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