity and meaning-making while AI handles decomposed tasks.

The Good Stuff - Episode 11 Show NotesSummaryIn Episode 11 of The Good Stuff podcast, hosts Pete and Andy welcome their inaugural guest, Joel Pember, brand director and co-founder of Juicebox. The conversation explores Joel's journey from photography to digital marketing, diving into philosophical discussions about AI's impact on creative industries, the evolving nature of brand and taste in an AI-driven world, and the future of agencies in a rapidly changing digital landscape.Introduction (00:00-02:00) Intro to our first-ever guest, Joel Pember, brand director of JuiceboxJoel's Background in Photography (02:50-06:30)Joel discusses his start as a photographer and the philosophical aspects of photo mediaExplanation of Magnum Photographers and the artistic side of photography beyond technical skillsAI's Impact on Photography and Creative Industries (06:30-11:00)Discussion about how AI might affect artistic expression and photographic storytellingReflection on the difference between AI-generated images versus images with lived experienceAI Ethics and Leadership (11:00-18:30)Sam Altman's open letter and the weight of responsibility on AI leadersDebate about governance versus innovation in AI developmentThe need for more philosophical and ethical conversations around AIGovernment Regulation vs. Organic Development (18:30-25:00)Discussion about regulation of technology (social media bans for children)Debate about centralized control versus free markets and bottom-up solutionsHow younger generations will adapt to and potentially circumvent restrictionsEconomic Pressure and Social Considerations (25:00-30:40)How economic pressures limit people's ability to engage with bigger questionsDiscussion about inflation, debt, and the impact on younger generationsThe need to question existing systems and consider alternativesBrand Value in an AI World (30:40-40:00)The evolution of social media platforms from connection to algorithmic discoveryHow brand value might increase in an era of AI-driven abundanceThe role of brands as shortcuts for trust and qualityThe Nature of Taste and AI as Taste-maker (40:00-50:00)Discussion about how taste is formed and whether AI can develop authentic tasteThe role of lived experience in developing taste versus algorithmic recommendationsCultural waves and how brands ride the zeitgeistThe Future of Agencies and Customer Experience (50:00-01:02:00)Joel explains how digital agencies have moved from the fringe to the center of brand strategHow customer experience and technology are replacing traditional advertisingThe role of AI in transforming how brands connect with customersAgency-to-Agency Interactions (01:02:00-01:15:30)Exploring how AI agents might interact with each other on behalf of humansDiscussion about hyper-localization and the shift away from global monocultureJoel's vision for Juicebox as designing meaningful connections between brands, people, and intelligent systemsConclusion (01:15:30-01:17:00)Reflection on the conversation and plans for future episodesJoking about making all future guests use the "Joel sprite" in their visualization

Show Notes: Episode 10 of "The Good Stuff"In this tenth episode of The Good Stuff, hosts Pete and Andy discuss how AI is transforming product development, business creation, and work. We explore how the falling cost of creation enables faster product-market fit testing, the future of venture capital, and the rise of multi-agent AI systems. Podcast Updates and Announcements (00:56-07:13)The hosts celebrate reaching episode 10Shout-outs to podcast supporters including Crispy, BundabergHodl, and BTCShellingPoint. Mention of Bethans upcoming book "The Human Edge" about critical thinking and human skills in an AI worldAI and the Changing Nature of Business Creation (07:13-15:17)Discussion of the Presidio Bitcoin podcast (PBJ)How AI is making engineering less important than product-market fitThe ability to rapidly test multiple ideas with minimal costProduct Market Fit and Personal Alignment (15:17-27:53)The importance of "product-founder fit" and choosing problems you genuinely care aboutReduced sunk cost bias when experimenting has lower costsHow energy and interest in a problem are better guides than purely tactical decisionsScott Adams' skill stacking concept applied to the AI eraHyper-Localization and the Future of Business (27:53-40:00)- The rise of hyper-local solutions built by people who understand specific markets"Proof of punch in the mouth" the trust advantage of local businessesPotential "death of B2B SaaS" as local solutions become more viableHow AI might transform interfaces between humans and business servicesBitcoin, Capital, and Long-term Value Preservation (40:00-55:43)Discussion of how Bitcoin fits into business strategy in an AI worldThe "up, up, down" methodology (margin up, capital up, risk down)How Bitcoin provides a way to preserve value in an uncertain futureThe trade of the next decade: "Use AI to earn more money now and keep it in Bitcoin"Multi-Agent AI Systems and UI Evolution (55:43-1:15:00)Experiences with Roo Code and orchestrating multiple AI agentsThe limitations of current chat interfaces that require human directionVision for more opinionated AI agents that drive interactions forwardFuture UI as high-agency AI that can maintain context and memory

The Good Stuff, with Pete and Andy - Episode 9: Tools, Tools, ToolsHosts: Pete and Andy (with bonus ambient drum and bass from a nearby camper van)We dive deep into the practical tools we're using for AI development, exploring the difference between AI as tools versus human-at-the-edge workflows, and discussing the technical complexity of building local AI systems.Key Discussion Points:The Cold Open: Screen Time and Digital Minimalism (00:00-05:52)**Pattern Matching vs. Reasoning in AI (07:00-17:20)Apple's recent paper questioning whether LLMs truly "reason" or just do sophisticated pattern matchingHow thinking models workThe relationship between human thought and AI pattern matchingHow AI systems handle novel problems and the role of entropyAI Tools in Practice (18:50-32:00)Why Cursor has gained such traction compared to alternativesThe importance of context management and local file accessPete's experience with OpenAI's Codex vs. local tools like Cline and CursorThe dopamine feedback loops that make certain tools more engagingLocal vs. Cloud AI Systems (30:00-40:00)The benefits of running AI systems locally rather than in web appsAvoiding the complexity of SaaSHow local processing leverages your computer's existing power and storageThe privacy advantages of keeping personal data on your own machineMemory and Knowledge Graphs (38:52-50:00)The limitations of basic RAG (Retrieval Augmented Generation) systemsIntroduction to graph RAG systems that provide richer contextHow Stakwork uses self-improving graph databases for better AI performanceThe importance of solving the "memory problem" for effective AI systemsLLMs as translation layers between human language and structured dataPersonal Knowledge Graphs (50:00-58:00)Pete building a personal knowledge graph systemUsing Docker containers and API interfaces for local AI developmentThe challenge of managing context across multiple AI tools and workflowsBethan's book "The Human Edge" Building AI Systems: Technical Complexity (58:00-01:10:00)How accessible it is for non-developers to build AI systems with current toolsThe "slow code" approach: treating development as a learning experienceApply Git liberally!Andy's experiments with N8N for workflow automation and content creation pipelinesWorkflow Automation vs. Autonomous Agents (01:16:00-01:22:00)Comparing deterministic workflows to autonomous agentsWhy most business tasks are better suited to static workflowsThe role of humans in AI systems: providing intent and experienceEnumeration vs. abstraction: building specific workflows rather than trying to create universal solutionsDevelopment Stack and Tools (01:13:00-01:16:00)Pete's current toolkit: Cline, Visual Studio, O3, Claude, Codex, Code, Personal Graph....Plans for a local Nostr-based ebook reader with cross-device syncingPaying for all the tools!Conspiracy Corner: Moon Mysteries and Dead Internet Theory (01:25:00-01:35:00)Discussion of moon landing anomaliesDead Internet Theory and how algorithms shape both content creation and consumptionThe decline of film qualityAI-generated content and the future of creativityKey Quotes:"The job of the LLM isn't to be everything... what LLMs are specifically good at is translating stuff into and out of human language""The price of bullshit is also dropping to zero""We're not here to raise low agency children!""Everyone loves a sausage!"

The Good Stuff, with Pete and Andy - Episode 8: The Golden Age of EntrepreneurshipPete and Andy explore how AI is creating unprecedented opportunities for entrepreneurship and individual agency, examining both the positive transformations and personal risks in this transitional period.Key Discussion Points:Opening & Technical Difficulties (00:00-05:53)The boys lost their "finest podcast ever recorded" due to technical issues!Learning to Code with AI (08:40-23:40)Andy shares his journey learning to code:Moving beyond "vibe coding" to intentional learning through project-based approachUsing AI as a technical co-founder and mentor rather than just automationStructured methodology: Planning with Claude, building with Cursor, reviewing and iteratingThe importance of staying involved in the process rather than abdicating to AIThe "Super Fast Waterfall" Development Process (18:50-22:00)Pete introduces the concept of AI-enabled development methodologyAI excels when given structured frameworks rather than open-ended tasksPermissionless Leverage and the Golden Age (36:40-45:20)Dramatic reduction in barriers to experimentation and starting businessesFrom needing teams, technical co-founders, and investor capital to solo executionShift from audience-of-millions to audience-of-one business modelsChallenging Traditional Startup Wisdom (45:20-48:40)Critique of Andreessen Horowitz founders' claim that small businesses are "meaningless"Rejection of the scale-equals-significance mentality- Benefits of lower capital requirements and venture-scale returns not being necessaryPersonal fulfillment vs. world-dominating ambitionsThe World of Abundance (48:40-55:00)Drawing parallels to the Industrial Revolution:AI as a deflationary force similar to mass production- The Value Trap creating financial incentives for disruption Competition eventually driving prices down and creating abundanceHumans as Experience and Observers (55:00-62:20)Philosophical discussion on the human role in an AI-driven world:Humans provide the "qualia" - the conscious experience AI lacksPeople identify problems and improvements while AI handles executionRenaissance-style revival where economic abundance enables pursuit of meaningful workPersonal Financial Risk in the Transition (62:20-72:00)Major concerns about individual exposure during the AI transition:30-year mortgages as problematic in uncertain employment landscapeRising interest rate environment making debt service more expensiveThe risk of being heavily leveraged without personal runwayBlue-Collar vs White-Collar Displacement (72:00-75:00)Short-term risks in traditional "safe haven" industries:White-collar displacement potentially flooding entry-level tradesImportance of finding unique personal value propositionsCreating for Yourself, Not Audiences (75:00-End)Drawing from Rick Rubin's creative philosophy:The value of non-commercial creative pursuits- AI enabling leisure and space for meaningful creative workYour job becomes experiencing life and improving its sharp edges for othersKey Insights:"This is a renaissance for entrepreneurs. If you're entrepreneurial minded, this is just a huge, an amazing time to be alive.""The cost of experimentation has just dropped precipitously and that is in general good for society.""Your job is to experience life and to realise where the sharp edges are and to improve them for everybody else."**Bottom Line: AI represents the greatest opportunity for individual agency and entrepreneurship in generations, but success requires intentional engagement with the technology rather than passive adoption, while carefully managing personal financial risk during the transition period.

The Good Stuff, with Pete and Andy - Episode 7: Rise of the GeneralistHosts: Pete and Andy (recording at City Beach, Perth)Episode Overview: In this episode, the hosts discuss automating their podcast production pipeline and explore how AI is changing knowledge work. They examine the impact of AI on jobs, explaining how it gradually automates tasks at a "subatomic" level rather than replacing entire roles immediately. The conversation delves into effective strategies for working with AI coding tools, the future of work, and why generalists with adaptable skills may thrive in an AI-powered economy.Podcast Production Automation (00:55 - 03:35)- The hosts describe automating their podcast production workflow- Their system handles audio processing, transcription, and content generation- AI tools generate show notes, article summaries, and identify potential clips- The goal is to streamline marketing efforts without manual interventionContent Generation at Scale (03:35 - 06:07)- Discussion of how automated processes save hours of manual work- Possibility of using voice cloning technology - Creating purpose-built content for different platforms from source materialKnowledge Capture in Organizations (06:07 - 10:44)- Applying similar automation techniques to organizational knowledge management- Capturing and sharing discussions across an organization- Using knowledge graphs to store company information- Creating personalized content delivery based on preferencesAI for Problem-Solving (10:44 - 15:25)- Challenging the criticism that AI can't solve novel problems- Discussion of Pablo's "Tenex agent framework" for problem-solving (https://primal.net/e/nevent1qqs227u92fagkjfwx590qe9z58m6fku9luy3tejylgwy5efz23rzndgqd0h93)- Importance of allowing AI time to work through complex problems- Comparison to human problem-solving processes that also require trial and errorAI's Impact on Jobs (23:30 - 31:20)- Examining how AI impacts jobs at a "subatomic" task level- Discussion of why people don't see their jobs as replaceable- Second-order effects of partial job automation (consolidation, wage impacts)- Historical context of technological disruption and job displacementFuture of Work in an AI Economy (31:20 - 38:35)- Debate on what jobs might remain protected from automation- Potential government responses (regulation, UBI, job programs)- Economic impacts like tax base erosion and inflation*- The shift to generalist skills in uncertain environmentsEffective AI Coding Techniques (57:30 - 1:08:00)- Strategies for working effectively with AI coding tools- Using a sequential approach rather than one-shot generation- The importance of planning before coding- Having Claude as a "project manager" while using Cursor for implementation- Balancing speed with understanding and control"Your job isn't a whole, it's 200 sub-jobs... and any one of them is automatable already given time and tooling"