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Essays on AI, growth, and operating in private equity environments. Long-form when the idea earns it. Short when it doesn’t.
By Yannic Desch · Walldorf · Essays auf Deutsch →
Essays
Development stopped being the bottleneck. The constraint moved to the start of the cycle, to discovery, signal and feedback, and most product teams still run that part by hand.
Read →The fastest way to speed up AI adoption isn't a better tool. It's a job description most companies haven't written yet.
Read →We're rebuilding a legacy platform with a team size that would have been impossible to justify two years ago. The math changed — but only if you ask the right question.
Read →94% of companies keep increasing AI spend even without measurable returns. The problem isn't budget — it's sequence.
Read →Founders keep asking if AI will commoditize them. They're looking at the wrong layer.
Read →I never created a Chief AI Officer role on my team. Here's what I did instead — and why the title was never the point.
Read →We ran four AI pilots in 18 months. Three died before production. The pattern is consistent — and it's not a technology problem.
Read →Agents don't fail like software. They drift. Here's what every deployed agent needs before it leaves testing — and why ownership matters more than monitoring.
Read →Why I finally built a home for my thinking — and what you'll find here.
Read →74% of AI's economic gains go to just 20% of companies. The gap isn't budget or talent. It's the question they started with.
Read →Most companies have deployed AI tools. Most employees aren't using them. The gap is a workflow problem, not a technology problem.
Read →60% of companies report minimal value from AI despite significant investment. That's not a technology problem. That's a question problem.
Read →How AI dissolved Microsoft Office's three competitive moats — format lock-in, muscle memory, and ecosystem gravity — and why Copilot doesn't solve the real threat. A framework for understanding AI's impact on software incumbents.
Read →The Agent Orchestrator: why PE-backed companies need a dedicated AI adoption role embedded in the business — not in IT. The hire that accelerates AI implementation 5x, measured in EBITDA impact rather than deployment count.
Read →Entry-level job postings are down 35% since 2023. AI is removing the grunt work where judgment develops — creating an experience gap that won't show up in the workforce until 2030. Research from Harvard, King's College London, McKinsey, and the WEF.
Read →A three-phase AI implementation framework for PE-backed companies: Plant (internal automation to free margin), Build (internal AI capability), Harvest (revenue impact). Why skipping phases is the most expensive AI strategy mistake in private equity.
Read →Notes
Why SMBs move faster on AI than enterprises: one database, no integration debt, no steering committee. The Leaner Stack Paradox explains why the simplicity that makes small companies feel 'behind' on technology is exactly what lets them win on AI adoption speed.
Read →Why building AI prototypes beats writing AI presentations — and how hands-on building is the only real AI curriculum for executives. Two concrete examples: image-based analysis and a voice assistant for tradespeople built with Twilio, ChatGPT, and Railway.
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