3reate

Is the panic over AI data centers actually justified, or are we worried about the wrong things? Andrew and Nathan broadcast from a struggling Silicon Valley connection to dismantle the current state of AI infrastructure and corporate strategy. We dive deep into Google's confusing pivot away from developer-focused enterprise tools like Antigravity toward consumer-facing AI, questioning if a $20-per-month B2C model is actually sustainable for the compute required. The conversation then shifts to the recent New York bill pausing AI data centers. We unpack why electrical grids and water usage are secondary issues compared to the looming societal crisis of AI monopolies and unbalanced wealth distribution. You'll learn why "squeezing blood from a turnip" perfectly describes the current tick-tock cycle of foundational models like Fable and Opus. We also explore why open-source solutions—from Nvidia to international players like DeepSeek—are the only reliable defense against a completely locked-down tech ecosystem. Finally, we tackle the historical parallels of technological suppression, from Prohibition to computing, showing why democratized access is critical for the next era of software architecture. Hit play to uncover the real bottlenecks in AI development, and if you're in the Bay Area, be sure to catch Nathan’s open-source transcranial direct current stimulation exhibit at Open Sauce 2026. (00:00) Internet issues in Silicon Valley. (01:43) Google killing AI enterprise products. (04:39) Workspace AI integration and pricing. (11:05) Why AI data centers aren't the problem. (16:33) Fable vs Opus: Model efficiency compared. (23:48) AI wealth distribution and tech taxes. (30:26) The technological monopoly of AI models. (35:59) Open-source models and the future. (41:45) Nathan's exhibit at Open Sauce convention. Watch on YouTube: https://www.youtube.com/live/3IFMKzWXtK4?si=1WdT0tYjrTEurVHd Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://www.youtube.com/@3reate https://www.twitch.tv/3reate

This week, we strip away the marketing fluff to look at the practical reality of outcome-driven software development. We trace how software abstraction has evolved from raw Assembly language down to modern multi-agent architectures that coordinate dozens of concurrent tasks to isolate and fix system bugs in a matter of minutes. We dive deep into the pragmatic trade-offs of modern engineering: The Agent Calculus: Evaluating the real economics of running autonomous sub-agent loops against scaling traditional enterprise engineering teams. Self-Healing Log Infrastructure: Implementing automated QA gates that leverage AI agents to monitor, trace, and instantly patch software errors natively. Designing for LLM Hallucinations: Practical tactics for building resilient APIs that accommodate structural model quirks, such as natively handling snake case and camel case discrepancies. The New PM Mandate: Why traditional Kanban-style project management is dying, forcing senior builders to shift entirely toward market validation and strict system boundaries. We wrap up the session with a contrarian prediction for the next phase of development: a complete shift toward machine-to-machine instruction sets optimized entirely for AI processing rather than human eyes. Stop spending hours debugging individual syntax blocks and start operating as a systems architect. (00:00) Hello! (03:14) – The myth of AI coding slop. (07:15) – Why human-readable code was created. (12:55) – Fixing bugs without looking at source. (19:05) – Orchestrating context with multi-agent networks. (28:30) – Why automated customer support fails users. (45:05) – Machine-optimized code is the future. Watch on YouTube: https://www.youtube.com/live/eLn4-XA-KdQ?si=m8HeRoEbJVIqIIgG Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://www.youtube.com/@3reate https://www.twitch.tv/3reate

Every tech executive promised a world-ending AI revolution by mid-2026, but raw production data tells a completely different story. The technical landscape is drowning in marketing noise, and pragmatic builders are left dealing with the structural friction of overhyped systems. In this mid-year recap, we bypass corporate tech fluff to run a brutal code-review on our 2026 predictions across tech, science, and art. We break down the exact mechanics behind the stealth degradation of Anthropic’s Fable model—revealing how safety classifiers quietly offload heavy processing to older frameworks while charging you premium rates. We then confront the core architectural flaw destroying consumer software: forcing non-deterministic models into systems that require absolute precision simply turns your product into an expensive random number generator. Beyond the software stack, we analyze the hidden debt of data center energy monopolies, the negative feedback loops poisoning institutional science funding, and the mass creative rebellion against automated slop. If you are exhausted by agency-driven hype and need a realistic, engineering-first perspective on where technology actually stands today, this manual is for you. (00:00) Mid-year 2026 predictions recap intro. (01:02) Anthropic Fable model features and flaws. (03:49) The illusion of AI company transparency. (08:55) Real look at AR VR digitization. (12:28) The breaking point of AI ROI. (15:56) Data centers straining global energy grids. (19:44) YouTube creators challenging traditional Hollywood. (22:28) Why non-deterministic software products fail. (26:34) The broken state of science funding. (31:44) Why LLMs won't solve hard science. (37:45) The human rejection of AI slop. (48:19) Audio augmentation is the real AR. Watch on YouTube: https://www.youtube.com/live/baZJfQbP8aY?si=yBGgDXPYSPiafYOL Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://www.youtube.com/@3reate https://www.twitch.tv/3reate

Tech giants want you to believe that rising hardware and software costs are the natural side effects of an inevitable AI revolution. They are lying. Apple's recent 20% price hike on MacBooks and iPads is a symptom of a deeper structural failure: a consolidated semiconductor supply chain controlled by a tight global monopoly. When a couple of manufacturing giants dictate memory allocation, independent builders and developers pay the tax. Speculative data center proposals are booking out future fabrication capacity based on promissory notes, ignoring the hard physical realities of an aging energy grid that cannot even supply the power to turn them on. This artificial demand spike isn't just inflating consumer tech; it is threatening edge compute and the open-source tinkering culture that built the modern internet. In this breakdown, we look closely at the raw mechanics of chip architecture, the operational friction of hardware scarcity, and why software is about to lose its historic deflationary edge. If you are building for the future, you can no longer ignore the physical constraints of the hardware you rely on. Learn how to navigate the upcoming infrastructure crunch before soaring cloud bills compromise your product architecture. Chapters: (00:00) US soccer historical record milestone. (03:25) Gripes with mandatory hydration breaks. (07:50) Monopolies and predatory event ticketing. (13:30) The truth behind Apple's price hike. (16:45) Chip architecture and supply constraints. (29:45) Compute scarcity threatens open innovation. (32:20) Rising cloud costs hit software. (44:00) Speculation and fake AI demand. Watch on YouTube: https://www.youtube.com/live/oD5jF7F-NSs?si=9RW1NzGtj1e50hTx Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://www.youtube.com/@3reate https://www.twitch.tv/3reate

Every builder feels the friction. We are transitioning out of a highly predictable system into a technical landscape dominated by hyper-specialized bottlenecks, bloated bureaucracies, and compounding architectural debt. Legacy frameworks are breaking down because current leadership models are fundamentally incompatible with reality, leaving pragmatic engineers trapped in a cycle of algorithmic noise and unverified promises. This episode strips away the hype-beast tech tropes to focus on the raw mechanics of modern execution. We map the historical trajectory of open frameworks—from their decentralized military origins to the current open hardware ecosystem—and reveal why extreme professional sub-contracting has broken complex systems. As software transitions into a commoditized race to the bottom driven by heavily subsidized AI platforms, the true competitive edge belongs to generalists who control their stack vertically. We break down the practical realities of managing your own local-first pipelines, combining customized software with durable, 3D-printed hardware components, and navigating defensive industry standards that operate primarily as gatekeeping institutions. Take back control of your operations. Unplug from the algorithmic feed, drop the screen fatigue, and align your everyday workflow with concrete, independent execution. Chapters: (00:00) Moving the live stream to Thursdays. (00:50) Navigating existential dread and industry burnout. (03:33) The reality of generational leadership shifts. (09:45) Shifting from predictable to intentional planning. (12:05) The extreme overselling of AI capabilities. (17:10) How algorithmic feeds amplify collective anxiety. (21:00) Practical strategies for unplugging from screens. (24:05) Forcing leaders to deliver execution timelines. (26:20) Aging establishments running modern digital infrastructure. (35:10) Historical origins of the open-source movement. (44:00) How outsourcing risk breaks complex systems. (47:35) Returning to a generalist workflow model. (50:05) Marrying custom hardware with local software. (54:10) Outdated regulatory standards throttling modern builders. (58:35) Distinguishing actual progress from arbitrary change. Watch on YouTube: https://www.youtube.com/live/ycmO_QntWM0?si=0tVErvELKesB2hvk Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://www.youtube.com/@3reate https://www.twitch.tv/3reate

The corporate marketing machine claims Anthropic's new Claude Mythos 5 and Claude Fable 5 architectures change everything. Builders know better. In this episode, we strip away the high-energy tech fluff to pressure-test Claude Fable 5 against actual, complex development workflows, bypassing synthetic benchmarks to examine the raw execution mechanics. Andrew walks through a brutal 20-hour case study using a massive automated agent swarm to refactor a proprietary coding platform interface—burning over 10 million tokens in the process. We break down exactly where Fable outperforms older tiers (specifically graph-based engineering tasks, architectural layout logic, and deep, multi-page technical planning frameworks) and identify exactly where it flatlines into expensive redundancy. We also unpack the highly restrictive safety guardrails currently kneecapping the ecosystem, examining the friction that occurs when a premium model silently offloads your security audits to older foundation tiers without explicit warning. Finally, we map out practical token-budgeting strategies to shield your workflow from compounding API debt, contrasting Anthropic's terminal-centric approach against Google's emerging tool suite. (00:00) We're baaaaaack (00:41) Naming chaos of Anthropic's new models. (01:57) Maximizing value through heavy token usage. (02:22) Breaking down Mythos versus Fable architecture. (03:02) Real-world failures of AI image generators. (07:56) Fable shines in complex conceptual mapping. (10:48) The power of deep planning documents. (15:07) Rebuilding an interface using agent swarms. (25:32) Strategic token budgeting for technical workflows. (31:38) Anthropic vs Google: Interface design philosophies. (40:03) Frustrations with overly aggressive safety guardrails. Watch on YouTube: https://www.youtube.com/live/nK3KfodwiVk?si=X7nNhUMi1k38Mlm8 Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://www.youtube.com/@3reate https://www.twitch.tv/3reate

When a tech startup hits rapid growth, the operational foundations almost always begin to crack. Founders frequently over-index on shiny enterprise software or push teams to experiment blindly with AI, creating a fragmented mess of disconnected workflows. The result isn't true innovation—it's operational debt and AI vibe slop. This episode strips away the corporate tech fluff to deliver an intensely practical breakdown of startup architecture with Christina Twitchell, founder and CEO of Her Wealth Mindset and CLT Collective. We dive deep into why traditional operations consulting handoffs fail scaling companies and how embedded, hands-on fractional operators bridge the execution gap. You will learn the exact distinction between a consultant who hands over a playbook and an operator who executes it, the true strategic mandate of an effective Chief of Staff, and how to stop over-indexing on tech tools when a simple process is what your business actually needs. Beyond the corporate grid, we challenge the standard metrics of wealth and time, offering a pragmatic framework to audit your weekly 168 hours to reclaim focus and control. Whether you are navigating a Series A transition or trying to pull back from an unorganized, company-wide AI implementation, this conversation serves as your tactical guide to building what lasts. Christina Twitchell founded CLT Collective (https://www.linkedin.com/in/christina-twitchell-5a545345/) after 10+ years scaling operations at companies like Block, ZipRecruiter, and Infusionsoft. Building first-of-kind functions, redesigning organizations mid-flight, and leading teams through the kind of complexity most consultants only advise on from the outside. Her work spans Strategy, Chief of Staff, Revenue and Customer Operations, Operating Model and Org Design. She specializes in the build phase — standing up what doesn't exist, fixing what's broken, and creating the infrastructure that makes growth sustainable. Her Wealth Mindset is a financial education platform built on a simple belief — real wealth includes your money, your time, your health, and your relationships. Tools and resources to help women build all of it, intentionally. Follow the journey @her_wealthmindset (https://www.instagram.com/her_wealthmindset/) Chapters: (00:00) Episode Preview. (00:56) Meet Christina Twitchell, multi-business founder and mother. (01:27) Empowering women through financial literacy platforms. (02:06) Providing fractional operational services for tech. (03:45) Aligning wealth building with personal values. (05:47) Cutting through intentional financial system confusion. (11:10) Defining foundational operations in tech startups. (13:03) Fractional operators versus traditional consulting models. (19:57) Deploying chief of staff roles effectively. (31:26) Avoiding over-engineered startup software infrastructure traps. (34:52) Fixing the unscalable AI vibe slop. (36:18) Organizing messy company-wide AI implementation strategies. (39:26) Predicting the upcoming AI ROI pullback. (46:29) Auditing your weekly hours for empowerment. Watch on YouTube: https://youtu.be/3CZyVGONWOM?si=tD59jn-fj3vYRbNw Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://www.youtube.com/@3reate https://www.twitch.tv/3reate

The conversation around artificial intelligence always seems to center on a singular anxiety: our power grid is going to collapse under the weight of AI data centers. But what if the environmental panic is just a distraction from a much deeper structural failure? In this episode, we strip away the surface-level hysteria regarding data center liquid cooling systems and energy consumption. While critics compare data centers to toxic manufacturing plants, the real friction lies in our legal and economic architecture. We are attempting to govern a 21st-century information economy using 20th-century zoning laws and traditional property tax frameworks. When a physical factory opens, it employs thousands of locals who buy groceries, pay income taxes, and stimulate the local economy. When an AI data center opens, it creates massive virtual value that is immediately extracted back to Silicon Valley, leaving the host community with a handful of jobs and a strained infrastructure. We break down the mechanical realities of closed-loop cooling, explore why standard server use-taxes are fundamentally broken, and offer actionable regulatory solutions—from mandatory grid-positive energy contributions to localized AI education credits. Stop letting outdated policies drain your community's resources. Tune in to understand the true cost of compute and how to fix it. Time stamps: (00:00) Stream intro and chatting with viewers (00:47) AI power requirements and resource realities (02:22) Debunking data center water consumption myths (03:29) How liquid cooling systems actually operate (06:00) Power density challenges of modern GPUs (09:21) Google's AI algorithm for data center cooling (12:24) Microclimate changes around Oregon data centers (17:14) How data centers impact local grids (21:14) The real problem with data center taxation (24:53) Economic extraction versus local community value Watch on YouTube: https://www.youtube.com/live/6hYEnx0gjL8?si=QEhckY1uA8sh6eqk Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://www.youtube.com/@3reate https://www.twitch.tv/3reate

The Department of Defense—recently rebranded as the Department of War—launched a public repository detailing decades of unexplained anomalous phenomena (UAP). This isn't corporate tech fluff or sensationalized clickbait; it is millions of pages of raw, institutional data capturing objects that appear to bend the known laws of physics. In this episode of 3reate, we bypass the typical screaming media hype to look at the engineering reality behind these tranches. If these crafts are genuinely instantaneous accelerators capable of crossing water-to-air boundaries without drag, our foundational physics models are fundamentally broken. However, as builders, we have to look at the alternative: are we simply witnessing complex hardware edge cases and buggy next-generation sensors tracking unprecedented atmospheric patterns? We dissect the deep-seated human ego driving the narrative of alien reverse-engineering. Disassembling space-time bending architecture isn't a problem solved by a few people in a clandestine lab—it requires an infrastructure humans cannot currently fathom. If a civilization mastered limitless energy to travel light-years, why would they crash in our backyard, and why would they care about a primitive nuclear ant colony? We map out the massive economic shifts that true infinite energy would unlock, from completely upending global supply chains to rendering resource constraints obsolete. (00:00) Hello! (01:17) Breaking down the war.gov disclosure website. (11:47) Why AI companies backtrack on AGI (14:32) Why advanced military sensors record anomalies. (23:35) Critical thinking: sensor errors versus physics. (31:35) The technical arrogance of reverse-engineering claims. (44:58) Deconstructing the Drake equation's massive flaws (52:50) Infinite energy and the motivation problem. Watch on YouTube: https://www.youtube.com/live/k75_HvlMqcI Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://www.youtube.com/@3reate https://www.twitch.tv/3reate

Tech layoffs are spiking again, and executives are pointing fingers at AI. It’s a convenient narrative designed to cover up years of reckless over-hiring and structural debt. If you are tired of the corporate fluff and unverified "trust us, bro" capabilities coming out of OpenAI, Anthropic, and Google, this breakdown is your intellectual palate cleanser. We introduce a simple philosophical frame to instantly de-hype any narrative: replace the word "AI" with "computer" and see if the panic holds up. From there, we expose the mechanics of automated code vulnerability scanning. While tech giants claim their new systems can secure the web, the reality is that AI-generated slop is effectively DDoS-ing open-source maintainers with unexploitable gravel instead of real software fixes. Finally, we follow the money. Discover why venture capital funds and tech leaders are driving the hype cycle toward massive initial public offerings (IPOs), why the goalposts for AGI will miraculously shift once those cash-outs hit, and how soaring data center and compute costs are already forcing enterprise companies to quietly restrict their token usage. Time Stamps: (00:00) Hello! (00:52) Tech layoffs use AI as scapegoat. (01:47) The simple philosophical computer test. (02:45) Unverified security claims from tech giants. (08:52) Open source choked by AI slop. (17:08) Following the money behind AI IPOs. (21:58) Rising compute costs break product ROI. Watch on YouTube: https://www.youtube.com/live/0bj4QpXmWyk?si=r_sUx9L4_hCN5FSJ Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://www.youtube.com/@3reate https://www.twitch.tv/3reate

In this episode, we tackle the growing exhaustion surrounding forced AI integration. From sleep apps that confidently hallucinate your biometrics to the broader societal impacts of online fabrication and clickbait, we explore exactly what happens when technology gets in the way of actual utility. We also look at the human side of the equation: why do comfortable teams stop innovating? Why has a culture of perfectionism replaced the scientific method of trial, error, and iteration? By drawing parallels between the high-stakes problem-solving of early rocket science and today's software development, we unpack how the fear of failure paralyzes progress. You'll discover why constraints often breed the most creative solutions, how to recognize the apathy trap in your own workflows, and why seasoned AI developers are the ones actively telling companies to stop putting AI into absolutely everything. If you're tired of useless tech trends and want to get back to building things that actually work, this conversation is your blueprint. Watch on YouTube: https://www.youtube.com/live/0UOrBCjAMJ8?si=fLUhYsBHWHq9JVdx Time Stamps: (00:00) Hello! (01:25) The true danger of clickbait and rage-baiting online (05:50) How comfort and lack of constraints kill workplace innovation (11:50) The perfectionism trap stopping engineers from problem-solving (14:20) Accidental innovation: What the invention of Velcro teaches us (19:35) Forced AI: A hilarious rant on a sleep app hallucinating data (23:45) Why an actual AI developer wants AI out of consumer products Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://www.youtube.com/@3reate

Is code really holding your team back, or is it your organizational structure? With AI empowering individuals to build faster than ever, traditional tech bottlenecks are rapidly disappearing. But as individual output skyrockets, a new problem emerges: keeping everyone moving cohesively in the same direction. In this episode, Andrew and Nathan dive deep into why the real AI bottleneck isn't your code—it's your people. They unpack the pitfalls of modern management, the death of the traditional product roadmap, and why context is the most valuable currency when working with both human developers and AI agents. From the dangers of "vibe coding" everything without focus, to the hard truth that your company's true moat is now organizational rather than technical, this conversation challenges everything you know about building software in the AI era. Stop letting outdated management styles and unclear roadmaps slow down your development. Whether you're a solo builder or running a massive tech team, understanding these organizational shifts is crucial for survival. "The bottleneck was never the code" by Rémi Louf: https://www.thetypicalset.com/blog/thoughts-on-coding-agents Watch on YouTube: https://www.youtube.com/live/rz-IX4WjRB4?si=n-_djUUZOC7cv712 Time Stamps: (00:00) We're live on Thursday!? (01:15) The bottleneck was never your code (03:35) AI accelerates individuals, not whole teams (06:40) The value and pitfalls of management (11:50) Roadmaps limit learning and product direction (21:35) Context is gold for human workflows (25:10) Focus means learning to say no (28:30) Vibe coding creates abstract spaghetti code (31:35) The new moat is purely organizational Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://www.youtube.com/@3reate

As AI-generated noise floods our social feeds, big platforms are effectively throwing up their hands and declaring "slop bankruptcy." Today, we explore the friction between technology and society with Devin Gaffney, CEO of Graze Social, who is fundamentally rewiring the attention economy. We dive into the architecture of outrage, the illusion of "credible exit" in federated networks, and how his company, Graze Social, acts as a "Photoshop for algorithms." You'll learn why platforms are designed to trigger "forest fires" of engagement, and how empowering individual users to design and monetize their own custom feeds might be our best defense against the coming wave of AI slop. Stop consuming the hype and start understanding the mechanism. Devin Gaffney is CEO and Co-founder of Graze Social, a platform for custom algorithms on the open social web that has served 10M+ users and delivered 28B+ posts. His career spans civic tech and social platforms — from misinformation research at Northeastern and Oxford to ML infrastructure at Meedan — with work in WIRED, The Atlantic, and PLOS One. Find Devin: https://www.graze.social https://www.devingaffney.com/ LinkedIn: https://www.linkedin.com/in/devin-gaffney/ Watch us on YouTube: https://youtu.be/WmQA7uNHj54 Time Stamps: (00:00) Episode Preview: Automating behavior on social platforms. (01:47) Devin's background in tech and academia. (08:23) Exploring Blue Sky. (11:00) Understanding the decentralized social networking model. (16:45) How outrage fuels the attention economy. (25:55) Graze: Building custom algorithms without code. (34:15) Developing an open ad network economy. (45:40) AI's impact on social media algorithms. (51:10) Big tech platforms declaring slop bankruptcy. (58:55) Cognitive bias and the outrage machine. Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://youtu.be/2wEMD8EvB9I?si=G3iUBE-z4Mx0Ng-Y

We tackle the elephant in the room: Data Governance. Andrew and Nathan sit down to unpack the real "AI Mindset" necessary for the modern creator, developer, and executive. We move beyond the hype of flawless AI automation and dig into the messy reality of the software development lifecycle. From fixing memory management crashes caused by AI-written code to understanding why an LLM needs you to hold its hand through every context shift, we explore what it actually takes to build reliable tools alongside artificial intelligence. Is your proprietary data actually as sacred as you think it is? We deconstruct the hoarding mentality that paralyzes companies and offer actionable frameworks for exposing your data models securely. Whether it's safely utilizing foundational models or bridging the friction between gatekeeping IT departments and eager product managers, this episode provides the blueprint for scaling AI responsibly. AI Data Governance Executive Summary: AI Data Governance is currently misunderstood as a strictly technical challenge when it is primarily a cultural and management problem. Organizations artificially throttle their own AI potential by treating all internal data as sacred, highly proprietary, and untouchable. True AI governance requires taking a realistic inventory of your data's actual value, dismantling internal IT gatekeeping, and finding secure ways to empower non-technical teams. By exposing data schemas rather than raw PII and fostering an environment of psychological safety, companies can securely leverage foundational models to multiply their workforce's productivity. Key Points: Reevaluate Data Sanctity: Companies default to hoarding data, but executives must ask hard questions: Is this data actually unique? What happens if it leaks? Do we even need to be collecting this PII in the first place? Expose Schemas, Protect Raw Data: You don't always need to feed sensitive data into an LLM to get value. Empower employees by exposing the data model or schema to the AI, allowing it to write queries and build reports without ever touching the underlying raw data. The "Build vs. Buy" Trust Factor: If you already trust third-party enterprise vendors with your cloud hosting or IT security, you can likely trust foundational AI model providers by implementing proper enterprise agreements and boundaries. Governance is a Management Issue: Employees hoard data and block AI integration when they lack psychological safety. If your culture punishes people for making mistakes or breaking things during experimentation, they will refuse to adopt the AI tools necessary to scale the business. The AI Mindset Executive Summary: The "AI Mindset" requires a fundamental shift away from expecting perfection or "magic" from generative AI. Because generative AI is inherently non-deterministic, it will inevitably hallucinate or introduce bugs—much like traditional software development. To succeed with AI, creators and engineers must treat the technology like a highly capable but completely uncontextualized collaborator. This means embracing an iterative loop of prompting, applying critical thinking to manage edge cases, and focusing on the massive productivity gains of "what could go right" rather than being paralyzed by what could go wrong. Key Points: Embrace Non-Deterministic Outputs: Generative AI is not a deterministic calculator; it operates on statistics. If you spend all your time trying to force it into rigid deterministic filters, you defeat the purpose of using it. The Context Deficit: Unlike humans who carry vast amounts of implied cultural and institutional knowledge, AI only knows exactly what you tell it in its current context window. You must explicitly set the stage, outline contraindications (what not to do), and explain the "why." Master the Iterative Loop: Building with AI requires a constant cycle of zooming in and zooming out. You must focus the AI on a narrow, specific problem (like a login screen), and then zoom out to critically think about how that fix impacts the broader system. Critical Thinking is the Ultimate Skill: AI cannot self-prompt effectively. It requires a human in the loop who can anticipate edge cases, ask hard questions, and steer the creative or developmental process. Watch on YouTube: https://www.youtube.com/live/IEb1_aAHo9I Time Stamps: (00:00:00) Pre-show banter and minor technical difficulties (00:01:45) Why Gen AI fails customer-facing products (00:05:30) Transitioning AI proof of concepts into production (00:10:00) Debugging AI code and unexpected edge cases (00:15:45) Giving up the expectation of AI perfection (00:17:40) Focusing on what can go right instead (00:22:00) Understanding why AI lacks human implicit context (00:24:45) Mastering the iterative loop of AI prompting (00:36:05) Reevaluating the true value of internal data (00:41:30) How to expose data models to AI safely (00:45:40) Why data governance is a management problem (00:51:00) Using AI tools to multiply worker productivity (00:55:45) Wrapping up with fun May Day triviaAI Mindset and AI Data Governance? Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://www.youtube.com/@3reate

Right now, the tech world is caught in an endless loop of throwing massive compute power at Large Language Models, hoping brute force will magically spark Artificial General Intelligence (AGI). But what if the foundational computing architecture is entirely wrong? In this episode, we sit down with Ian Hamilton, CEO of Synthetic Cognition Labs, who is walking away from standard models to build true AGI. Ian dismantles complex ideas, detailing why current AI is essentially faking memory and why the path forward lies in hyperdimensional computing. By exploring the friction between biology and technology, we examine how mapping the neural networks of a fruit fly provides a better roadmap for continuous learning than a billion-dollar GPU cluster. You'll learn the critical difference between LLM tokenization and human "analogy-making," and why breaking the AI scale monopoly might require us to nuke everything we know about computing and start over. If you are tired of the AI buzzword salad and want to decode the future, this is your blueprint. Follow Ian: https://www.linkedin.com/in/ianchamilton1/ Check out: https://syntheticcognitionlabs.com/ Watch us on YouTube: https://www.youtube.com/watch?v=Rd0SpOb5gMo Time Stamps: (00:00) Preview (00:58) Ian's introduction (04:15) Why static LLMs fail at continuous learning (07:14) The coding loop and AI memory walls (16:30) Hyperdimensional computing and non-Von Neumann architecture (17:44) Biological inspiration from fruit fly neural networks (24:00) Sparse distributed memory and human-like analogy (39:20) Bridging the hardware gap with LLM emulation (51:40) The danger of the AI scaling monopoly Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://youtu.be/2wEMD8EvB9I?si=G3iUBE-z4Mx0Ng-Y

What do a broken toilet on a lunar spacecraft and the catastrophic Chernobyl nuclear disaster have in common? They both serve as ultimate masterclasses in how we handle complex systems and critical information. In this episode, Andrew and Nathan dive into a recent NASA launch, highlighting the fascinating reality of troubleshooting space plumbing on a live, global broadcast. While it might seem embarrassing, that baseline of absolute transparency is exactly why humanity can successfully reach the moon. We juxtapose NASA's open problem-solving with the fatal secrecy of the Soviet Union's nuclear program, where ego, covered-up design flaws, and siloed data led to one of the worst human-made disasters in history. Whether you are writing code, leading an interdisciplinary team, or building the technologies of the future, hoarding information guarantees failure. We explore why the corporate "cover-up" culture halts progress, the undeniable power of open-source development, and how publicly owning our mistakes is the only way to build true collective wisdom. Listen now to uncover why humility, integrity, and honesty remain the most important tools in any creator's toolkit. Stop consuming the hype and start understanding the mechanisms of progress. Subscribe to 3reate for more deep dives into the friction between science, technology, and art! Watch on YouTube: https://www.youtube.com/live/vOOvv3xtsTQ?si=RQxnU4dq7XdbXMZL Time Stamps: Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://www.youtube.com/@3reate

Has your casual scrolling turned into an unbreakable habit? You're not alone, and it's certainly not by accident. Recent landmark court rulings have declared that platforms like Meta and YouTube intentionally design their systems to be highly addictive. The era of innocent social media is officially over. In this episode, we dive deep into the legal and psychological reckoning currently facing the tech industry. We explore the hidden architecture of recommendation algorithms, detailing how they trap users in endless echo chambers, prioritize watch-time over truth, and fuel bizarre conspiracy theories. We also tackle the terrifying rise of AI-generated content and deepfakes. With the "uncanny valley" rapidly disappearing, we are entering a digital landscape where seeing is no longer believing. How do we navigate a world where digital trust is fundamentally broken? We discuss the urgent, counter-intuitive need to return to physical, analog verification systems to combat fraud. Finally, we provide a practical blueprint for breaking free from the infinite scroll. Learn how to handle digital withdrawals, set intentional boundaries, and replace toxic platform engagement with meaningful routines. Understand the invisible forces fighting for your attention. Hit play to decode the algorithm, and subscribe for more deep dives into the friction between technology and human psychology! Watch on YouTube: https://www.youtube.com/live/6oQ9wGegnec Time Stamps: (00:00) We're Live?! (00:10) Social media legally ruled intentionally addictive. (01:55) Questioning YouTube's role as social media. (05:25) Recommendation algorithms push users toward conspiracies. (11:20) Science versus belief in modern conspiracies. (14:50) AI disinformation and the shrinking uncanny valley. (16:15) Why we desperately need analog trust systems. (20:05) The real danger of gating powerful AI. (23:45) Actionable strategies to break digital addictions. Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://www.youtube.com/@3reate

We dismantle the AI layoff excuse. We explore why executives who are separated from the daily work are using artificial intelligence as a smokescreen for over hiring and poor strategy. From the differences between conversational and agentic AI to a breakdown of the abrupt Digg.com beta shutdown, we reverse-engineer the realities of the modern tech ecosystem. We go beyond the headlines to provide a blueprint for the future. You'll learn why AI is an amplifier that requires rigorous human processes, not a magic bullet that can run a company on autopilot. We explain why the practitioner is more valuable than ever in catching AI hallucinations, refining that final 20% of complex code, and building exceptional products. If you want to survive the hype and learn how to actually leverage AI as a 10x tool without losing your mind, hit play. Time Stamps: (00:00) The absurdity of tech's AI layoff excuse. (01:28) Generative versus agentic AI workflow differences. (04:21) Scaling AI code versus traditional software engineering. (06:40) Why non-technical managers misunderstand AI capabilities. (12:00) Burning it down: The paradigm shift reality. (14:30) AI isn't magic; human validation remains essential. (18:48) Digg.com's abrupt shutdown and the myth of AI moderation. (26:00) How to actually build software and PRDs using AI. (30:50) AI as an amplifier for developer productivity and noise. Watch on YouTube:https://www.youtube.com/watch?v=reWfqWk85mo Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://www.youtube.com/@3reate

We’ve engineered a world of unparalleled comfort, but at what cost? From the stagnation of the US healthcare system to the fragility of our agricultural crops, our societal resistance to "deviance" is quietly setting us up for failure. In this episode, we unpack the dangerous illusion of monopolies and monocultures. We trace how systems originally designed for massive "zero-to-one" growth—like the national power grid or the tech dominance of Intel and AMD—become vertically integrated traps that stifle true innovation. When the switching costs feel too high, it is easy to stay on a sinking ship just because it's familiar. But you don't necessarily have to burn it all down to build something better. We explore the architectural blueprints for change: why building parallel systems beats waiting for collapse, the historical necessity of sharing innovation dividends, and why true diversity is the ultimate survival strategy against systemic failure. Step out of the comfort zone and start building the future. Subscribe for weekly deep dives into the hidden mechanisms running our world, and join the conversation in the comments below. Time Stamps: (00:00:00) Debate origins and the current global state. (00:02:44) Personality distributions and their societal impacts. (00:10:00) Why the US healthcare system resists change. (00:13:54) Monocultures fail: the danger of zero deviance. (00:23:43) Building parallel systems instead of burning down. (00:29:31) Utility monopolies and the Cuba power crisis. (00:34:16) Tech duopolies: the Intel and AMD stagnation. (00:38:58) Agricultural monocrops and losing natural diversity. (00:44:00) Titanic analogy: taking uncomfortable leaps for survival. Watch on YouTube: https://youtu.be/HvMpRPyEpRs?si=xdoTfUHCZp-o0pZm Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://youtu.be/2wEMD8EvB9I?si=G3iUBE-z4Mx0Ng-

Today, we reverse-engineer the mind of Michelle Plante, a hidden operator turning life's raw observations into standup comedy. From finding her comedic voice after seven years of sobriety to facing the brutal, instant feedback of a live audience, she reveals the raw human experiment of real-time performance. We also dive deep into the collision of analog habits and modern focus. You'll learn how the tactile friction of writing on physical paper engages different neural pathways than typing, forcing us out of digital loops and into the present moment. We discuss the structural blueprints for building resilience when things fail instantly, why corporate top-down mandates always backfire against human nature, and how to harness observational humor as a tool to navigate the changing landscape of creativity. This isn't just a loose conversation; it's an actionable guide. Plus, Michelle shares her simple, screen-free morning journaling protocol to ground your day before the world demands your attention. Watch us on YouTube: https://www.youtube.com/watch?v=tAEx8jVDXCo Listen to Michelle's last 3reate podcast: https://3reate.com/podcast/why-we-need-more-discomfort-and-less-ai-with-michelle-plante-ep-44-3reate/ Find Michelle: https://www.michelleplante.com/ Instagram: https://www.instagram.com/michelleplantecomedy/ Time Stamps: (00:00:00) Hello! (00:01:52) Discovering standup comedy through sobriety. (00:06:17) The neurological power of physical writing. (00:11:41) Daily journaling habits for being present. (00:16:03) Real-time feedback and building resilience. (00:26:07) Why human behavior resists top-down force. (00:30:11) Reading the room and intentional pacing. (00:37:34) The tactile art of roasting coffee. Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://youtu.be/2wEMD8EvB9I?si=G3iUBE-z4Mx0Ng-Y

In this episode, we sit down to dismantle the "always-on" tech culture. We reveal the architecture behind "Lunchtime," a custom Model Context Protocol (MCP) server that routes secure, peer-to-peer encrypted messages through Signal. This setup allows you to text your AI agents and manage complex coding workflows entirely asynchronously, freeing you from the keyboard while ensuring you don't endlessly burn compute tokens. Beyond the code, we dive into the psychology of product sense and the friction of the creator economy. We explore the Henry Ford assembly line approach to software simplicity and why the hardest technical skill is knowing when to stop adding features. Plus, we drop the first hints about a transformative new stealth project that has been brewing since 2019. Join our community of secret masters and hidden operators of the innovation economy. Subscribe to 3reate, check the show notes to fork the open-source repo, and equip yourself with the mental models to build the future. Watch: https://www.youtube.com/live/y4ob06RwC_w Time Stamps: (00:00) Weekly updates. (02:54) Choosing Signal for secure AI messaging. (08:57) A checker loop for continuous AI agents. (11:53) Coding remotely and reclaiming personal time. (18:13) Knowing when to stop building software. (21:52) Developing product sense and gut instinct. (27:50) Teasing a new transformational stealth project. Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://youtu.be/2wEMD8EvB9I?si=G3iUBE-z4Mx0Ng-Y

In a world of AI noise, real-world innovation often gets buried under proprietary paywalls. Today we’re debuting our new "Edge Collider" format—a collaborative, workshop-style deep dive designed for the applied polymath. Instead of a passive interview, we’re putting a real-world prototype on the table. Today’s subject: Open Source tDCS (Transcranial Direct Current Stimulation). Neurological conditions like depression and anxiety remain notoriously difficult to treat, often requiring expensive or invasive clinical intervention. By open-sourcing the hardware and software protocols for tDCS, we are working to lower the barrier to entry and facilitate a "standardization of protocols" that the current scientific field lacks. In this episode, we break down: The "Edge Collider" Philosophy: Why we’re replacing "show and tell" with collaborative, high-stakes peer review. The Hardware Reality: The raw truth about building physical products, managing supply chains, and the "human labor" required to facilitate clinical science. The Open Source Paradox: Why we chose a specific license to force collaboration rather than letting our research sit stagnant in a private repository. Safety & Ethics: How we’re using firmware constraints to ensure this technology remains a tool for wellness, not a hazard. We don’t just want you to listen—we want you to build. You can find the full schematics, bill of materials, and firmware in the links below. Watch: https://www.youtube.com/live/z1ZmxE8DnhE Time Stamps: (00:00) Intro: The "Edge Collider" format (05:48) The Science of Open Source tDCS (08:42) Motivation: Why build neurological tech? (11:35) Scaling: The challenge of physical products (13:39) The hardest part of the build (17:48) Licensing: Why GPL vs. BSD matters Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://youtu.be/2wEMD8EvB9I?si=G3iUBE-z4Mx0Ng-Y

The future of software isn't just generating code—it's knowing what to build and why. We sit down with Cameron Hotchkies, a Staff Software Engineer at Block, focused on data reliability from the lens of traditional site reliability. They decode the hidden mechanics of AI-assisted development. From the meditative focus of woodworking to managing multi-agent AI systems, discover why "vibe coding" won't survive a 3 AM system crash. In a world flooded with AI noise, true engineering is no longer just about writing lines of code—it’s a survival strategy. The loudest voices claim software engineering is dead, but the hidden architects building our digital infrastructure know the truth. We go beyond loose chat to find the hard truths: What happens when "vibe-coded" AI software hits the wall of a 3 AM production crash? And why is "tech debt" actually the ultimate strategic leverage if used correctly? We explore the critical difference between disposable scripts and load-bearing architecture, the rebirth of the Waterfall method in the age of prompt engineering, and why human intuition remains the ultimate safeguard against algorithmic chaos. Cameron provides the actionable blueprints you need to navigate the rapidly changing landscape of software development and system design. Connect with Cameron on LinkedIn: https://www.linkedin.com/in/chotchkies/ or at his website: https://semisafe.com Watch: https://www.youtube.com/watch?v=07zdubQWf9s Time Stamps: (00:00) Intro (01:08) Analog hobbies: Woodworking and modular synthesizers (06:29) Rediscovering Waterfall: Research, Plan, and Implement (15:45) Why AI won't kill software engineering (18:04) Disposable AI scripts vs. load-bearing architecture (25:00) AI will not go on-call for you (41:12) Project estimation and planning with AI (48:21) Reframing tech debt as engineering leverage (01:02:24) Career wisdom: Always build in public Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://youtu.be/2wEMD8EvB9I?si=G3iUBE-z4Mx0Ng-Y

Are you keeping your startup ideas a secret? The era of hoarding concepts and relying on proprietary data moats is over. In this episode, we explore why execution beats secrecy, how AI is dismantling traditional software defenses, and the controversial future of artificial intelligence in healthcare. Stop hiding your ideas and start building the future. Are you keeping your startup ideas a secret out of fear they'll be stolen? That exact mindset might be the thing holding you back. The future isn't built by those who hide their concepts behind NDAs; it's built by those who execute. In this episode, we dismantle the myth of the "stolen idea" and explore why sharing early and often is your best strategy for iterative growth. We dive deep into the collapsing walls of the traditional "data moat." With the rapid advancement of frontier AI models, having a proprietary dataset is no longer the impenetrable defense it used to be. From building open-source podcast apps in hours to AI's capability to infer complex solutions without needing exhaustive historical data, the landscape of software and business is shifting dramatically. We also tackle the controversial and impending rise of AI in healthcare. We discuss why frontier models might soon diagnose common illnesses better than human doctors, the limitations of current systems, and what that means for data privacy and medical infrastructure moving forward. Whether you're a founder, a developer, or just trying to navigate the intersection of technology and society, this conversation provides the blueprints you need to adapt. Stop overvaluing your unexecuted ideas and learn how to leverage the new rules of innovation. Subscribe and join the discussion today. Time Stamps: (00:00) Weekend hustles and managing work-life balance (02:30) Why sharing your startup ideas matters (04:30) Building an open-source podcast sync app (08:15) Navigating the stealth product cold start (12:30) Why proprietary data moats are dying (18:20) AI code generation changes software development (25:20) The controversial future of AI diagnostics (46:40) Imputing synthetic data to fill gaps (49:00) Execution and feedback require sharing ideas Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://youtu.be/2wEMD8EvB9I?si=G3iUBE-z4Mx0Ng-Y Watch: https://www.youtube.com/live/qWEDY2_Bw-Y?si=cIgERdsC25PKQ3Tt

You're best watching this as a video since we're live coding. Watch on YouTube: https://www.youtube.com/live/WDMcmxizoCI AI tools promise to write code for you, but what happens when the build fails? In this episode, we strip away the hype and dive into the gritty reality of AI-assisted software development. Using Antigravity and Flutter, we take on a major refactor of the open-source YourPods application: adding a private, local-only user account system. We start by prompting the agent to re-architect the authentication flow, then move into the trenches of implementation. You’ll see the entire process unedited—reviewing the AI's generated "PRD," troubleshooting over 190 analysis errors, and debugging cryptic Xcode build failures. We also explore the nuances of "human-in-the-loop" development, showing you how to guide the AI when it gets stuck and how to catch the subtle logic bugs it leaves behind. Whether you're a non-technical founder trying to build an MVP or a developer looking to optimize your workflow, this session offers a transparent blueprint for shipping features using modern AI agents. Time Stamps: (00:00) Intro: Technical difficulties (02:42) Why Flutter? Explaining the tech stack and open-source goals (04:50) Tooling up: Introduction to Anti-Gravity and the AI environment (06:22) The Problem: Demoing the YourPods sync limitation (15:00) Agent Workflow: Setting up the file explorer and AI chat (21:05) Context Windows: Why you should separate features into different chats (27:52) The Prompt: Writing the specific instructions for a "Local Account" (36:50) The "Pseudo PRD": Reviewing the AI’s implementation plan (55:04) Reality Check: Hitting the first round of 190+ analysis errors (01:20:05) Build Failed: Debugging the specific Xcode "Phase Script Execution" error (01:36:38) It's Alive: Successfully creating the first Local Account (01:58:35) UX Friction: Discovering the "locked-in" navigation bug (02:04:00) Call to Action: How to contribute to the repository Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://youtu.be/2wEMD8EvB9I?si=G3iUBE-z4Mx0Ng-Y

We move past the doom-and-gloom headlines to explore the "Time Collapse"—why things we expected in years are happening in days. If AI can out-code a human, what happens to the architects of the future? Join us as we deconstruct the new "Practitioner Economy" and explain why your human judgment is now the most valuable resource on the planet. The digital landscape is currently experiencing a "Time Collapse." In this episode, we break into a live discussion already in progress to tackle a unsettling reality: the gap between AI capability and human processing is widening. With the release of Google DeepMind’s PhD-level reasoning models, the "bottleneck" has officially shifted from the machine to the human. We explore the transition from "edutainment" to "Applied Polymathy," where knowing how to code is becoming less important than knowing what to build. We dive deep into the Google DeepMind research paper, exploring how reinforced structures and dynamic context are turning LLMs into digital native citizens with superhuman capabilities. What we cover in this session: The Demigod Analogy: Why AI feels like a Greek myth come to life—extraordinary power paired with unique vulnerabilities. The Abstraction Trap: How software layers are being replaced by "Future Projections" that the human brain isn't yet wired to handle. Identity & Work: If AI can do your job better, faster, and cheaper, where do you find your purpose? We discuss the shift from "Knowledge Work" back to "Human Expression." The Engineering Myth: Why the death of "coding" isn't the death of "engineering," and how to leverage AI to solve the messy, complex problems of the physical world. This isn't just another conversation about curiosity; it’s a blueprint for the "Secret Masters" of the innovation economy. Stop consuming the hype and start understanding the mechanism. We are no longer at the precipice of the moment—we are in it. Time Stamps: (00:00) Going live mid discussion >_< (00:20) Recording an offline debate on AI. (01:31) Google DeepMind’s Deep Think model updates. (04:24) AI as an abstraction on software. (07:21) The Greek demigod analogy for AI. (10:50) Unlocking context and memory in models. (14:41) How human systems adopt technology slowly. (16:23) Reconciling work identity with AI automation. (18:30) Why coding is only part of engineering. (24:19) Global perspectives on AI sentiment shifts. (30:29) The transition from physical to knowledge work. (38:38) Replacing coding versus replacing total engineering. (41:19) AI as a massive opportunity for doers. Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://youtu.be/2wEMD8EvB9I?si=G3iUBE-z4Mx0Ng-Y Watch on YouTube: https://www.youtube.com/live/ETpFUsj1GkE?si=9XIpElR9Jg1qGR_q

The narrative is setting in: software engineering is dead. According to the leadership at Anthropic, the profession has less than a year before AI agents take the wheel completely. But for the applied polymaths actually doing the work, the reality is far more complex. In this deep dive, we dismantle the hype to find the signal. We analyze the historical parallels of the printing press and the compiler—tools that didn't destroy jobs, but radically shifted the barrier to entry. The code itself is becoming a commodity, but the "Why" and the "How" have never been more valuable. We explore why "vibe coding" fails at scale, why the cost of maintenance is the hidden killer of AI-generated software, and why the industry is pivoting from "writing syntax" to "context engineering." If you are an artist, scientist, or technologist, this is your blueprint for survival. The future won't be built by those who can write the fastest boilerplate; it will be owned by those with the taste to curate it and the architectural vision to scale it. Join us as we explore the "Application Layer"—the final frontier where human judgment reigns supreme. Chapters: (00:00) Hello! (01:55) Why software engineering evolves rather than dies. (02:50) Cyclical nature of centralized versus distributed computing. (03:55) AI builds fast, but humans must maintain. (11:00) How compilers went from impossible to trivial. (14:20) Solving solved problems versus creating novel value. (15:40) Bold claims often mask incremental model improvements. (20:30) The application layer is the next frontier. (23:40) Future engineers need taste, judgment, and experience. Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://youtu.be/2wEMD8EvB9I?si=G3iUBE-z4Mx0Ng-Y Watch on YouTube: https://www.youtube.com/live/PuM1Sp934nI

The digital landscape is shifting from chat windows to direct execution. In this episode, we dismantle the hype surrounding "OpenClaw" and the new wave of autonomous agents that run locally on your machine. While the ability to self-execute tasks sounds revolutionary, the reality involves exposed API keys, zero guardrails, and a "Wild West" security environment that most users aren't ready for. We then pivot to the bizarre phenomenon of "MoltBook"—a Reddit clone populated entirely by AI bots conversing with one another. Is this the "Boltzmann Brain" of the digital age, or just a massive waste of electricity? We explore the friction between innovation and utility, debating whether these infinite loops of generative mimicry actually produce value or just noise. Finally, we tackle the core competency of the future creative: Judgment. AI can execute, but it cannot discern. We discuss why you must never outsource your decision-making, how to experiment without breaking your bank (or your OS), and why the "Spectator" mindset is the death of true craft. Stop watching the algorithm; start mastering the tool. Chapters: (00:00) Hello! (01:36) OpenClaw: Autonomous AI agents explained. (04:54) The security risks of unprotected API keys. (09:08) Why you must not outsource judgment to AI. (15:34) How agents "hack" memory using context windows. (20:06) MoltBook: The futility of AI-only social networks. (25:31) The neurological filter: Human brain vs. AI inference. (34:39) The Spectator Problem: Passive entertainment vs. active innovation. Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://youtu.be/2wEMD8EvB9I?si=G3iUBE-z4Mx0Ng-Y Watch on YouTube: https://www.youtube.com/live/bVP-opKjawg

Stop writing lines of code, start AI Coding. Andrew shipped a fully functional, international app in just six hours—not by typing syntax, but by managing a "murder" of AI agents, AI Coding. In this episode, we dismantle the "Vibe Coding" trend and replace it with the "Abstraction Workflow," a new method where creativity and judgment replace technical rote memory. Learn how to stop coding and start architecting. The era of "Vibe Coding" is already over. If you are still trying to tab-complete your way through scripts, you are working too slow. We are witnessing the shift from the "Creator Economy" to the "Practitioner Economy," where the barrier to building software has collapsed—if you know how to manage the machine. Andrew breaks down exactly how he built and shipped "Your Pods"—a complex podcast player with Apple Watch and CarPlay support—in a single afternoon. This isn't a discussion about prompts; it is a technical blueprint for a new way of working. We explore the Abstraction Workflow, a method of splitting codebases by context rather than feature to keep AI agents from hallucinating. We discuss why you should treat LLMs not as text editors, but as a "murder of agents" with specific roles, and why "Judgment" has replaced "Syntax" as the most valuable skill in engineering. Whether you are a senior engineer looking to accelerate or a creative with zero coding experience, this episode equips you with the mental models to build software at the speed of thought. Tune in to deconstruct the future of development. Time Stamps: (00:51) Shipping a functional app in six hours. (09:06) Why "Vibe Coding" is already obsolete. (15:55) Breaking code into context-based abstractions. (20:23) Managing a "murder" of AI agents. (25:22) When AI suggests creating race conditions. (29:00) Creativity is now the ultimate technical skill. Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://youtu.be/2wEMD8EvB9I?si=G3iUBE-z4Mx0Ng-Y Watch on YouTube: https://youtube.com/live/LdRCogLCbOU

Andrew built a fully functional iOS app in six hours using AI—and got it approved by Apple on the first try. This isn't just about coding; it's a fundamental shift in how we build. We explore why the era of the "Individual Contributor" is ending and why the future belongs to those who can manage AI agents like a human team. Stop writing syntax. Start directing the machine. The barrier to software creation has officially collapsed. In this episode, Andrew breaks down how he built, polished, and published a paid iOS app to the Apple App Store in under six hours of active work. He didn’t write the code line-by-line; he managed the AI that did. We deconstruct the specific mental shift required to move from a "Coder" to an "AI Manager." We analyze how the traditional product cycle—prototyping, testing, and ticket grooming—has been rendered obsolete by "Vibe Coding," a workflow that allows for real-time feature building during user feedback sessions. Andrew reveals the specific management techniques that allowed him to bypass weeks of development hell and how he got AI-generated code past Apple’s notorious review process on the first attempt. The technical moat is gone. The new advantage is your ability to direct synthetic intelligence with creative precision. If you are still obsessing over syntax, you are already behind. Join us as we blueprint the future of the engineering workflow. Time Stamps: (00:00:55) Human creativity is now the number one skill. (00:03:00) Shifting from coding to managing AI agents. (00:05:30) Building a working prototype in three sentences. (00:08:45) Developing an iOS app in four hours. (00:11:56) Treating AI chatbots like employee delegates. (00:19:40) Rapid prototyping is now instant implementation. (00:23:23) Getting AI code App Store approved immediately. (00:28:17) Why non-creative workers will get left behind. Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://youtu.be/2wEMD8EvB9I?si=G3iUBE-z4Mx0Ng-Y Watch on YouTube: https://youtube.com/live/0CNXLEGM5aE

Is using an LLM to write documentation "cheating," or is it just the modern version of using Spellcheck? We cover: The Linux Controversy: Why open-source communities are rejecting AI, and why they might be fighting gravity. (https://www.theregister.com/2026/01/08/linus_versus_llms_ai_slop_docs) The Liability Trap: Using the Waymo "Trolley Problem" to explain why humans must remain the "Architects of Liability," even if they aren't the architects of the code. The Medical Test: A thought experiment on trust—would you care if a robot saved your life, or only if it made a mistake? Vibe Coding: The rise of non-technical programming and the security nightmares hiding inside "easy" code. The Bottom Line: Creativity is your ultimate advantage, but clinging to "manual labor" as a badge of honor is a survival strategy for the past. We strip away the drama to give you the mental models needed to navigate the age of synthetic media. Time Stamps: (00:00) Linus Torvalds bans AI documentation from Linux. (01:03) Why the tool matters less than the output. (02:22) Photoshop, Art, and the "Fake" debate. (06:05) Thought Experiment: AI vs. Human Medical Diagnosis. (08:00) Waymo, autonomous liability, and the "Trolley Problem." (09:50) The Spellcheck Defense: Are you "cheating" with AI? (13:30) Vibe Coding: Innovation or security nightmare? Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF https://youtu.be/2wEMD8EvB9I?si=G3iUBE-z4Mx0Ng-Y Watch on YouTube:

Gravity is a constraint—both for manufacturing and for your mindset. In this episode, we dismantle the physics of innovation, exploring why the next generation of computer chips must be built in space to survive. We also ground this futuristic vision in the practical tools you need today, breaking down Google’s Antigravity IDE and why the shift from “coder” to “architect” is the only way to survive the AI boom. Stop planning your year; start engineering your workflow. Most New Year’s resolutions fail because they focus on the vision rather than the execution. As we enter 2026, the gap between having an idea and building it has never been smaller—but the environment where we build is changing radically. In this episode, we explore two frontiers that are redefining what it means to be a "maker." First, we look up at the emerging "Space Forge" economy. We deconstruct why manufacturing in microgravity isn't just sci-fi vanity—it’s a logistical necessity for creating the atomic precision required for next-gen computing. We analyze how removing gravity solves defects that are physically impossible to fix on Earth. Then, we bring that concept back down to the code editor. We go hands-on with Google’s Antigravity environment for Gemini. Is it a gimmick, or does it finally offer the "Architect" workflow that developers have been waiting for? We compare the user experience directly against Claude Code, analyzing where the "Chat vs. IDE" war is heading and which tool gives the polymath practitioner the ultimate leverage. Topics Deconstructed: The Execution Trap: Why "Vision" is cheap and "Milestones" are the currency of 2026. Zero-G Fabrication: How microgravity unlocks higher yields for semiconductor manufacturing. The "Architect" Workflow: Moving from writing syntax to directing multi-agent AI systems. Gemini vs. Claude: A forensic look at context management and UI friction in the latest IDEs. The future belongs to those who can build in any environment—whether that's low earth orbit or a high-latency code base. Join us as we blueprint the tools you need to build the future. Time Stamps: (00:00) Committing to weekly live stream experiments. (01:42) Why annual resolutions fail without milestones. (05:22) Fabricating computer chips in microgravity. (09:17) Solving logistics with hyper-local space manufacturing. (12:00) Reviewing Google’s Antigravity coding environment. (15:34) Comparing Claude Code versus Gemini workflows. (20:18) The geopolitical outlook for 2026 Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF Watch on YouTube: https://www.youtube.com/live/insEOyYxV5Y?si=XDJhXhMPcCH-lYpZ

The digital landscape of 2025 was defined by a paradox: vanishing barriers to entry but exponential barriers to attention. As we enter 2026, the era of edutainment and variety shows is over, replaced by a demand for deep, specific expertise? This episode is designed for the applied polymath—the practitioner who operates at the high-stakes intersection of vision, method, and scale . Andrew and Nathan to explore why the Practitioner Economy will dominate the next twelve months. We dive deep into three critical shifts: Artistic Individualism: Why the "AI slop" wave is triggering a retreat into "smart niches" and original IP. Scientific Friction: The widening gap between breakthrough research, such as Alzheimer’s reversal, and a public psyche defined by mistrust. The Tech ROI Reckoning: Why we predict a major Fortune 100 player will finally call bullsh-t on massive AI investments that lack clear returns. 3reate is your field guide to this volatile intersection. We don't just spark curiosity; we equip you with the mental models to build the future. Stop consuming the noise and join our community of hidden operators today. Chapters: (00:00) Hello and welcome to the last pod of 2026! (00:52) Art Predictions 2026 (05:11) Science Predictions 2026 (12:08) Promising breakthroughs in reversing Alzheimer’s within animal models (15:28) Tech Predictions 2026 (19:59) Why a Fortune 100 company will finally call bullsh-t on AI Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF Watch on YouTube: https://youtu.be/uvXuWshY0ps?si=tZnIvPu_SKS64gFC

Two years ago, 3reate began with a bold hypothesis: that creativity is the universal solvent for the world's most complex problems. As we celebrate our second anniversary, host Andrew steps into a rare solo cast to peel back the curtain on the journey so far. This isn't just a celebration; it’s a manifesto for the "doers"—the practitioners who build the future while others merely describe it. In this episode, we explore the evolution of the show from a small audio stream to a visual-first platform with five-digit monthly engagement. Andrew dives deep into the core philosophy that creativity is a trainable skill, comparable to physical training, and explains why the podcast is shifting toward a "Practitioner Economy" model. By focusing on the "Secret Masters" of innovation—those too busy doing the work to seek the spotlight—3reate provides a unique blueprint for navigating a volatile technical landscape. Looking ahead to 2026, the strategy is sharpening. We are increasing our interview cadence and moving toward live, interactive YouTube sessions where you, the audience, can participate in the synthesis. We’re also previewing our 2025-2026 transition, including upcoming predictions across the pillars of Art, Science, and Tech. If you are ready to stop consuming the hype and start understanding the mechanism of innovation, subscribe to 3reate and join our community of applied polymaths. Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF Watch on YouTube: https://www.youtube.com/live/03hAuwwBI-E Chapters: (00:00) Andrew introduces a rare solo cast. (00:58) The origin of 3reate: Solving universal problems. (01:30) Creativity as a pervasive process, not magic. (04:23) Defining "Doers" vs. "Talkers" in society. (05:07) Growth stats: Reaching five-digit monthly engagement. (08:01) The 2026 Roadmap: Increasing interview frequency. (08:45) Shifting to live, participatory YouTube sessions. (11:01) Closing: It is never too late to start.

Katie from Renegade Plastics pulls back the curtain on the innovation economy making sustainable plastic? We dismantle the myth of biodegradable plastics and explore how polypropylene is revolutionizing everything from industrial tarps to ski lift seats. Learn how to stop being a "wishful recycler" and start building a sustainable future. We explore the "Friction Hook" between science and technology—specifically why industry remains entrenched in toxic PVC and how to overcome the inertia of 60-year-old manufacturing standards. Katie deconstructs the blueprints of the future, revealing why traditional recycling rates remain abysmal and how "biodegradable" claims are often a "Level 1" promise that masks deeper environmental issues. This isn't just a loose conversation; it is a structural audit of the objects we use every day. From the technical requirements of hospital mattresses to the carbon footprint of metal water bottles, you will receive the actionable mental models needed to navigate the changing landscape of creativity and sustainability. Stop consuming the hype and start understanding the mechanism of the innovation economy. Katie is a third generation engineer putting her genetic-predisposition to work creating a better way of managing finite resources. She joined Renegade Plastics 4 months after its inception. Her role has been to put sustainability at the forefront of all company decisions while making sure the polypropylene-based coated plastics fabrics meet market demands. Check out Renegade Plastics: https://renegadeplastics.com/ Connect with Katie on LinkedIn: https://www.linkedin.com/in/katie-kolesar-704764b/ Watch on YouTube: https://www.youtube.com/watch?v=z72tlSDB-fU Chapters: (00:00) Intros (03:45) Transitioning from environmental policy to startups (11:16) The hidden toxicity of common vinyl plastics (17:05) Breaking the "heavy plastic equals quality" myth (20:58) Engineering superior sustainable industrial textile alternatives (35:58) Avoiding the "biodegradable" marketing trap (48:45) How to be an informed plastic consumer

Andrew and Nathan deconstruct the build of Seeeks—a post-production tool created almost entirely through AI-driven synthesis. Learn how to bypass the App Store, leverage the Practitioner Economy, and turn raw ideas into functional blueprints for the future of creativity. Join the "Secret Masters" of the innovation economy today. In a digital landscape where the barriers to entry have vanished but the barriers to attention have risen, the new advantage lies in Applied Polymathy—the rigorous intersection of art, science, and technology. This week, we dismantle the "passive conversation" format to bring you a structural roadmap for building in the AI era. We explore the launch of Seeeks, a podcast post-production engine built using a vibe coding methodology where LLMs handled the vast majority of the heavy lifting.+4 We dive deep into: The Practitioner Advantage: Why the era of pundits is over and "unknown doers" are the new authority in the creator economy.+1 Packaging Concept-First: Moving beyond "guest-first" marketing to focus on the high-value "Secret Masters" who are too busy doing to seek clout. SaaS vs. Utility: Reconstructing the business model to favor transparency and pay-per-use over extractive, "level 1" subscription models. The Technical Blueprint: Navigating FlutterFlow, PWAs, and the often-ignored importance of MP3 enclosure metadata for cross-platform discovery. Stop consuming the hype and start understanding the mechanism. This is your field guide to navigating the volatile intersection of code and creativity. Join our tribe of like-minded practitioners and equip yourself with the mental models needed to build the future. Check out Seeeks for podcast post production: https://seeeks.com Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF Watch on YouTube: https://www.youtube.com/watch?v=KZcoo7S9GOE Chapters: (00:00) Helloooo! (00:48) Introduction to the Seeeks post-production app. (01:05) Proving that vibe coding actually works. (02:28) Avoiding App Store pain with PWAs. (16:40) Comparing utility pricing and SaaS models. (25:53) Why embedding MP3 enclosure metadata matters. (38:57) Handling AI context loss during coding. (45:12) Using AI as a strategic thought partner.

The world is getting safer, cleaner, and more polite—and it might be killing the future. We are living in an era defined by a "Decline of Deviance," where the removal of risk has resulted in a homogenization of culture and a collapse of true creativity. In this deep dive, we move beyond "loose conversation" to deconstruct the friction between security and innovation. We explore the "Safety Trap"—why Hollywood churns out sequels and why you can’t find original ideas on Google anymore. We track the historical precedent of how society lost indoor plumbing for a thousand years and ask: are we about to lose our technological edge for the same reason? This isn't just theory; it's applied polymathy. We dismantle the "Search vs. Discovery" problem, explaining how modern algorithms force-feed us answers while hiding the solutions we actually need. Andrew also pulls back the curtain on the "Practitioner Economy," revealing how he "vibe coded" his new post-production platform, Seeeks, using AI to bypass traditional coding workflows entirely. Stop outsourcing your curiosity to the algorithm. Join us as we reverse-engineer the necessity of risk and learn why the future belongs to the deviants. Subscribe to  3reate to equip yourself with the mental models to build what comes next. Read what we're reading: The Decline of Deviance: https://www.experimental-history.com/p/the-decline-of-deviance Our Overfitted Century: https://www.theintrinsicperspective.com/p/our-overfitted-century Support the pod: https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF Chapters: (00:00:00) Hello World! (00:00:48) Evidence that society is slowly stagnating. (00:04:25) Why comfort disincentivizes taking creative risks. (00:07:52) How ignoring norms unlocked human flight. (00:10:41) Outsourcing our decisions to opaque algorithms. (00:17:24) Why search engines kill genuine discovery. (00:23:38) Losing indoor plumbing for a millennium. (00:29:50) Building software without writing any code.

Andrew and Nathan dive into the concept of "Brain Rot" and whether short-form content is destroying our ability to focus. They discuss the difference between consuming information and gaining true wisdom, warning against the illusion of competence. Later, the conversation pivots to Artificial Intelligence, exploring how "context engineering" with LLMs can actually train us to be better human collaborators by prioritizing clarity over politeness. Is "Brain Rot" a real medical condition or just a slang term for a generation losing its attention span? In this live-streamed episode, Andrew and Nathan break down a recent NBC News article warning of the emerging risks tied to short-form video. They explore the terrifying impact of the scroll-loop on critical thinking, the loss of nuance in societal debates, and the false confidence created by 30-second tutorials that mimic mastery. But it’s not all doom and gloom. The hosts discuss actionable strategies to reclaim your focus, including the importance of "slow" hobbies like cooking, puzzles, and crochet that force delayed gratification and deep work. The conversation then takes a technical turn toward Artificial Intelligence. Andrew argues that working with AI has made him a better collaborator. They discuss the art of "Context Engineering"—moving beyond simple prompt engineering to provide deep background—and how the frustration of communicating with an LLM mirrors the challenges of delegating tasks to real people. Finally, they wrap up with a philosophical look at why AI models (and modern workplaces) suffer from being too "nice" rather than being "kind," and why honest feedback is the ultimate form of collaboration. Watch us on YouTube: https://www.youtube.com/live/P6ArSg96gCE Support the pod:  https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF Chapters: (00:00) Hello! (01:52) Discussing NBC article on brain rot risks. (05:10) Redefining brain rot as attention rot. (08:40) Short-form content versus distinct mastery skills. (10:06) Dunning-Kruger effect and startup founder ignorance. (16:40) Rebuilding focus through slow, deliberate hobbies. (21:20) Using AI to improve human collaboration. (23:30) Importance of context engineering in prompting. (30:30) Distinguishing between being nice and kind.

Andrew and Nathan return for a pre-holiday special to clear the queue of listener questions left over from their recent livestream. They dive deep into the intersection of creativity and logic, debating whether AI art can ever possess a soul and discussing how scientific thinkers are often misunderstood by the public. Andrew and Nathan sit down to tackle the questions they didn't have time to answer. The conversation begins with a look at the blurring lines between art, science, and technology, arguing that the most successful creators are those who can operate in all three circles. The hosts then move into a philosophical debate regarding Artificial Intelligence: is AI-generated imagery just "noise dressed up pretty," or can it eventually claim to have a soul? They also explore the frustration of scientific misrepresentation in the media and the "change fatigue" that comes with modern tech life—specifically targeting the recent design updates in iOS. Finally, they discuss the concept of timelessness in art. Is beauty subjective, or is it mathematically wired into our biology? Andrew explains how patterns like the Fibonacci sequence suggest a universal standard for beauty that transcends culture. The episode wraps up with personal advice on handling professional burnout and where to focus your mental energy going into 2025. Watch us on YouTube: https://www.youtube.com/watch?v=MXRGtmpZxjU Watch or listen to our recorded live stream: https://3reate.com/podcast/does-ai-benefit-humanity-ai-on-trial-youtube-live-stream-3reate/ Support the pod:  https://3reate.com https://ko-fi.com/3reate https://patreon.com/3reate Listen: https://podcasts.apple.com/us/podcast/3reate/id1723426314 https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF Chapters: (00:00) Answering leftover questions from the livestream. (00:30) Are art, science, and tech blending? (03:42) Debating if AI art has soul. (06:19) How scientific thinkers get misrepresented. (11:32) Defining what makes art truly timeless. (13:00) The golden ratio and universal beauty. (17:23) Managing burnout and constant industry change.

Watch us on YouTube: https://www.youtube.com/watch?v=fbk0gjU22x4 Listen to Michelle's last audio only 3reate podcast: https://3reate.com/podcast/e006-alcohol-free-group-travel-for-women-making-life-intentionally-meaningful-and-embracing-discomfort-with-michelle-plante/ Andrew welcomes Michelle back to the show for a candid conversation that bridges the gap between personal growth and technological philosophy. Michelle updates listeners on her shift away from the travel industry and how she discovered a new passion for improv comedy. She explains how the "yes, and" mindset of improv forces people to put down their phones, stop self-censoring, and actually listen to one another—skills that are becoming increasingly rare. The discussion takes a philosophical turn as Andrew analyzes the current state of AI and society. Drawing comparisons between 1984 and Brave New World, he argues that our biggest threat isn't government oppression, but rather a self-imposed apathy and a reliance on comfort. The duo discusses the "black box" nature of AI models, questioning the ethics of the invisible guardrails that shape the answers we receive. Key themes discussed in this episode: The Value of Improv: How performance art combats the distraction of the digital age. AI Ethics: The concern regarding transparency, bias, and the "happiness filters" placed on Large Language Models. Productivity Paradox: Why we are using AI to do more work instead of creating more time for life. Critical Thinking: The risk of raising a generation that cannot sit with discomfort or solve problems without a digital assistant. Join us for a thought-provoking session on how to maintain your humanity when the technology around you is trying to simulate it. Support the pod: https://3reate.com, https://ko-fi.com/3reate or https://patreon.com/3reate Chapters: (00:00) Hello! (01:05) Transitioning from corporate life to travel. (02:16) Creating alcohol-free travel experiences for women. (04:25) Burnout and reigniting passion through AI. (06:07) Competing in a Midwest Rant Championship. (08:10) How improv forces you to be present. (12:14) Comparing Brave New World to 1984. (14:30) Using AI productivity to gain free time. (17:48) The hidden bias within AI models. (21:28) When AI gives bad relationship advice. (28:40) The danger of avoiding human discomfort.

Watch on YouTube: https://www.youtube.com/watch?v=n0rnCfVSyvg Listen to our last audio episode Has AI Killed SEO?: https://3reate.com/podcast/has-ai-killed-seo-with-annie-deihl-and-robyn-white-ep-38-3reate/ Annie and Robyn join Andrew to share essential strategies for retailers navigating the AI revolution this holiday season. From benchmarking your brand’s visibility using five specific prompts to optimizing your homepage speed and FAQs for AI crawlers, this episode covers exactly how to ensure customers find you. Tune in to learn why optimizing for artificial intelligence is ultimately just optimizing for humans. The holiday season is here, and the way customers find products is shifting rapidly. In this video episode, Andrew welcomes back Annie and Robyn to discuss how retailers, solopreneurs, and marketing managers can adapt to the AI tool revolution just in time for Black Friday traffic. The conversation centers on the importance of benchmarking. The team shares a practical framework using five specific prompts to test how AI tools—like ChatGPT, Perplexity, and Google AI Overviews—perceive your products. By simulating customer behavior, such as asking for recommendations, comparing competitors, and prioritizing features like price or use-cases, you can immediately identify gaps in your online visibility. Beyond benchmarking, the group dives into actionable experimentation and optimization strategies, including: Leveraging Video: Why AI tools prioritize YouTube content. Performance:* The critical need for fast homepage load speeds to match AI latency requirements. Technical SEO: How to use llms.txt to guide AI crawlers, similar to robots.txt. Content Structure: Using FAQs to answer specific problems (like assembly instructions) to capture niche search intent. Ultimately, the episode concludes with a powerful insight: the question "How do we AI?" is no different from "How do we human?" By creating scannable, helpful content, you serve both your human customers and the AI agents trying to find you. Listen on YouTube: https://www.youtube.com/@3reate Listen on Apple Podcasts: https://podcasts.apple.com/us/podcast/3reate/id1723426314 Listen on Spotify: https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF Support the pod: https://3reate.com, https://ko-fi.com/3reate or https://patreon.com/3reate Chapters: (00:00) Hello! (01:06) Benchmarking brand visibility on AI tools (01:46) Prompt 1: "I need recommendations for [product category] that [specific requirements]" (02:06) Prompt 2: "What is/are the best [product/s]? (02:43) Prompt 3: "I'm comparing [competitor products]. Which would work better for [use case]?" (02:57) Prompt 4: "I'm comparing [competitor products]. Which would work better for [use case]?" (03:21) Prompt 5: "Should I be aware of anything else? What else should I know about my brand?" (06:00) Why AI tools prioritize YouTube content (06:16) Homepage speed impacts AI search results (07:23) Optimizing FAQs for specific user problems (08:23) Using llms.txt to guide AI crawlers (08:45) Optimizing for AI helps human customers

Watch Does AI Benefit Humanity - AI on Trial recording from our live YouTube broadcast: https://www.youtube.com/live/c-9jt4OVH0Q Join Andrew and Nathan for a special interactive debate where a coin toss determines their stances on Artificial Intelligence. Nathan takes the "Con" side, arguing that the AI boom represents a dangerous misallocation of global resources (water, energy, and finance). He dives into the "Alignment Problem," illustrating the existential risk via the famous "Paperclip Maximizer" thought experiment, and warns that offloading tasks to LLMs is rapidly eroding human critical thinking. Andrew takes the "Pro" side, defending AI as the first non-deterministic technology in history. He argues that current limitations are merely the growing pains of a "digital toddler" and predicts a future where AI acts as a personalized "Jarvis-like" lab assistant that amplifies human potential rather than replacing it. The hosts also tackle audience questions regarding: Safety Guardrails: Can the government effectively regulate code? The Definition of Art: Can a machine express the human condition? Future Jobs: Why Geoffrey Hinton suggests becoming a plumber. The episode concludes with a look at "sleeper technologies," specifically how World Models and Google’s custom TPUs (Tensor Processing Units) might solve the energy efficiency crisis currently plaguing the industry. **Debate stances do not necessarily reflect the views of the hosts.** Listen on YouTube: https://www.youtube.com/@3reate Listen on Apple Podcasts: https://podcasts.apple.com/us/podcast/3reate/id1723426314 Listen on Spotify: https://open.spotify.com/show/48Y2M7Ppja43Uq2wlyUtPF Support the pod: https://3reate.com, https://ko-fi.com/3reate or https://patreon.com/3reate Chapters: (00:00) Hello! (00:47) Coin toss determines debate stances. (03:17) Nathan argues AI wastes global resources. (04:15) Andrew claims AI transforms human input. (14:14) The Ultron comparison and safety risks. (19:06) Paperclip maximizer scenario and alignment risks. (32:53) Erosion of human critical thinking skills. (50:31) Defining art: Human versus machine creation. (56:55) Hinton's advice on plumbing career security. (01:13:15) Google TPUs versus Nvidia GPU efficiency.

Watch us on YouTube: https://www.youtube.com/watch?v=CuPIxJjKOY8 Andrew and Nathan are back to discuss how they actually use AI for practical work, specifically for software development and coding. Nathan kicks things off by explaining his preference for CLI (Command Line Interface) based agents, like Claude Code. He details his evolution from treating AI like a "junior software engineer" to now pushing the boundaries with advanced "hive mind" or "swarm" frameworks. This approach involves spinning up multiple AI agents with specific roles—like a coder, an architect, a QA tester, and even a documentation agent—to tackle complex features simultaneously. Andrew shares his completely different approach, which he calls vibe coding?! He primarily uses the chat window in Gemini, leveraging customized "Gems" that are pre-instructed for specific tasks. He has different Gems for architecture, reasoning, and coding. A key instruction he bakes in is "don't assume anything, ask for clarification," which helps avoid the common AI "looping problem." By grounding his AI Gem with his project's code repository, he can iteratively challenge the AI, test his own assumptions, and rapidly build features. The conversation explores how these AI-assisted methods have dramatically accelerated development time, cutting app prototyping down from six months to just a few weeks. They conclude by sharing practical, non-technical tips that anyone can use, whether you're coding or analyzing a spreadsheet, emphasizing the importance of breaking down large problems and clearly defining the AI's context. Support the pod: https://3reate.com, https://ko-fi.com/3reate or https://patreon.com/3reate Chapters: (00:00) Hello world! (01:22) Nathan’s approach: Using AI for coding. (03:15) Advanced AI: Using "hive minds" (swarms). (06:56) Vibe coding? with Gemini Gems. (09:26) Tell AI "don't assume anything." (13:50) AI speeds up app development significantly. (16:51) Best skill: Breaking down massive problems. (21:33) The importance of bounding the AI's context. (24:07) Pro-Tip: Ask AI to write better instructions.

Watch us on YouTube: https://www.youtube.com/watch?v=JexgL_vxyYU How do you actually use AI in creative work? We move beyond the hype to discuss how they use AI as a thought partner, a learning tool, and a collaborative aid. They share specific, practical use cases for coding, self-directed learning, and even language tutoring. Learn why AI won't take your job, but why you must remain the "human in the loop" to get real value. We dive into the practical, creative, and sometimes surprising ways they use AI in their daily work. They kick things off by establishing their core philosophy: AI is a powerful tool, but always requires a "human in the loop." Andrew pushes back on the idea that AI will take everyone's job, arguing that generative AI is non-deterministic, while valuable work requires predictable, determined outcomes. The real value, they argue, is in freeing up low-value tasks—like meeting summarization—to allow for more high-level human participation. Nathan, an engineer, shares his practical use cases, such as using AI for coding, brainstorming, and accelerating learning. He details a specific example of using AI to transcribe and format tables from images into markdown, a task that was previously manual and tedious. Andrew adds a pro-tip: feeding AI a screenshot of text often yields better vectorization results than pasting the text itself. The conversation shifts to using AI as a "thought partner." Andrew uses it for ideation and to find counterpoints to his hypotheses. He uses it to critique and shorten long emails, careful to use it as an aid rather than a writer to avoid the generic "AI voice." Nathan warns against letting AI become a crutch that dulls critical thinking. A key theme is using AI for self-directed learning to solve "unknown unknowns." Nathan shares a story about using an LLM to identify a complex, non-standard coordinate system from a document in Puerto Rico—a problem he didn't even know how to Google. They finish with a deep dive into advanced "context engineering," sharing their best prompting tips. This includes using system prompts (like Nathan’s "Spanish tutor" that explains why a correction is made), asking the AI to "generate a plan first" for procedural tasks, and forcing the AI to "ask clarifying questions" instead of making assumptions. Support the pod: https://3reate.com, https://ko-fi.com/3reate or https://patreon.com/3reate Chapters: (00:00) Hello world! (00:33) Using AI as a "thought partner" (02:26) Why AI (probably) won't take your job (04:56) Pro-tip: Screenshots can yield better results (08:17) Warning: Don't let AI become a crutch (10:30) Use case: Solving "unknown unknowns" (coordinate system) (16:29) Use case: AI as a customized language tutor (19:50) Prompting tip: Make the AI generate a plan

Watch us on YouTube: https://www.youtube.com/watch?v=AqkA9sKH_Y0 "Deploying capital" sounds simple, but in most tech companies, it's a bureaucratic nightmare. Why do teams spend entire quarters planning for the next quarter, only to argue over meaningless, subjective metrics? In this episode, we explore the massive gap between executive vision and employee execution. A great vision is useless if your teams can't (or won't) build it. We dive into the common dysfunctions that stop progress: internal politics, "budget jacketing" where managers fight for resources, and the "keeping the lights on" mentality that starves innovation. We also discuss the "Big Tech" incentive problem, where employees are rewarded for building a shiny new thing, getting promoted, and letting the code rot—leaving the company to fix the core business function later. The fix isn't another complex framework. The solution is a mix of top-down vision and bottom-up empowerment. We share the "Band-Aid Story"—a powerful, real-world example from a hospital—that shows how trusting employees to solve their own problems leads to massive efficiency gains. Finally, we tackle the human element of power dynamics. When executives say "we're a flat org," is it true? Or are employees just afraid to speak up because "you can fire me"? This is the cultural rot that kills good ideas. Support the pod: https://3reate.com, https://ko-fi.com/3reate or https://patreon.com/3reate Chapters: (00:00) Hello world! (1:27) Prioritization frameworks become bureaucratic. (3:22) Executives fail to get vision executed. (5:44) "Budget jacketing": the political game. (9:50) Big Tech: Build, promote, let it rot. (20:58) The "Band-Aid Fix" story begins. (23:11) No one will tell management their opinion.

Watch us on YouTube: https://www.youtube.com/watch?v=gxk3mmapp6g A report on podcast ad effectiveness sparks a debate about the medium's evolution from niche "edutainment" to mainstream, ad-driven entertainment. The hosts argue that "algorithmification" has broken our ability to discover new things, using the wild theories surrounding a real interstellar comet as a case study in lost curiosity. Support the pod: https://3reate.com, https://ko-fi.com/3reate or https://patreon.com/3reate Chapters: (00:00) Hello world! (01:04) Andrew introduces a "Top 15 Podcasts by Ad Performance" list (03:35) The hosts realize something about top-performing shows (10:10) Andrew criticizes how ad-driven models and algorithms force creators into narrow niches (13:24) Modern algorithms kill the human chaos element of discovery (19:26) The conversation pivots to aliens and the strange discovery of interstellar comet 3I/Atlas

Check out our YouTube getting ready for Holiday AI: https://www.youtube.com/watch?v=n0rnCfVSyvg Listen to their most recent update: https://3reate.com/podcast/ai-powered-holiday-retail-black-friday-ready-3reate/ Has AI Killed SEO? WTF is GEO and AEO?! Annie Deihl and Robyn White join the podcast to discuss the evolution from traditional SEO to SEO for AI- GEO (Generative Engine Optimization) or AEO (Answer Engine Optimization), explaining how brands must now build authority and trust to be recommended by generative AI models. The conversation explores the practical challenges of AI adoption, debunks corporate hype, emphasizes the critical need for human expertise, and stresses that "learning to learn" is the most important skill for navigating this new era. Read Annie & Robyn's piece SEO is so Yesterday. The future is here with AISO, GenAO, and AAO! https://www.womenxai.com/post/seo-is-so-yesterday-the-future-is-here-with-aiso-genao-and-aao Check out WOMENxAI (https://www.womenxai.com/) - A diverse network of women who are dedicated to amplifying women’s voices, leadership, and impact in artificial intelligence. Annie Deihl is a platform builder for customer experience, operations and data. She specializes in e-commerce and fintech. Connect with Annie on LinkedIn: https://www.linkedin.com/in/anniedeihl/ Read what Annie is reading: GenAI Marketshare from ProfG Markets Newsletter Robyn White is a UX Director with expertise in content design and AI-enhanced user experiences. With a background in leading UX strategy and cross-functional teams, plus an insatiable curiosity about emerging technologies, she enjoys helping organizations create impactful digital solutions in the rapidly changing AI landscape. Connect with Robyn on LinkedIn: https://www.linkedin.com/in/robyn-white Read what Robyn is reading: Your AI Survival Guide by Sol Rashidi Support the pod: https://3reate.com, https://ko-fi.com/3reate or https://patreon.com/3reate Chapters: (00:00) Hello world! And introductions. (01:20) The discussion introduces SEO for AI aka GEO aka AEO, explaining the paradigm shift from traditional Google search lists to AI models providing single, authoritative answers. (06:01) To be recommended by AI, brands must build authority and trust by creating consistent, in-depth content (how-tos, FAQs, videos) on top of good SEO practices. (09:34) AI should be used as a tool with a human in the loop to assist content strategists, not replace them, ensuring brand voice and consistency are maintained. (11:06) The hype around AI is overblown; it cannot replace true human expertise, and companies often fail to get ROI because they lack a clear strategy or the necessary data infrastructure. (18:39) In the age of AI, learning to learn, critical thinking, and deep expertise will become more valuable than ever as automation handles simpler tasks. (33:22) Brands risk customer backlash by misusing AI; J. Crew, for example, faced criticism for "creative bankruptcy" after using AI-generated images. (36:12) Parents should teach kids critical thinking to question AI-generated content and are strongly warned to avoid internet-connected generative AI toys, which are uncontrollable and unsafe. (46:46) Final recommendations include the book Your AI Survival Guide and encouraging listeners to get proactively involved in shaping local AI policy.

Watch us on YouTube: https://www.youtube.com/watch?v=gqHiABJNPrA We discuss their recent journey of trying to grow 3reate podcast on YouTube, exploring the difficult balance between genuine creativity and manufacturing content for the algorithm. We share practical lessons from our experiments and give blunt advice to aspiring creators and entrepreneurs. Support the pod: https://3reate.com, https://ko-fi.com/3reate or https://patreon.com/3reate Chapters: (00:00) Hello world! (00:31) The YouTuber journey and the conflict between staying creative versus manufacturing content to grow a brand. (02:04) Most advice for creators comes from people who are already famous, we're not! (03:19) Diverse topics hurt discoverability. (04:51) The dark side of growth. (07:15) How the metrics break down. (10:31) Andrew reveals two secrets. (14:47) Figuring out the algorithm can be its own form of creative problem-solving, similar to science. (15:45) Why 99.9% of people won't be successful. (17:39) We debate the definition of art. (22:24) Entrepreneurship parallel advice for both (28:41) Andrew ends the episode by teasing the next topic. . .

Watch us on YouTube: https://www.youtube.com/watch?v=KsVRs8xkzFo What happens when an AI gets dangerously good at faking reality? This week, we're tackling OpenAI's Sora 2 and its strange new social media features. We'll show you some of the wild, copyright-infringing videos it creates while refusing simple requests and discuss the massive ethical problems of releasing this "unnecessary technology" to the public. Later, we get real about the creator journey—from the frustrating struggle with YouTube and Instagram algorithms to the unfiltered advice every aspiring creator needs before they start. Support the pod: https://3reate.com, https://ko-fi.com/3reate or https://patreon.com/3reate Chapters (00:00) Hello World! (00:20) Sora 2's Weird Social Media Platform: OpenAI's new video AI is also a social media app, and its content rules make absolutely no sense. (02:18) Sam Altman as a Cartoon Villain: See the bizarre, brand-infringing video Sora created of OpenAI's CEO that shows just how flawed the AI is. (05:18) The Brainwashing Conspiracy: Are platforms like YouTube secretly training us to ignore the signs of AI-generated fakes? (06:28) The Unethical Double Standard: AI companies get to experiment on society without consent, a dangerous double standard that needs to stop. (18:28) The Creator's Algorithm Battle: Why does the same video thrive on YouTube but completely die on Instagram? We break down the frustrating reality. (31:19) Unfiltered Advice for New Creators: Thinking of starting a YouTube channel? Here’s the one piece of advice you absolutely need to hear first.

In this episode, Austin, co-founder of the sales platform Topsail, shares his startup journey. He explains how his team pivoted multiple times after realizing their customer acquisition costs were too high, eventually finding success by simplifying their product to a single button that boosts sales productivity. The conversation also dives into startup cosplay—the act of pretending to be a founder without doing the hard, uncomfortable work—and explores how AI is best used as a hidden tool to augment human connection, not replace it, making genuine conversations more valuable than ever. Austin Buell co-founded Topsail after a pivot from BLUPRNT a digitized brand strategy workshop. A large portion of that project was algorithmic questions, but AI was responsible for competitive research, creating marketing plans, and converting the algorithm outputs from hard to read formulas into natural language; which all translated into Topsail. Topsail simplifies a seller’s outreach motion to a single button click – transforming your team into a well-drilled, world-dominating force overnight. Connect with Austin on LinkedIn: https://www.linkedin.com/in/austinbuell/ Check out Topsail: https://topsail.app/ Support the pod: https://3reate.com, https://ko-fi.com/3reate or https://patreon.com/3reate Chapters: (00:00) Welcome to 3reate! (00:55) What is Topsail? (01:56) Go-To-Market Strategy (03:10) The Startup Pivot (04:49) Why They Pivoted to Topsail (10:12) Startup Cosplay vs. Real Work (19:59) Using AI as a Hidden Tool (25:00) A Founder's Role & Vibe Coding (50:37) Conversational Led Sales, the future with AI?