“I’m coming around to the view that running human-written code – without it being AI-audited – is going to be considered the reckless thing.”

In this episode, Martin Alderson – cofounder of Catchmetrics, engineering leader with two decades shipping enterprise software, and author of a Top 100 Hacker News blog on the intersection of software engineering and economics – cuts through the AI noise with the rare combination of someone who actually builds with agents every day and can read what that does to markets. The thesis that runs through the whole conversation: most companies think their AI problem is a tooling decision. It’s not. It’s a mindset problem, and the wrong one is quietly existential.

What You’ll Discover:

[01:29] The $285 Billion Markdown File

→ Why Wall Street wiped out a quarter-trillion in SaaS value over 13 markdown files – and the three distinct ways every SaaS company is now exposed.

[05:38] The Figma Trap

→ How SaaS companies ended up paying their single biggest competitor every time a customer uses their product – and how many others are in the same corner.

[12:33] The 180 Nobody Saw Coming

→ Why the “AI writes insecure code” fear is flipping on its head – and the case that human-written code without an AI audit is about to be the reckless choice.

[15:55] Why Non-Technical People Out-Build Engineers

→ The reason marketers and PMs are shipping products in a weekend – and the human psychology that lets them iterate without the guilt that kills good ideas.

[23:45] Why a Copilot License Can Kill Your Company

→ The bifurcation of intelligence: how a “safe” enterprise tool convinces leaders AI is mediocre, right as they’re about to be out-executed.

[28:33] Five People vs. a Thousand-Person Company

→ Are small teams with agents winning a window that closes when the frontier labs steamroll them – or is this the new permanent state?

[33:14] The One Question Every CEO Needs to Answer

→ The deceptively simple question Martin puts to leaders – and why most boards can’t even answer it.

[35:50] The Oligopoly Scenario

→ Why open-weights models are quietly closing up, and the future Martin is genuinely worried about: three or four giants extracting rent with little incentive to innovate.

Key Takeaways:

• The barrier to building complex software has collapsed – but the threat to incumbents isn’t customers rebuilding a CRM, it’s a five-person team out-executing them on cost and speed.
• Don’t measure AI adoption by Copilot licenses issued or people trained. Ask how many tokens your organization is actually consuming – and whether you can even answer that at a board level.
• The real strategic question isn’t “how do we add AI to what we do?” It’s “if we reimagined the whole business with ten great people and agents, what would it look like – and what’s blocking us from getting there?”

About Martin Alderson:

Martin Alderson is cofounder of Catchmetrics and the writer behind martinalderson.com, a Top 100 Hacker News blog covering the AI transformation through the dual lens of software engineering and economics – read and recommended by people including OpenAI co-founder Andrej Karpathy. He’s spent two decades shipping enterprise software and writes some of the sharpest analysis anywhere on where AI, building, and markets actually collide.

“We’ve seen a lot of technological innovation over the last few hundred years. I think this is the last invention.”

In this episode, Dr. Michael Housman – Wharton-trained data scientist, founder of AIccelerator, and bestselling author of Future Proof – cuts through the noise on why most organizations are failing at AI adoption. The problem isn’t the technology. It’s the people. We dig into what leaders consistently get wrong, how to architect real behavior change inside organizations, and why the ability to tell a compelling story might be the most durable career skill of the AI era.

What You’ll Discover:

[00:00] Why OpenAI Was as Surprised as the Rest of Us→ An insider account of how ChatGPT caught fire – and why even its creators didn’t see it coming.

[06:26] Technology Is Easy, People Are Hard→ The cautionary tale of hiring software that worked perfectly and changed nothing – and what it taught Housman about the real barrier to AI ROI.

[08:49] Carrots, Sticks, and Lightbulb Moments→ The practical change management playbook for getting a workforce to actually adopt AI – and why incentives alone aren’t enough.

[11:40] From Pilot to Production→ How to bridge the gap between “AI wow moment” and systematically redesigned business processes that stick.

[20:49] Stop Using AI as a Better Google→ Why the real unlock is using LLMs as a thought partner – and how to force them to stress-test your ideas instead of flattering you.

[22:43] Can AI Fix Your Cognitive Biases?→ The nuanced truth about AI bias, why classification models outperform doctors, and how to prompt against your own blind spots.

[29:13] Follow the Interesting→ Career advice for a world where developer jobs are already being disrupted – and why storytelling may be the last skill algorithms can’t touch.

Key Takeaways:- Successful AI adoption is a change management problem first. Without behavior change at the frontline, the technology is irrelevant.- Don’t use AI to do your work for you – use it to pressure-test your thinking. Ask it to beat up your ideas.- The most future-proof career move is leaning into distinctly human skills: storytelling, relationship-building, and judgment.

About Dr. Michael Housman:Dr. Michael Housman (House) is the founder and CEO of AIccelerator and author of the #1 bestseller Future Proof: Transform Your Business with AI or Get Left Behind. A Wharton PhD in applied economics, he has spent 17 years building and deploying AI platforms across Fortune 500 companies and high-growth startups.

"If you show me a company that succeeded with every experiment, I'll show you a company that's very poor at picking their experiments." — Jason Goldberg

In this episode, Jason "Retail Geek" Goldberg — Chief Commerce Strategy Officer at Publicis Group and co-host of the top-ranked Jason & Scott Show — makes the case that most companies are asking the wrong question about AI. A 30-year commerce pioneer who launched Blockbuster's first e-commerce site in 1995 and has since driven billions in online revenue across hundreds of clients, Jason brings rare long-view perspective to the agentic commerce moment. We dig into why Walmart went from banning AI to hitting a trillion-dollar market cap, why fast followers beat first movers, and what the one question Doug McMillan asked in every meeting has to do with all of it.

What You'll Discover:

[02:16] Is Agentic Commerce Real — Or the Next Blockchain?→ Jason's framework for separating genuine disruption from hype, and why he thinks agentic is one of only five true disruptions in 6,000 years of commerce

[08:27] The Walmart Story: From "AI Is Illegal Here" to $1 Trillion→ What a single question from Doug McMillan — asked in every meeting — unlocked inside the world's largest retailer, and what it reveals about the job of a CEO in volatile times

[14:16] Efficiencies vs. New Behaviors: The AI Trap Most Companies Fall Into→ Why optimizing what you already do will save you money this year and cost you everything in five — and the consumer behaviors that will disintermediate your shelf entirely

[19:06] The Gartner Hype Cycle as a Leadership Tool→ How to use the trough of disillusionment to your advantage, and why being unrealistically optimistic about the future is just as dangerous as ignoring it

[23:11] The ROI Trap: Why You'll Always Choose the Oak Tree Over the Acorn→ The structural reason most companies starve their best future bets — and what exceptional organizations do differently

[25:15] Why Ivory Tower Innovation Almost Always Fails→ The REI green vest story: what happens when the scientists solve the wrong problem, and where the real innovation instinct actually lives in your organization

[32:43] The Fast Follower Advantage — and the Regret Question→ Why you haven't missed the agentic window, what AltaVista vs. Google tells us about timing, and the one question to ask yourself before leaving any strategy meeting

Key Takeaways:

• Being first rarely wins. Being prepared to move fast when the signal is clear almost always does.
• The CEO's real job in disruption isn't picking products — it's being the chief change agent for 1.6 million people who learned from their predecessors.
• The ROI framework will always favor your existing business over your future one. Exceptional companies build a different budget category for experiments — and expect most to fail.

About Jason Goldberg:Jason "Retail Geek" Goldberg is the Chief Commerce Strategy Officer at Publicis Group, where he advises the world's largest retailers and brands on digital transformation. He co-hosts the top-ranked Jason & Scott Show podcast and has been named a leading global retail influencer by Rethink Retail for six consecutive years.

What happens when the cost of intelligence drops to zero? The only thing that matters is knowing how to give the right instructions.

In this episode, Andreas Bachmann – co-founder of Adacor, a managed cloud and critical infrastructure provider serving banks, automotive, healthcare, and energy clients across Germany – shares what 22 years of deliberate, founder-led growth actually looks like. We explore the real tension between innovation and zero-tolerance uptime, the co-founder crisis that almost broke the company, and why Andreas believes the primary job of every knowledge worker in five years won’t be doing the work – it’ll be managing the agents doing it for them.

What You’ll Discover:

[00:01:19] Innovating When Failure Is Not an Option → How Adacor runs experiments for critical infrastructure clients who can’t afford a single hiccup – and the mental model that makes it work

[00:05:30] The Sustainable Growth Playbook → Why Andreas chose deliberate, step-by-step growth over hypergrowth – and how that decision made Adacor more competitive, not less

[00:13:49] The Co-Founder Crisis Nobody Talks About → At 40–50 people, Adacor fractured into silos and the founding team needed “marriage counseling” – what they decided, and who stepped back

[00:17:34] Self-Organization Without Chaos → How Adacor implemented OKRs, dailies, and retrospectives in a high-stakes environment – and the one thing that makes retros actually stick

[00:23:37] Building a Human-Centered Tech Company → From family compatibility programs to volunteer firefighter support – why Andreas treats the company as the strong one, not the individual

[00:27:26] The AI Question: Bullshit or Real? → Why Andreas went all-in on AI in 2022, how Adacor hacked EU innovation grants to build an AI team years early, and why he skipped the GPU commodity race entirely

[00:34:16] The Future of Work Is Managing Agents → Andreas’s thesis on what happens when intelligence is automated and essentially free – and what human value actually looks like on the other side

Key Takeaways:

• Sustainable growth is a competitive advantage in high-trust industries – adding people too fast breaks the thing clients pay you for
• “Fast fashion software”: non-developers are already using AI to write and discard code; this is a glimpse of where all knowledge work is headed
• The best retros are useless without a committed “what do we do about it now?” – every retrospective at ATCO must produce 1–3 actionable initiatives
• The co-founder transition from parallel silos to one clear direction is one of the most underreported breaking points in company building
• The new leadership superpower isn’t having all the answers – it’s knowing when to step back and trust the people who do

About Andreas Bachmann:

Andreas is co-founder and CEO of Adacor, a German managed cloud and critical infrastructure company he’s been building for over 22 years with a deliberate focus on stability, human-centered culture, and innovation that doesn’t break things. He’s also a founding force behind Media Monster, an initiative supporting mental health and work-family compatibility in tech.

“As we move up the pyramid of command and control, people stop telling us the truth. We as leaders actually become dumber.” – What if everything you learned about leadership is based on a system designed for sovereigns managing illiterate peasants?

In this episode, Peter Laughter – a recovering CEO, Quaker, and self-described student of human connection – challenges the foundations of how we lead organizations. Drawing from his own transformation (from anxiety-ridden command-and-control leader to champion of distributed power), Peter lays out a radically different vision: one where your job as a leader isn’t to have the answers, but to make sure the people who do can actually speak up.

What You’ll Discover:

[00:00] Why Disruption Is Just Evolution – And Why We Keep Fighting It

→ The biological case for why struggle is the feature, not the bug – and why the gap between technological waves has collapsed

[06:00] The Deming Effect: How Market Forces Will Force Leadership Change

→ Why big organizations can’t change from within, and how a wave of AI-displaced workers will build something better from scratch

[12:00] Why Bayer’s Top-Down Decentralization Might Be Doomed

→ The critical difference between mandating a system and growing one – and lessons from Zappos’ Holacracy disaster

[18:00] The Becky Moment: When an Employee Called Out Her CEO’s Core Values Violation

→ Peter’s personal turning point – how getting overruled by a team member killed his anxiety and changed his entire leadership philosophy

[24:00] How to Actually Start: The “What Are You Seeing?” Framework

→ A dead-simple Monday-morning practice that shifts you from having the plan to gathering perspectives

[30:00] Why Consensus Is Violence and Decisions Should Be Made by Framework

→ How Peter built a values-based decision system where employees could challenge the CEO – and why it produced better outcomes

[36:00] Recruiting Is Broken: Why You Should Hire Happy People, Not Desperate Ones

→ Why starting the recruiting process before you need someone completely changes who you attract

[40:00] The Misconception That Hurt Most: “I Was Supposed to Be The One”

→ Peter’s answer to what he got wrong – and why he’s optimistic about the future despite everything

Key Takeaways:

• Command and control doesn’t just limit organizations – it actively makes leaders dumber by cutting off honest feedback
• You don’t need everyone on board to change an organization – 20-30% creates a cascade (Greg Satel’s Cascades model)
• Start any leadership challenge by asking “What are you seeing?” and actually listening for the brilliance in the answer
• Replace consensus (which beats ideas down to the least common denominator) with values-based decision frameworks

The gap between idea and reality is now nearly zero – and that changes everything about who can build what

About Peter:

Peter is a former CEO turned leadership advisor whose work centers on what he calls “abundant leadership” – the recognition that power and authority are fluid, not fixed. Rooted in Quaker decision-making principles and real-world experience building distributed organizations, he helps leaders create environments where emergent leadership can thrive.

“Why do I have to tell your chatbot to do something? Just do it.”

In this episode, Jeff Seibert – founder of Digits (AI-native accounting platform), former Twitter Head of Product, and the engineer behind Crashlytics (now on 6 billion devices) – reveals what it actually takes to build AI-native companies from scratch. We explore why most companies are getting AI wrong by bolting chatbots onto old products, how to structure teams for extreme velocity, and why the accounting industry is about to experience its HP-35 calculator moment. Jeff’s bold prediction: the entire month-end close process will be automated within 12 months.

What You’ll Discover:

[02:45] Why Accounting Data Quality is Decades Behind Product Analytics → The genesis story of Digits: when Twitter’s 100-person finance team couldn’t answer a simple budget question in under three weeks

[08:28] Building Companies for AI From Day One → How ML-native architecture differs from traditional databases and why this matters more than the AI hype suggests

[10:31] The 65-Person Company That Runs All-Hands Every 48 Hours → Jeff’s radical approach to velocity: weekly sprints, fractal team structures, and why they’ll never hire “lone eagle” engineers

[15:20] Keeping Teams Intentionally Small at Scale → How to eliminate the “empire building” problem by dissociating engineering coaches from project staffing

[19:59] What CEOs Actually Do That AI Can’t Replace (Yet) → The 10%/90% leadership philosophy and why Sundar Pichai’s “AI will replace CEOs” take misses the point

[23:30] Disrupting QuickBooks: Technology vs. Distribution → Why accounting is uniquely suited for AI disruption and how startups can outpace 800-pound gorillas

[26:14] Why AI Isn’t Just Another Ajax Moment → The fundamental shift from “talk to our chatbot” to “the AI should just do it” – and what that means for software architecture

[30:47] The Architectural Wall Ahead for Large Language Models → Why current LLM architecture won’t reach AGI: the context window problem, lack of memory, and inability to backtrack during inference

[32:05] The Great Work Displacement: Data Entry is Dead by 2026 → Jeff’s evolved prediction on AI’s economic impact and why the “lump of labor fallacy” applies to automation fears

Key Takeaways:

• AI-native means redesigning your data architecture from scratch, not adding a chatbot interface to legacy systems
• Run your company on the shortest planning horizon you can see – for Digits, that’s 4-5 week “horizons”
• Hire senior people who are “chill” with strong opinions, loosely held – and actively filter out solo operators
• The most powerful AI products won’t ask users what to do – they’ll understand the goal and just execute
• Accounting’s month-end close will be automated by end of 2025, marking one of AI’s first complete workflow eliminations

About Jeff Seibert:

Jeff is the founder and CEO of Digits, the AI-native accounting platform. Previously, he served as Twitter’s Head of Consumer Product (launching the algorithmic timeline), co-founded Crashlytics (acquired by Twitter, now runs on 6 billion smartphones), and was featured in Netflix’s Emmy-winning documentary “The Social Dilemma.” He’s backed 100+ startups as an angel investor and has been building software since releasing his first app at age 12.

Related Links:

• Digits

“We couldn’t start inkjet again if we had it in our hands because we’re not meeting the rules.” That stark admission from former HP Fellow Will Allen reveals why even the most innovative companies struggle to recreate their own breakthroughs—and what it takes to actually scale disruptive technology.

In this episode, Will Allen, holder of 102 US patents and the first HP Fellow promoted within HP’s Global Print Business, takes us inside three decades of Silicon Valley innovation from logic analyzers to consumer inkjet printing to his current role as CTO at Kaspix, where he’s pioneering ultra-low-power AI inference using analog circuits. We explore why research should be treated as investment portfolio management (not an expense to cut), how “showing beats telling” when getting buy-in for radical ideas, and why getting AI to the “true edge” – directly at sensors and actuators – will fundamentally change computing economics.

What You’ll Discover:

[00:00] Why Research and Development Are Two Different Things

→ The fatal mistake of treating R&D as a single expense line when research is actually an investment with portfolio-level returns

[06:03] Has Silicon Valley Run Out of Ideas?

→ Why scaling success creates the very constraints that prevent future innovation, and whether we’re less innovative than decades past

[10:12] The Scaling Trap That Kills Success

→ Real HP story: how field-fixing problems scaled so badly that engineers couldn’t design problems out, and what this means for any growing business

[16:23] Getting Past the “$100 Million Question”

→ How to navigate corporate demand for predictable returns when developing something the market has never seen before

[18:03] “A Functioning Proto Is Worth a Thousand Pictures”

→ The clownfish story: how a weekend demo got low-drop-volume printing approved after months of rejection, and the art of communicating on stakeholders’ terms

[21:16] Signal Spotting and Fundamental vs Killer Apps

→ Will’s framework for distinguishing noise from transformational trends—and why asking “what’s the killer app?” might be the wrong question

[24:47] Kaspix and the True Edge

→ Why analog circuits for AI inference could be as transformative as the mouse, enabling intelligence directly at transducers without memory-compute bottlenecks

[29:56] Where AI Is Actually Heading

→ Beyond the hype: specialized AIs, “AI middle management,” and why rapid societal change from deterministic technology creates uncomfortable transitions

[36:04] The Advice Will Would Give His Younger Self

→ Why leaders who invested years in education suddenly think quarterly, and how to reclaim the long-term thinking that got you there

About Will Allen:

Will Allen is CTO at Kaspix, pioneering ultra-low-power AI inference through analog circuit design. Previously, he spent 30 years at HP, becoming the first HP Fellow promoted within HP’s Global Print Business. He designed the color imaging pipeline used in HP’s first 4 million color consumer inkjet printers, led IP production in HP Labs’ AI and Emerging Compute Lab, and holds 102 issued US patents across printing, displays, robotics, and digital imaging.

Related Links:

• Will’s LinkedIn Profile

• Will’s Professional Homepage
• Will’s YouTube Channel
• Kaspix
• Kaspix Founder Pablo Zegers interviewed on The Innovators Podcast by John Biggs

What if the leadership frameworks we’ve relied on for decades are fundamentally broken for today’s world? In this thought-provoking conversation, Pascal sits down with Jeffrey Rogers—his collaborator of nearly a decade—to explore how leaders can navigate sustained uncertainty and systematic disruption.

Jeffrey, an expert in organizational learning and futures thinking, challenges the “Good to Great” era of one-size-fits-all leadership models. Instead, he advocates for meta-learning: the ability to learn how to learn, adapt frameworks contextually, and build organizations that can transform repeatedly. They dive deep into the tension between efficiency and experimentation, why the “middle horizon” (5-10 years) is so hard to envision, and how generative AI fits into organizational learning—spoiler: it’s not the efficiency tool you think it is.

Key Topics Covered:

• Why best practices are dead and what replaces them in high-uncertainty environments
• The efficiency vs. learning paradox: how to balance execution with experimentation
• Generative AI’s real value: rapid prototyping, not scaling (and why that matters)
• The futures cone and how to think about multiple possible futures
• Practical advice for middle managers when leadership won’t listen
• Building learning systems that connect across your organization

In this episode, we are joined by Gero Hesse, a distinguished “Top HR Influencer” and CEO of EMBRACE, a Bertelsmann Investments company at the forefront of HR technology. Drawing from his deep expertise, Gero offers a profound perspective on how the HR industry must evolve in an era defined by constant change. The conversation delves into the pressing dichotomy of the talent shortage driven by demographic shifts versus the narrative that AI will automate countless jobs. Gero argues that while technology will inevitably replace administrative roles, it will simultaneously create new ones, shifting the core challenge to workforce transformation and reskilling. He envisions a future where HR transitions from an administrative function to a strategic one, responsible for shaping the cultural and ethical rules for a new, blended workforce of humans and machines.

Gero also shares his personal leadership philosophy, which is anchored in radical authenticity and a commitment to building long-term, trust-based relationships. He believes in being the same person at work and in his private life, a principle visibly reflected in the edgy, unconventional branding of his company and its festival-style conferences. Ultimately, Gero provides clear guidance for leaders and HR professionals: as automation handles routine tasks, the enduring value of HR will lie in its ability to manage the human side of the business. He champions a future where the focus shifts to shaping culture, fostering employee identification, and guiding technology integration in a way that amplifies human potential rather than simply replacing it.

We’re joined by John Fallon, former CEO of Pearson PLC, who led its transformation from a 175-year-old publisher to a global digital learning company. Now an author and academic, John shares insights from his new book, “Resurgent,” on how established companies can thrive amidst disruption by leaning into their core strengths while learning to be agile. He argues that a strong, unifying sense of purpose is the most critical factor in navigating the immense challenges of change.

John asserts that the “transformation” aspect of digital change is far harder than the “digital” part itself. He describes the core leadership challenge as bridging the gap between exponential technological progress and the linear way humans adapt. Success requires making change tangible and near-term, and he reframes middle managers not as a “permafrost” layer blocking change, but as the organization’s essential “shock absorbers” who translate strategy and manage the associated anxiety.

Looking ahead, John provides practical advice, from using AI as a tool to create a powerful “first draft” that human creativity can then elevate, to having the patience required for a journey that often takes over a decade. He explains that leaders must protect small, innovative initiatives with non-financial KPIs and foster a culture of continuous change, recognizing that in the modern era, you are either busy being born or busy dying.

→ John’s new book "Resurgent: How Established Organizations Can Fight Back and Thrive in an Age of Digital Transformation"