Bare Knuckles and Brass Tacks

What if the reason most people struggle to build meaningful professional relationships isn't effort — it's that they've mistaken a transaction for a foundation?David Homan has spent thirteen years building the largest private network of super connectors on the planet. Not by being the most impressive person in the room, but by being the most useful one — long before anyone asked. His thesis is that trust operates on a time horizon most people aren't patient enough to respect. That the introductions that change lives rarely pay off in weeks. They pay off in years, through chains of three to five people that no existing technology has ever been able to track — until now.In this episode, David walks us through the architecture of real community: why action is the only currency that matters, what it actually means to honor a chain of connections, and how a moment of genuine vulnerability can outperform a hundred polished elevator pitches. He also makes a case that most of us have at least two phone calls we should have made by now — and haven't.Learn more about David's work: Orchestrating Connection SOAR Connect

What happens when a community votes no…but the #AI datacenter construction starts anyway?That is not a hypothetical. It’s what happened in Saline Township, Michigan, when a $16 billion OpenAI-Oracle data center was rejected by the local planning commission, rejected again by the township board, and broke ground weeks later anyway. The developer sued. The town settled. They had no real choice.Sharon Goldman has been covering the AI data center buildout for Fortune — not from boardrooms, but from township halls, planning commission meetings, and rural communities that had never imagined something like this landing in their midst. What she’s found is a story that the technology press largely isn't telling: the buildout is a bottom-up crisis dressed up as a top-down triumph.The numbers tell part of it. Saline Township received $14 million in community benefits from a $16 billion project, against an annual budget of $1 million. In Richland Parish, Louisiana, the land where Meta's Hyperion facility now sits was once pitched for an auto plant that would have created two to three thousand permanent jobs. The data center is promising 500. The construction workers are mostly from out of state.And the justifying ideologies — the race with China, the national security imperative — has no finish line. This race has a vague one-upsmanship and a $700 billion spend with no clear end in sight.What Sharon sees coming, and what she thinks the press is missing, is the backlash that is quietly becoming a political force — showing up in recall elections, in governor's races, and in the kind of conspiratorial thinking that emerges when people have lost trust and no longer believe that democracy is working for them.You can read more of Sharon's reporting here: A Michigan farm town voted down plans for a giant OpenAI-Oracle data center. Weeks later, construction began | Fortune Meta's $27 billion AI data center is causing chaos in small town Louisiana | Fortune At the edges of the AI data center boom, rural America is up against Silicon Valley billions Huge AI data centers are turning local elections into fights over the future of energy Elon Musk is pushing to build data centers in space. But they won’t solve AI’s power problems anytime soon Big Tech will spend nearly $700 billion on AI this year. No one knows where the buildout ends Inside a multibillion dollar AI data center powering the future of the American economy

In the wake of more layoffs attributed to "AI," we thought it worthwhile to revisit this conversation from earlier in the year. Increasingly, AI is being used as a catch-all excuse to justify layoffs without clear return on business value, other than the stock price...so it's time to dig deeper.What if your AI rollout isn't failing because of the technology, but because no one asked your employees how they feel about it?Dr. Marissa Alert is a clinical psychologist who works with organizations scaling AI. Her argument is deceptively simple: the resistance leaders keep running into isn't a change management problem. It's a diagnostic failure. And until you treat it like one, AI rollouts turn into guesswork.High usage doesn't mean successful adoption. It might just mean fear-driven compliance.In this episode, we get into what business leaders and organizations consistently get wrong: the assumptions made about how employees will respond, the gap between leadership alignment at the top and the confusion that trickles down, and why layering an AI mandate onto a workforce already running on empty is a very different problem than a training rollout.We also got into something harder: what it means when employees are being asked to integrate tools that might replace them, and why most leaders don't have a good answer for that question.If your organization is tracking adoption rates and still seeing 20%, this episode is worth your time.Mentioned Jack Dorsey’s Block cuts nearly half of its staff in AI gamble

What if the story we're being told about AI's inevitability is hiding something underneath?That's the question Jessica Parker and Kimberly Becker put to George K. on their podcast, Women Talking ‘Bout AI.This conversation is a replay from their feed. It followed the money: the special purpose vehicles, the obfuscatory financing, the concentration of risk in a handful of companies and a single island in the Taiwan Strait. But what they kept arriving at wasn't really a financial question. It was a human one.Who has skin in the game? And what happens to the rest of us when the people building this technology can't answer what outcome they're actually trying to produce?The conversation covers why the dot-com analogy is the wrong frame for the current investment craze, why an AI crash could starve the narrow applications that actually work, and why the "everything machine" promise was probably never going to pay for itself.It also gets into what chatbot tutors get wrong about teaching, why we keep analogizing ourselves to whatever technology we just built, and what it might mean that generalists could be the ones who come out of this ahead.The kind of conversation where you leave with more questions than you came in with. Which is exactly what we're after.

The AI hype machine is taking up all the oxygen we need to actually stop the harm happening today.This month we heard from three guests who didn't compare notes. Didn't coordinate. And all three circled the same thing: the #AI hype machine isn't just wrong, it's actively making things worse.Capital flows going to “everything machines” instead applications that actually accomplish tasks. Gas turbines burning methane next to communities already carrying four times the national cancer rate. AI chatbots mathematically, not metaphorically, mathematically, engineered to reinforce delusional thinking in vulnerable users. Deepfake abuse still expanding, still mostly targeting women and minors, still unsolved. This is the real harm inventory.This month. Right now.Meanwhile the discourse is about whether a model might hypothetically stage a coup in five years.We're not doing doomer porn. We're saying watch the industry’s hands, not the mouth. The boring risks are already here. The extraordinary stuff — the farmer in Morocco beating generalist models with expert-annotated field data, the researcher finding antibiotics with true wet lab work — that's also already here! It's just not getting same headlines and the funding.System Check. This month's episodes, broken down against current events and whatever's rattling around our brainboxes.Mentioned: Smaller models find the same bugs as Mythos Stanford HAI 2026 AI Index Discovering a new class of antibiotics Dmitri Alperovitch's testimony on compute Baidu robotaxi outage MIT CSAIL study on AI psychosis NAACP lawsuit against xAI XAI gas turbines polluting rural communities Northern Virginia datacenter health impacts Human Line Project

Are tech industries selling us a problems they invented?Ryan Clarque, CSO at Black Rifle Coffee Company, doesn't flinch at the big provocations. When Claude's Mythos model showed up in every LinkedIn feed promising a software apocalypse, Ryan's take was blunt: the basics were broken before Mythos, and they'll still be broken after it. The real question about a powerful AI model, it’s whether you've built a program capable of doing anything about them when it does.But the conversation doesn't stop at hype-busting. Ryan has quietly done something the industry insists can't be done: built a lean, two-person security operation that ditched the big-ticket SIEM vendors, took control of its own telemetry, and outperformed programs with ten times the headcount and budget. When one of those vendors found out, they sent their "heavy hitter" to prove Ryan wrong, who left agreeing Ryan didn't need them.What emerges is a portrait of a practitioner who learned to distinguish progress from movement — and who thinks most of the industry is confusing the two. The procurement cycle, the Gartner roadmap, the sequence of investments you're told you must make: Ryan's argument is that inertia dressed up as strategy has left small security teams demoralized and over-leveraged, and that the fix is less about budget and more about the willingness to build your own way out.And then, at the end of a week of planes and conferences, Ryan says something that reframes all of it. The reason he doesn't chase the car or the watch or the title isn't asceticism — it's that working in security means observing the worst of what people do to each other, and the only way to stay functional is to invest hard in what actually holds. Time. Trust. People who remember how you made them feel.Mentioned: Cal Newport on Mythos vs other LLMs in finding software vulnerabilities

What if narrow #AI, rather than imagined AGI through scaling will be what changes the world? In some places, that’s already happening.El Mahdi Aboulmanadel founded DeepLeaf after watching smallholder farmers in Morocco misdiagnose crop disease because three distinct conditions can look identical to the human eye. Wrong diagnosis, wrong treatment, chemical residue on food.Best case scenario? Export crops rejected at customs.Worst case scenario? Food scarcity for communities that can’t afford it.DeepLeaf's answer is deliberate focus: one problem, field-validated data, models trained on hyperspectral and RGB image pairs across 57 crops. The accuracy doesn't come from scale. It comes from specificity. Fine-tuned continuously on new field data. The result is less compute, faster iteration, and outcomes closer to the ground truth.DeepLeaf has both cloud inference for large or multi-crop operations and lightweight edge models downloaded per crop for farmers running on Android phones in areas with no connectivity. The architecture fits the user, not the other way around.We get into economic potential for farmers, and of course, the effects of the war in Iran.This episode is about what new AI perspectives than the ones taking up all the oxygen in the West. This is technology that’s built for communities that Silicon Valley usually ignores.

Amber Bennoui calls it like she sees it: most of what gets sold as "AI security" is just cloud security with sparkle emojis on it.She's co-founder of AISECA, a veteran product leader, and a more honest voices in a space that isn't exactly famous for honesty right now.We sat down with her fresh off RSA, and the conversation got very real:The real AI risk isn't the sci-fi scenario. It's the DevOps engineer at a 900-person company arguing they should be able to send commands via a remote control feature, with three security people in the building who don't even know the conversation is happening. It's the tools already embedded in software your finance and HR teams use every day, making decisions nobody gave explicit permission for.Amber's argument is simple and uncomfortable: most organizations have a discoverability problem they haven't solved yet, and vendors are selling dashboards to people who don't even know what's running in their own house. That's not security. That's theater.We also got into what it actually takes to build something vendor-agnostic and practitioner-led when the companies with the biggest budgets are also the ones racing to define what AI security means. And whether the tension between speed and safety is even something security teams get to resolve — or whether that decision has already been made for them.Mentioned:  MIT Paper, "Sycophantic Chatbots Cause Delusional Spiraling, Even in Ideal Bayesians"

When was the last time a news headline about AI actually told you something true?George K. and George A. recorded this one from opposite sides of the planet — George K. fresh off RSA in San Francisco, George A. embedded at a global trust and safety conference in London. The distance didn't slow them down.This month's System Check has a theme: we’re living inside a story that powerful institutions are writing for us, and most of us aren't stopping to ask who's holding the pen.Meta and YouTube just lost a landmark lawsuit — not over what they published, but over how they designed their products to keep you hooked. The legal strategy that finally worked was the one used against Big Tobacco. Meanwhile, 82% of journalists now use some form of AI tool in their work. The people covering AI are increasingly shaped by it. The snake is eating its tail.The arms race math doesn't add up either. Forty billion dollar bridge loans. Circular investments. Credit-based bets assuming a revenue base that doesn't yet exist. And somewhere in rural Mississippi, kids are developing breathing problems because gas turbines got trucked in to power a datacenter the community never voted for.The question running underneath all of it: are we making decisions based on outcomes, or based on vibes? And if it's vibes — whose vibes are they, and how did they get there?Mentioned: Meta and YouTube verdict news coverage Center for Humane Technology’s podcast “Your Undivided Attention” episode on the Meta and YouTube lawsuit verdicts Ed Zitron’s recent monologue Research into how media covers AI UK Study on AI media coverage Muck Rack’s 2026 State of Journalism Report WSJ: CFOs expect to reduce headcount because of AI Anthropic co-founder Jack Clark on not being able to idle AI systems Iran War affects world helium supply, creating semiconductor bottleneck Environmental effects of Elon Musk using gas turbines to power data centers in rural communities

What if the best investment decision is one where no human is involved?Brant Meyer, partner at Trac VC joins the show this week to talk about the firm’s approach, where algorithms — not partners in puffer vests — make every single call. Over 115 investments to date with zero human investment decisions. An 8.5% loss ratio, orders of magnitude less than traditional VC, would seem to suggest they’re on to something.George K. and George A. wanted to know, if machines make the decision, what exactly is Brant’s job? But the more interesting conversation isn't about the wins. It's about what the model forces you to confront. We assume removing the human removes the bias — but Trac's algorithms are trained on data with its own biases.Then there's the psychological dimension. Brant makes the case that most resistance to algorithmic investing is emotional rather than rational. VCs resist algorithms because the discretionary call is the whole point. The juice, as he puts it, is the feeling of knowing. Strip that away and you're threatening an identity.Which raises the question George K. and George A. keep circling: how did venture capitalists acquire oracular status in the first place? The hit rate doesn't justify it. The pattern recognition, Brant argues, was never really theirs to claim.And yet , no founder wants to take money from a robot. The relationship still matters. The question is just whether we've been confusing that relationship with the thing it was never actually doing.Mentioned:Trac VC’s video

We've spent the last several months talking to people who live at the intersection of technology and the humans on the receiving end of it.A data privacy attorney. A corpus linguist. A clinical psychologist. A performance coach. An entrepreneur who built a business on failure.They don't all agree with each other. But they're all pointing at the same thing: the gap between how technology gets built, deployed, and sold — and what it's actually doing to people.This week's episode is our attempt to pull that thread. Mike McLaughlin — The AI ecosystem is running on bad data, has no real mechanism to fix it, and the next wave of cybercrime will target the training data itself. Kimberly Becker, PhD — AI-generated text is structurally overconfident, and a corpus linguist traced that pattern all the way back to how decontextualized certainty language helped fuel the opioid epidemic. Dr. Marissa Alert — What organizations call employee resistance to AI is, clinically, a fear and identity threat response that most rollouts are spending millions to ignore. Tychon Carter — Winning is often where the real crisis begins, and the goalpost never stops moving until you decide your value isn't determined by your output. The "Bad Hombre" — A solopreneur who built a business on public failure makes the case that the willingness to fail more than most people even try is the only real competitive advantage.Every one of these conversations eventually arrives at the same place: the distance between what we're building and who it's landing on.

Why do your friends and parents still get breach notification letters from companies they’ve never heard of?John Watters aka “The Cowboy” joins the show this week for a hard look at information security. In the early 2000s, he built iDefense from a bankruptcy buyout into one of the most influential threat intelligence companies in the world, pioneered responsible disclosure before the term even existed, and has watched the attack surface evolve from nation-state espionage into something that hits your credit card at a restaurant on a Tuesday.His answer to the breach question? The industry's been losing the clock. Attackers can move from target selection to exploitation in days. Defenders are still operating in weeks. And the gap isn't closing, not by a long shot. If anything, it's widening.This conversation goes from the living rooms of people who've stopped trusting cybersecurity to the boardrooms of Fortune 500 CISOs who still can't explain their third-party risk exposure in plain English. We talk time compression, threat intelligence architecture, the AI arms race that only one side seems to be taking seriously, and the uncomfortable truth about analysis paralysis in a field where the cost of inaction is terminal.John's closing advice to defenders: automate yourself out of a job before someone else does it for you.That one's worth the price of admission alone.Mentioned:This is How They Tell Me the World Ends, by Nicole PerlrothCISO Mike Melo’s post on security theater

What if your AI rollout isn't failing because of the technology, but because no one asked your employees how they feel about it?Dr. Marissa Alert is a clinical psychologist who works with organizations scaling AI. Her argument is deceptively simple: the resistance leaders keep running into isn't a change management problem. It's a diagnostic failure. And until you treat it like one, AI rollouts turn into guesswork.High usage doesn't mean successful adoption. It might just mean fear-driven compliance.In this episode, we get into what business leaders and organizations consistently get wrong: the assumptions made about how employees will respond, the gap between leadership alignment at the top and the confusion that trickles down, and why layering an AI mandate onto a workforce already running on empty is a very different problem than a training rollout.We also got into something harder: what it means when employees are being asked to integrate tools that might replace them, and why most leaders don't have a good answer for that question.If your organization is tracking adoption rates and still seeing 20%, this episode is worth your time.Mentioned Jack Dorsey’s Block cuts nearly half of its staff in AI gamble

The voices telling you it won't work usually belong to people who never tried. Nobody gives you permission to take a chance. You just do it.Chris built a 50K MRR business without a formal education, a tech background, or a plan. As an actor, a car dealership paid him $400 to be in a commercial and he thought, "If I can pretend to do this, what happens if I just actually do it?"From there it was taking on teaching himself APIs, webhooks integrations, and enough failures to make most people quit. He's now responsible for 40% of some dealerships' bottom lines, working remotely from Ottawa, heading to Costa Rica.We talked about why people don't take that first step. Chris's take is it's mostly the room you're in. When you move somewhere nobody knows you, the risk calculus changes. The voices telling you you're going to look stupid usually belong to people who never left.We also got into social media, the throttled notification drip sequences designed to keep you coming back, the rage bait economy, the positive reinforcement loop that rewards the most outrageous behavior. His advice was simple: put your phone down and tackle your life goals head on.Chris also hosts Bad Hombres TV on YouTube.

What happens when you get everything you thought you wanted and still feel empty?Tychon Carter won Big Brother Canada, gained fame and followers overnight, and felt completely lost. The success arrived before he was ready for it. The external validation didn't fill the internal void.In this conversation, we dig into the gap between looking successful and actually feeling whole. Tychon walks through his journey from urban planner to reality TV winner to performance coach, and the hard lessons about self-worth that came with it.We explore the masks we wear in professional spaces, the cost of performative confidence we don't feel, and why so many high-achievers feel stuck despite checking all the boxes. Tychon's "Start With You" framework breaks down three critical areas most of us keep out of balance: Power (accessing your authentic self) Play (creating and enjoying life beyond work) and Peace (finding internal harmony)The conversation gets real about mental health, the isolation trap of self-reliance, and why giving to community might be more rewarding than the endless pursuit of more.Mentioned Johann Hari, Lost Connections On prescribing community work to treat depression More on Adam Grant and Jane Dutton’s study of contribution journalsMore about Tycoon Carterhttps://www.tychoncarter.com/

This week we're taking stock of conversation trends to let it rip on AI market jitters and what happens when the math stops math-ing.We start with the numbers that have investors nervy: Amazon's $200 billion capex projection for 2026, and the uncomfortable reality of building an entire economy on depreciating GPU infrastructure with a three-year shelf life. Why the dot-com bubble comparison are incomplete, and questioning what happens when billions flow into overwhelming into transformer model architecture while research into others starves.Then we shift from market corrections to attention economics, unpacking how AI tools promise productivity while actually training us to outsource thinking itself. The cost is both financial and experiential. When was the last time you sat alone without reaching for your phone? Can you still read sentences that run four lines long?The episode lands on an uncomfortable question about who gets to have unmediated experiences anymore, and whether we're living our own lives or just consuming other people's.Mentioned: Ed Zitron ’s “Better Offline” podcast Derek Thompson’s Plain English podcast interview with Paul Kedrosky on market conditions and signs of a bubble Stephen Colbert on “truthiness” Enshittification, coined by Cory Doctorow MIT on the philosophical puzzle of AI Netflix’s main competition is sleep Point of view: Gen Z will remember more of other people’s memories than their own Blaise Pascal writing about attention in 1670

What happens when AI-generated text masquerades as human research?Kimberly Becker, PhD, a corpus linguist joins the show this week to talk about her study comparing human-written versus AI-generated abstracts in high-stakes healthcare research.The findings reveal something unsettling about how LLMs may potentially reshape scientific communication. ChatGPT's outputs showed higher informational density, formulaic patterns, and a lack of hedging, the linguistic uncertainty that marks careful scientific thinking. The AI doesn't say "may suggest" or "could indicate." It asserts. Confidently. Even when it's wrong.This matters beyond academia. When we optimize for speed and polish over depth and precision, we're changing how we write, and therefore changing how we think. We're externalizing cognition to systems trained on Reddit threads and blog posts, then wondering why the output feels sterile and an inch-deep.Becker's work raises uncomfortable questions: Are we training ourselves to accept confident wrongness? What happens when a generation of researchers doesn’t communicate uncertainty? And fundamentally, can a predictive text model ever replicate the pause, the breath, the examination that Neil Postman argued was essential to meaningful thought?This episode is about whether we're paying attention to what we're losing while we chase efficiency.Mentioned: James Marriott, Dawn of the Post-Literate Society Neil Postman’s seminal work, Amusing Ourselves to Death Derek Thompson, The End of Thinking•  • Linguistics Relevance Theory

We need to stop treating our data like something to be stored and more like a mission critical supply lines.Andrew Schoka spent his military career in offensive cyber, including stints in the Joint Operations Command and Cyber Command. Now he's building Hardshell to solve a problem most organizations don't even realize they have yet.Here's the thing: AI is phenomenal at solving problems in places where data is incredibly sensitive. Healthcare, financial services, defense—these are exactly where AI could make the biggest impact. But there's a problem.Your ML models have a funny habit of remembering training data exactly how it went in. Then regurgitating it. Which is great until it's someone's medical records or financial information or classified intelligence.Andrew makes a crucial point: organizations still think of data as a byproduct of operations—something that goes into folders and filing cabinets. But with machine learning, data isn't a byproduct anymore. It's a critical supply line operating at speed and scale.The question isn't whether your models will be targeted. It's whether you're protecting the data they train and interpret like the supply lines they actually are.Mentioned: Destruction of classified tech in downed helicopter during Osama bin Laden raid

Are we sleepwalking into a security crisis that makes ransomware look quaint?Nuclear security expert Audrey Crowe joins the show to talk about the convergence of grey zone warfare, critical infrastructure, and nuclear security. This isn't your parents’ Cold War nuclear threat, this is about adversaries who've figured out they don't need missiles when they can manipulate our infrastructure through cyber operations, disinformation, and coercion that lives in the murky space below armed conflict.While our adversaries operate in the grey zone with zero institutional friction, democratic nations tie themselves in bureaucratic knots. We demand attribution, legal frameworks, and perfect evidence before we can even acknowledge a threat. It's like showing up to a knife fight with a permission slip.Audrey walks us through how Stuxnet changed everything, why the nuclear sector spans energy, transportation, healthcare, and government regulation, and why she's on a mission to get nuclear industry stakeholders share more information with one another.We also get into the elephant in the room: Big Tech's sudden hunger for nuclear power to feed AI data centers. When profit-driven actors start controlling nuclear infrastructure, will safety remain sacred? Or will we sacrifice long-term security for short-term computational power?

What if the real AI revolution isn't about better models—but about unlocking the data we've been sitting on?Mike McLaughlin—cybersecurity and data privacy attorney, former US Cyber Command—joins us to discuss something most people miss in the AI conversation: we're building the infrastructure for a completely new asset class.The conversation moves past today's headlines and LLM limitations into what becomes possible when we solve the data access problem:Research acceleration at unprecedented scale. Imagine biotech startups accessing decades of pharmaceutical failure data, every null result, every experiment that didn't work. That's years cut from development cycles. That's drugs to market faster. That's lives saved.Universities as innovation accelerators. Right now, research institutions pay to store petabytes of data collecting dust on servers. Mike argues they're sitting on billions in untapped assets to fuel innovation.Beyond synthetic training. The next generation of AI won't be trained on Reddit threads and scraped websites. It'll be trained on high-quality, provenance-verified research data from institutions that have incentive to participate in the ecosystem.Mike's vision isn't just about compliance or risk mitigation. It's about creating the conditions for AI to actually deliver on the promise everyone keeps talking about. The compute exists. The capital exists. The models are improving. What we need now is the mechanism to turn decades of institutional research into fuel for the next wave of moonshot innovation.MentionedGoogle licensing deal with RedditPoisoning Attacks on LLMs Require a Near-constant Number of Poison SamplesMIT researchers discover new class of antibiotics using machine learningReducing bacterial infections from hospital catheters using machine learning

When did we stop asking how things work? Rich Greene joins the show to talk about his new podcast Plaintext with Rich,  and we get into something that matters more than any tech: curiosity itself.Rich spent 20 years in Special Operations before becoming a SANS instructor. Now he's taking complex tech topics and breaking them down for people who need to understand, not just use.There's a tension building between the tech sector and society at large. AI promises to make everything easier, and maybe it does. But easier can become a trap when it stops us from asking the fundamental questions. When convenience replaces comprehension, we don't just lose technical skill, we lose the ability to think critically about the systems we're building and trusting.The conversation pushes on a deeper problem: we're creating a generation that believes technology is magic. That you can "vibe code" production software. That prompts replace understanding. And when everything becomes a black box, we've surrendered more than we realize.Communication and curiosity - those are the skills that matter when the tools change every six months.Find Plaintext with Rich: Spotify Apple Podcasts Blog on Medium

Wishing you a very happy and prosperous New Year! We'll be back in 2026!

It's a holiday week, so turn off this podcast! But if you'd like to tune in all the same, then we're here to say think you. You, the listeners, have been the greatest gift this season as we've made this turn in our format from security to looking more broadly at the human impact of technology. You've stuck with us. We've gotten a lot of great messages of support, and we love the direction of the show and love that you love it! Happy holidays from BKBT! May your time off be peaceful and energizing for the new year.

We're off this week, deep into planning and scheduling for next year. Please enjoy this Best Of episode, originally released in October.Hannah Storey, Advocacy and Policy Advisor at Amnesty International, joins the show to talk about her new brief that reframes Big Tech monopolies as a human rights crisis, not just a market competition problem.This isn't about consumer choice or antitrust law. It's about how concentrated market power violates fundamental rights—freedom of expression, privacy, and the right to hold views without interference or manipulation.Can you make a human rights case against Big Tech? Why civil society needed to stop asking these companies to fix themselves and start demanding structural change. What happens when regulation alone won't work because the companies have massive influence over the regulators?Is Big Tech actually innovating anymore? Or are they just buying up competition and locking down alternatives? Does scale drive progress, or does it strangle it?What would real accountability look like? Should companies be required to embed human rights due diligence into product development from the beginning?Are we making the same mistakes with AI? Why is generative AI rolling forward without anyone asking about water usage for data centers, labor exploitation of data labelers, or discriminatory outcomes?The goal isn't tweaking the current system—it's building a more diverse internet with actual options and less control by fewer companies.If you've been tracking Big Tech issues in silos—privacy here, misinformation there, market dominance over here—this episode is an attempt to bring those conversations together in one framework.Mentioned:Read more about the Amnesty International report and download the full report here: “Breaking Up with Big Tech: a Human Rights-Based Argument for Tackling Big Tech’s Market Power”Speech AI model helps preserve indigenous languagesEmpire of AI, by Karen HaoCory Doctorow’s new book, "Enshittification: Why Everything Suddenly Got Worse and What To Do About It"

2025 was hella weird. The AI revolution is here whether we asked for it or not. This week, George K and George A reflect on the year and what it means for 2026.At AWS re:Invent, George A watched a machine create a custom fragrance and marketing campaign in real-time from a voice prompt. What does that portend for product prototyping, and scaled manufacturing?Could voice and natural language finally replacing typing as the primary interface? We're watching the biggest shift in human-computer interaction since the mouse.Worldwide AI adoption isn't hype anymore—it's happening and doing so unevenly. Some enterprises are getting serious and some are still noodling. The tools are maturing. The question shifted from "if" to "how do we do this responsibly."There are serious questions to answer. GPU lifecycles. The Magnificent Seven’s circular financing models. The human cost of moving this fast. But that's the work—building technology that serves us instead of the other way around.The revolution came. Now comes the interesting part: what we actually build with it.2026 is going to be wild. We remain up to the challenge.Mentioned: Brookings Institution, “New data show no AI jobs apocalypse—for now” Discussed in further detail with Ethan Mollick on Your Undivided Attention Reid Hoffman’s interview with Wispr Flow founder/CEO Tanay Kothari More on Coreweave’s financing model at The Verge

What if your biggest career obstacle isn't external—it's the “broken code” running in your own head?Rachelle Tanguay joins the show to unpack the difference between consuming self-help content and actually doing the uncomfortable work of rewiring your internal programming.From advising deputy ministers to coaching professionals across sectors, she's seen what happens when high-performers hit the wall between knowing what to do and actually being able to execute.This conversation cuts through the dopamine-hit culture of five-minute reels and quick fixes. Rachelle breaks down why most people confuse consuming content with doing the work, how imposter syndrome is not your own voice “chirping in your ear," and why even the most senior leaders need help to see the forest through the trees.If you've ever wondered why smart people with all the right information still can't break through their own barriers, this episode is for you. No buzzwords, no corporate speak—just an honest look at what it takes to level up when the real bottleneck is you.Mentionedhttps://www.kornferry.com/about-us/press/71percent-of-us-ceos-experience-imposter-syndrome-new-korn-ferry-research-findshttps://www.mogawdat.com/solve-for-happyhttps://jamesclear.com/atomic-habits

Graeme Rudd spent years taking emerging technology into austere environments and watching it fail.He assessed over 350 technologies for a Department of Defense lab. The pattern was consistent: engineers solved technical problems brilliantly. Lawyers checked compliance boxes. Leadership approved budgets. And the technology failed because no one was looking at how humans would actually use it.So he went to law school—not to practice law, but because solving technology problems requires understanding legal systems, human behavior, operational constraints, and business incentives simultaneously.Now he works on AI governance, and the stakes are higher. "Ship it and patch later" becomes catastrophic when AI sits on top of your data and can manipulate it. You need engineers, lawyers, operators, and the people who'll actually use the system—especially junior employees who spot failure points leadership never sees—in the room together before you deploy.This conversation is about why single-discipline thinking fails when technology intersects with humans under stress.Why pre-mortems with your most junior people matter more than post-mortems with experts.Why the multidisciplinary approach isn't just nice to have—it's the only way to answer the question that matters:Does it work when a human being needs to operate it under conditions you didn't anticipate?

What happens when you go all in and bet on yourself?Taylor McClatchie, professional Muay Thai fighter with ONE Championship, joins the show to share how she did just that.She spent a decade in reproductive science, working in a lab. Then she walked away from it all to turn her pastime into her profession. Went 20-0 as an amateur. Made her pro debut at Madison Square Garden with a head kick knockout. Has competed 65 times—exceptionally rare for a North American woman in combat sports.This episode isn't about technology. It's about what happens when you stop following the prescribed steps and start building a life around what actually matters to you.Taylor didn't fall in love with winning. She fell in love with the process. With adding one more piece to training camp—sprints, nutrition coaching, strength work—and never taking them away. With waking up and doing it again.She talks about needing three types of sparring partners: people worse than you to test new skills, people at your level to compete with, and people better than you just to survive the round. "I never want to be the best person in the room because what am I getting from beating up on the new kids?"The parallel to our industry is unavoidable. You can't grow if you're always punching down. You need to be uncomfortable. You need rounds where you're just trying to survive.We spend a lot of time on this show questioning whether technology actually serves human interests. Sometimes the best lessons come from outside our world entirely—from someone willing to abandon the expected path to pursue something real.

Eric Pilkington joins the show to cut through the noise around artificial intelligence and deliver some hard truths about what's actually working—and what's just expensive theater.AI isn't new; it's been around for 70+ years. The current generative AI boom is democratization, not innovation—and 95% of AI projects are still failing.Startups with no product, no customers, and no revenue raising $30-100 million. Companies are getting massive funding without a single dollar of revenue.The real AI leaders aren't the loudest voices on conference stages. They're the ones quietly embedding AI into workflows, building better products, and closing the gap between pilots and actual impact. Most companies chase cost savings instead of using AI to drive top-line growth. You can't cut your way to growth. Real business transformation comes from understanding the actual problems you're solving, not from chasing the newest shiny object. The superheroes of AI aren't prognosticating on stages—they're in garages and labs building things that'll matter five years from now.Mentioned:MIT Study on failure of AI pilots in business

Hunter Grad, CEO and founder of Ameliogenix, joins the show to talk about developing mRNA immunotherapies for cardiovascular disease. George K and George A sit down with Hunter to discuss: How a procrastinated university project turned into a biotech startup tackling the leading cause of death worldwide The novel application of mRNA technology to permanently reduce cholesterol levels through targeting proteins within the body rather than viral diseases What it takes to bootstrap a biotech company in Ottawa, not Silicon Valley The brutal realities of fundraising in biotech versus software startups, and why pivoting isn't always an option when lives are on the line Clearing up the myths and misinformation around mRNA technology, from how it actually works to addressing fertility concerns The role of machine learning in accelerating biotech research and drug discovery, and why quality data matters more than flashy AI hypeHunter breaks down complex immunology concepts into digestible explanations while sharing the raw challenges of being a young founder in a traditionally academic-led industry. This episode explores innovation at the intersection of technology and medicine, the importance of rigorous science over buzzwords, and what it means to swing for the fences on a problem that affects 2 billion people worldwide.Mentioned:Using AI, MIT researchers identify a new class of antibiotic candidates

Hannah Storey, Advocacy and Policy Advisor at Amnesty International, joins the show to talk about her new brief that reframes Big Tech monopolies as a human rights crisis, not just a market competition problem.This isn't about consumer choice or antitrust law. It's about how concentrated market power violates fundamental rights—freedom of expression, privacy, and the right to hold views without interference or manipulation.Can you make a human rights case against Big Tech? Why civil society needed to stop asking these companies to fix themselves and start demanding structural change. What happens when regulation alone won't work because the companies have massive influence over the regulators?Is Big Tech actually innovating anymore? Or are they just buying up competition and locking down alternatives? Does scale drive progress, or does it strangle it?What would real accountability look like? Should companies be required to embed human rights due diligence into product development from the beginning?Are we making the same mistakes with AI? Why is generative AI rolling forward without anyone asking about water usage for data centers, labor exploitation of data labelers, or discriminatory outcomes?The goal isn't tweaking the current system—it's building a more diverse internet with actual options and less control by fewer companies.If you've been tracking Big Tech issues in silos—privacy here, misinformation there, market dominance over here—this episode is an attempt to bring those conversations together in one framework.Mentioned:Read more about the Amnesty International report and download the full report here: “Breaking Up with Big Tech: a Human Rights-Based Argument for Tackling Big Tech’s Market Power”Speech AI model helps preserve indigenous languagesEmpire of AI, by Karen HaoCory Doctorow’s new book, "Enshittification: Why Everything Suddenly Got Worse and What To Do About It"

RE-ISSUE: This recording corrects for an audio overlap problem in the previous version of this interview at the 28:00 mark.Zach Lewis, CIO/CISO at University of Health Sciences and Pharmacy in St. Louis, joins the show to talk about his experience with a ransomware attack by the LockBit group.Zach takes us beyond the technical recovery into territory most people don't talk about: the gut-punch moment of finding the ransom note and the months of running on pure adrenaline while keeping his team from cracking under pressure.Key takeaways from our conversation:The human toll matters. When hospital systems go down, it's not just inconvenient. People can't get medications, emergency rooms have to reroute patients, and lives are at stake. This is the cyber war nobody wants to acknowledge.Attribution is nearly impossible. Even when you know who attacked you, there's rarely closure for victims.Leading through crisis. Zach shares how he kept his team together during months of remediation by staying calm on the outside, and knowing which team members could handle the pressure and which ones needed to stick to routine work. Sometimes the best leadership is just being that steady presence when everything else is chaos.If you want to understand what really happens when ransomware strikes, this episode is required listening.Available wherever you get your podcasts.Zach's book "Locked Up" drops January 6th and is available for pre-order now: https://www.amazon.com/dp/1394357044Mentioned:Cyber Attack Suspected in German Woman’s DeathChase Cunningham and cyber war

Clinical psychologist, Dr. Sarah Adler, joins the show this week to talk about why “AI Therapy” doesn’t exist, but is bullish on what AI can help therapists achieve.Dr. Adler is a clinical psychologist and CEO of Wave. She's building AI tools for mental healthcare, which makes her position clear—what's being sold as "AI therapy" right now is dangerous.Chatbots are optimized to keep conversations going. Therapy is designed to build skills within bounded timeframes. Engagement is not therapy. Instead, Dr. Adler sees AI as a powerful recommendation engine and measurement tool, not as a therapist.George K and George A talk to Dr. Adler about what Ethical AI looks like, the model architecture for personalized care, who bears responsibility and liability, and more.The goal isn't replacing human therapists. It's precision routing—matching people to the right care pathway at the right time. But proving this works requires years of rigorous study. Controlled trials, multiple populations, long-term tracking. That research hasn't been done.Dr. Adler also provides considerations and litmus tests you can use to discern snake oil from real care.Mental healthcare needs innovation. But you cannot move fast and break things when it comes to human lives.Mentioned:A Theory of Zoom FatigueKashmir Hill’s detailed reporting on Adam Raine’s death and the part played by ChatGPT (Warning: detailed discussion of suicide)Colorado parents sue Character AI over daughter's suicideSewell Setzer's parents sue Character AIDeloitte to pay money back after caught using AI in $440,000 report

This week George K and George A switch formats to tackle the AI revolution's messiest questions—from autonomous coding agents to digital actresses and deepfake scams.The hosts examine what happens when innovation moves faster than ethics. When Claude Sonnet 4.5 promises 30 hours of autonomous coding, what's the real trade-off between productivity gains and security fundamentals? When talent agencies want to represent AI-generated actresses, are we witnessing the death of human performance art or just another moral panic? And when Brazilian scammers can steal millions in $19 increments using celebrity deepfakes, who bears responsibility—the platforms, the regulators, or the users?They explore the uncomfortable economics behind AI video generation, where companies promised to cure cancer but instead delivered infinite dopamine-mining slop. The conversation digs into data center energy consumption, the exploitation of human attention, and why your grandmother clicking Facebook ads might represent democracy's newest vulnerability.George A brings a practitioner's lens to AI governance, arguing for education from elementary school up, metadata standards for content authenticity, and balanced regulation that protects innovation without enabling exploitation. George K challenges the fundamental premise: if supercomputers are being pointed at our dopamine receptors just to sell more ads, what happened to building technology that actually improves human life?Most importantly, they ask: Are we building applications that create a better future, or are we just doubling down on the attention economy? News examined: Anthropic releases Claude Sonnet 4.5 in latest bid for AI agents Emily Blunt among Hollywood stars outraged over 'AI actor' Tilly Norwood AI: Meta, Google & OpenAI lean into AI Generated Social Videos Brazilian scammers, raking in millions, used Gisele Bundchen deepfakes on Instagram ads

The lads are traveling this week, so we're revisiting their interview with Savannah Sly, dominatrix and sex worker rights advocate. She joined the show to talk about privacy, power, and the nuances of human intimacy as generative AI takes hold.George K and George A talk to Savannah about: The current state of privacy for vulnerable communities and the real-world operational security challenges they face Practical steps individuals can take to protect their digital identities when dating online The intersection of AI, deepfakes, and the weaponization of intimate content The zeitgeist and cultural headwinds for sex workers today

This week George K and George A switch formats to consider the deeper questions behind recent tech headlines.The hosts dig into the philosophical tensions driving today's biggest tech stories. When does technological dependency become too dangerous to ignore? How do we distinguish between genuine innovation and elaborate pump-and-dump schemes dressed up as progress? What are the real costs when entire economies become intertwined with a handful of companies?They explore whether we're witnessing the early stages of a historic bubble or if we're already past the point of no return. The conversation touches on the ethics of deploying untested technology on vulnerable populations, the normalization of surveillance capitalism, and why regulatory capture might be democracy's biggest threat.Most importantly, they ask the question that should keep every technologist awake at night: Are we building the future we actually want to live in, or are we just building the future that's most profitable for a few?The news examined: Details emerge on the US’ TikTok deal with China  Things just got worse for Nvidia in China To protect underage users, ChatGPT may ask for ID Meta’s smart glasses get smarterMentioned in the discussion: MIT report: The GenAI Divide STATE OF AI IN BUSINESS 2025 Ed Zitron’s podcast, Better Offline, and newsletter analysis of “Magnificent Seven” companies Kashmir Hill’s detailed reporting on Adam Raine’s death and the part played by ChatGPT (Warning: detailed discussion of suicide) Meta’s leaked policy on allowing chatbots to engage in “sensual” chats with children

Phil Dursey joined the show this week to cut through the hype and talked through what red teaming for AI means in mindset and practice.The conversation reveals a fundamental problem: organizations are rushing to implement AI without understanding their own workflows. Executives are buying "the thing with the AI" expecting magic efficiency gains, but they've never mapped out basic business processes. You can't automate what you don't understand.Phil's approach starts with the right question: "Are we using the right tool for the use case?"We also talked about education and kids. Find out why Phil argues philosophy and humanities give you the biggest advantage when working with AI systems. It’s what he looks for in hiring, too. The ability to formulate good questions, understand context, and think clearly matters more than technical prowess.And finally we touch on the job market. We're heading toward AI capabilities that will exceed human professionals in specific domains. The displacement won't be overnight, but it's coming.If you're implementing AI in your organization, this episode should make you pause and ask harder questions. The technology is powerful, but power without thoughtful application is just expensive chaos.Mentioned: Phil Dursey's guide, Red Teaming AI Hard Fork podcast segment on a student's AI workflow

A stalkerware economy is thriving on TikTok, and it's generating hundreds of thousands in sales. Journalist Rosie Thomas from 404 Media joins the show this week discuss her investigation into GPS trackers being sold as relationship surveillance tools directly through TikTok Shop. This isn't some dark web operation - it's happening on one of the world's most popular social platforms.The findings are disturbing. Content targets people with taglines like "Is she really going out with friends?" are generating hundreds of thousands in sales. Algorithms don't just show you this content - they amplify it the moment you engage.The digital economy we all live in has normalized surveillance to the point where stalking your partner is being marketed as a reasonable relationship tool. The technology isn't new, but the accessibility and algorithmic amplification absolutely is.This conversation touches on everything from the failure of tech companies to consider abuse cases in product design, to how parasocial relationships are replacing actual community bonds, to the legal gaps that leave victims with limited recourse.If you work in tech, this episode should make you uncomfortable. As a citizen, it should terrify you. It's a reminder that our biggest threats often come from the normalization of our culture's worst tendencies.Read more on 404Media: https://www.404media.co/tiktok-shop-sells-viral-gps-trackers-marketed-to-stalkers/

This week on the show: some seriously cutting-edge territory. George A talks about what he saw at the Love and Sex with Robots conference in Montreal. Then George K and George A discuss AI companions, embodied LLMs, and the wild intersection of technology and human intimacy.This isn't just about sex robots - it's about the broader question of how AI is reshaping fundamental human experiences. The reality check: If you think this stuff is too niche or weird to matter, give it 5 years. This technology is going to be everywhere - in education, therapy, companionship. The question isn't whether it's coming, it's whether we'll think through the implications before it's too late.This might be one of the most uncomfortable (and important) tech conversation we're not having as a society.Fair warning: This episode gets real, fast. But if you work in tech, security, or just want to understand where we're heading as a species, it's worth your time.Stay tuned to the end to hear about the "door prize" George A from the conference that is gonna make the office Secret Santa…interesting.Mentioned this episode: Our Season 4 opener with Savannah Sly Gov Pritzker Signs Legislation Prohibiting AI Therapy in Illinois Parents of teenager who took his own life sue OpenAI You can read the full text of the lawsuit here  Scene from Interstellar that George K references

Sumona Banerji, founder of MindShield and PhD candidate in cyber psychology, joins us to discuss building cognitive resilience in an age of exponential technology and algorithmic manipulation.George K and George A talk to Sumona about: Truth is fragmented - Everyone only sees a piece of it, creating space for better discussion The TAR framework - Trigger, Analysis, Response for emotional regulation with manipulative content Expanding the amygdala - How meditation literally grows brain regions for critical thinking Algorithm curation - Your feeds mirror your choices; conscious curation transforms your information dietFrom documentary filmmaker to tech psychology researcher, Sumona's unconventional path offers unique insights into protecting our cognitive capacity as knowledge workers navigating an increasingly complex information landscape.-------------Got an idea or topic you'd like us to cover? Drop us a line at [email protected]

Former NFL player Mark LeVoir joins us this week to talk about life after pro sports, and the lessons he took transitioning to a career in tech.George K and George A talk to Mark about: The transition from professional sports to tech sales and why goals beat identity every time His simple method for aligning business outcomes with corporate objectives in enterprise deals Building sales teams that can fail fast, learn quick, and operate on trust instead of aggressive tactics Life lessons from the NFL locker room and why hanging with Tom Brady is just like hanging with regular dudes"I want my people to be able to fail. Fail fast. What do we learn from it? If your intent's in the right spot and you just failed, it's a coaching experience. If your intent isn't right, we're having a different conversation."Plus, George A. gets Mark talking about hanging with Tom Brady, why Lamborghinis are useless when you're 6'7", and his top cigar picks, because why not?------If there’s a burning topic you think we should address, let us know! Email us at [email protected]

This week Savannah Sly, dominatrix and sex worker rights advocate, joins the show to talk about privacy, power, and the nuances of human intimacy as generative AI takes hold.  George K and George A talk to Savannah about: The current state of privacy for vulnerable communities and the real-world operational security challenges they face Practical steps individuals can take to protect their digital identities when dating online The intersection of AI, deepfakes, and the weaponization of intimate content The zeitgeist and cultural headwinds for sex workers todayNew season, new scope. Thank you for listening!

Season 4 is here! While George K and George A are in Las Vegas for Black Hat and DEFCON this week, here's a preview of some changes coming to the podcast.We're grateful for every listener. Thank you for being on this journey with us!

Rinki Sethi joins the show this week! She's held just security leadership roles on just about all possible sides, and now she's also a VC investing in the next generation of founders.George K and George A talk to Rinki about: Real talk and timeline on AI in SecOps How security teams are gonna get reorganized around AI tooling Why most founders fall in love with solutions instead of problems The brutal truth about career development in the AI eraBest quote: "I don't think AI is going to replace people. AI is going to replace people that aren't using AI - and it's already starting to happen."Rinki breaks down why the finance team beat an engineering team during a hackathon at her portfolio company, and why that feat portends an industry wide change.For vendors: Stop trying to impress CISOs with your tech specs. They're drowning in noise and need you to understand the actual problems their teams are facing.For practitioners: Learn the fundamentals, then use AI to scale. The combo is gonna separate good from great.————👊⚡️Support the show!For as little as $1 a month, you can support the show and get exclusive member benefits, or send a one-time gift!https://ko-fi.com/bareknucklesbrasstacksYour contribution covers our hosting fees, helps us make cool events and swag, and it lets us know that what we're doing is of value to you.We appreciate you!

Kendrick Trotter joins the show to talk about going from Uber driver to a major account executive at a public cybersecurity company, then founding his own business that created over $70 million in annualized salaries for underrepresented professionals.George K and George A talk to Kendrick about: How a Division I football scholarship and one life-changing Uber ride with an Amazon VP changed everything His game-changing approach to calling CISOs Building Us and Technology - training 13,000+ people for free and placing them at companies like Zscaler and Airtable The harsh reality of what happened to DEI initiatives and why diversity of thought drives 30% more revenueThe bottom line: Kendrick's story proves that with the right mindset, genuine human connection, and "unreasonable hospitality," you can break barriers and create opportunities for others.————👊⚡️Support the show!For as little as $1 a month, you can support the show and get exclusive member benefits, or send a one-time gift!https://ko-fi.com/bareknucklesbrasstacksYour contribution covers our hosting fees, helps us make cool events and swag, and it lets us know that what we're doing is of value to you.

George K and George A went completely off-script this week and recorded their first one-on-one episode in years. Fair warning: it gets heated about some industry trends that have been grinding their gears.George K and George A get into: The AI hype cycle vs. actual utility as George K articulates step by step how he used an LLM to prepare for a talk - what it could and couldn't help with The danger for companies gutting entry-level positions while claiming "AI efficiency" The risks of a generation that can't handle disagreement or boredom The return of Gilded Age exploitation disguised as "hustle culture"Real talk: If your company is advertising 70+ hour work weeks as a feature, you're part of the problem. We didn't survive a pandemic just to forget every lesson about work-life balance for the sake of some exec's third yacht.If you're feeling the cognitive dissonance of working in tech right now, you're not alone.What's your take? Are they just two old guys yelling at clouds, or are these legitimate concerns about where our industry is headed?————👊⚡️Support the show!For as little as $1 a month, you can support the show and get exclusive member benefits, or send a one-time gift!https://ko-fi.com/bareknucklesbrasstacksYour contribution covers our hosting fees, helps us make cool events and swag, and it lets us know that what we're doing is of value to you.We appreciate you!

Tanya Janca joins the show this week, with unique perspective on building secure software and advocating for better cybersecurity policy.George K and George A talk to Tanya about: Her transition from 14 years as a Canadian public servant to private sector entrepreneurship The core values that guide her work: performing good and moving the industry toward secure software Entrepreneurship since age 19: solving real problems that hurt badly enough for people to pay Civil advocacy for security by design policies and challenging inadequate government cybersecurity practicesTanya's perspective on building businesses around genuine problem-solving rather than just seeking acquisition or wealth creation offers valuable insights for any founder. Whether you're interested in secure coding, entrepreneurship, or how to advocate for better cybersecurity policy, this episode delivers actionable insights from someone who's been in the trenches and made real impact.Mentioned: The Eh List: https://ehlist.org/ Forte Group: forte-group.org/home-our-mission Tanya’s petition: https://www.ipetitions.com/petition/secure-canadas-future Tanya’s Secure Coding Guideline: newsletter.shehackspurple.ca/c/secure-coding-guideline

Vivek Khindria, longtime CISO, joins the show and he brought the heat. We talk building security teams, quantum computing timelines, and why your board doesn't want to hear about firewall rules.George K and George A talk to Vivek about: Why betting on business people and teaching them security > hiring tech nerds who can't talk to humans Why enterprises must start the conversation around crypto agility now with the quantum computing future ahead Your board wants to hear about "resilience," not your latest pen test results How to balance outsourcing vs maintaining in house talentVivek's been around the block and back, knows his stuff, and isn't afraid to call out nonsense. Plus he talks about why most security leaders are burning out and what to actually do about it.This is the kind of conversation that makes you better at your job, not just better at using buzzwords.

This week, we're returning to the original inspiration for our Pride in Cyber campaign!Angela Brown and Amber DiPippa join the podcast to discuss their scholarship initiative supporting LGBTQ+ individuals pursuing cybersecurity.George K and George A talk to Ang and Amber about: The scholarship's origins and its goals for supporting LGBTQ+ cybersecurity students  The realities and financial hardships unfairly leveled at queer communities  Practical advice for authentic allyship and community support🏳️‍🌈👊⚡️The Pride in Cyber collection is now available in the BKBT Merch Store. ALL PROFITS from all sales of pride merch for the entire month of June will be donated to Ang and Amber's scholarship fund. Shop today at https://bkbtpodcast.shop/collections/pride-in-cyber

Madeline and Oliver from Phish Club joined the show to talk community building for junior practitioners in cybersecurity.George K and George A talk to Madeline and Oliver about:The power of lateral networking - building relationships with peers who will rise together rather than just trying to impress executivesWhat actually gets you hired - home labs and technical write-ups beat certifications every timeCreating inclusive community - from Discord lounges to bringing non-cyber friends, because networking is networkingThe real skills that matter - curiosity in interviews, asking questions, and showing initiative beyond just following documentationTheir approach is simple but powerful: consistency, authenticity, and making sure no one sits alone in the back. The result? A thriving community that's helping practitioners actually connect, learn, and advance their careers together.------🏳️‍🌈 It's PRIDE month! ALL PROFITS from all sales of the Pride collection during the month of June will be donated to scholarships for LGBTQ+ students in cybersecurity.And this year we have generous vendor sponsors who will match our donation!Shop swag, help students. You can shop the collection here: https://bkbtpodcast.shop/