Inlay

AI makes producing documents almost free. But reading them? That cost hasn't changed. When "Ask Claude" doesn't mean the colleague from France, you have a problem.

"Are we building the right thing?" is a question as old as engineering itself. GenAI made it easier than ever to skip. Time to start asking again.

The IT consolidation was coming long before ChatGPT. AI just gave it a narrative. And the people who actually understood the systems? They're updating their LinkedIn.

OpenAI valued at $852 billion without profit. Sora lost $1 million per day. Big Tech spends $700 billion yearly, and most of it vanishes into chips and electricity. IPOs are coming. Before you buy in, remember T-Online. That was counted as a safe bet, too.

The new ThoughtWorks Tech Radar reads like a warning letter. Cognitive debt. Broken productivity metrics. Terms nobody agrees on. If you've been reading my posts, none of it will surprise you. It's always nice to get evidence that I'm not completely crazy and making all of this up.

I listened to a podcast about "assisted migration" for trees and plants. A fantastic topic for a systems thinker. I listened to an AI podcast just before that. And then a few uncomfortable synaptic connections clicked.

Spec-Driven Development is the hot new thing in vibe coding. Write a perfect spec, let the agent work, sit back. Sounds familiar? We called it Waterfall. We hated it. We sucked at it. Why do we think we're suddenly ready for it now?

The S-to-P Jig is an advanced cognitive jig from DSRP. Scrum is a perfect example. And understanding it explains why good Scrum Masters adapt the framework instead of just following it.

When it takes a team two weeks to add a button, the problem isn't the button. And the solution isn't AI. I've been there. Literally. A simple button on a screen. Two calendar weeks. And if you're on the outside looking in, you think: what are these people doing all day? Are they incompetent? Lazy? You see a button. You think it's a button problem.

I was listening to the A/B Testing podcast the other day, episode 229, where Alan Page had my friend Chris Armstrong on as a guest. At one point they were talking about Verification and Validation. Two concepts that have been around forever. Two simple questions, really. "Are we building the thing right?" That's verification. "Are we building the right thing?" That's validation.

OpenAI just closed a $122 billion funding round, pushing their valuation to $852 billion. Let that sink in. A company that isn't profitable yet, valued higher than most countries' GDP. An IPO (Initial Public Offering, when a company sells shares to the public for the first time) is expected by the end of the year. Big Tech is planning to spend nearly $700 billion on AI this year alone.

ThoughtWorks just dropped Volume 34 of their Tech Radar, and it reads less like a technology map and more like a warning letter. Several signals on the same screen, all pointing the same way. If you've been following my posts, none of them will surprise you. What's new is that one of the most respected consultancies in our industry is now saying it out loud.

AI has made producing documents almost free. A few prompts, a couple of minutes, and you have a risk analysis, a complete SOP, or a technical file section that looks polished and professional. The cost of output has collapsed. Not to zero, mind you. It takes electricity, water cooling the data centers, and money for the API tokens. But compared to the cost of a human writing it?

I recently listened to a podcast about "assisted migration." Scientists are helping plants and trees migrate to new areas because climate change is happening too fast for natural evolution. A tree that thrives at a certain temperature profile can't just walk north when its habitat becomes inhospitable. And also the seeds don't spread that quickly. Think acorns. So researchers look up international catalogs, find similar species that already grow in warmer climates, and carefully introduce them to new regions.

Imagine you want to buy a new bike. Before you even walk into the shop, you already have a picture in your head. Where will you ride? City commute, gravel paths, weekend tours in the mountains? Luggage and how much? How often? You build a little mental model of your situation. And then, almost without noticing it, you walk into the shop and use that model as a lens.

As of when writing this post in the first days of April 2026, the vibe coding community is buzzing about "Spec-Driven Development." Write a perfect specification, let the AI agents loose, sit back, and watch the magic happen. Revolutionary, right? For me, it feels like a déjà vu from the 2000s. Back then, we called it Waterfall or V-Model. The idea was the same: define everything upfront, hand it over to the people who build it, and collect your finished product at the end.

I have to say the mentioned project in the post was not the worst waterfall. But it was also a project with a few hundred people overall and a lot of expertise and specialists.

I have not seen many places over the last 26 years that invested in good requirements writing. A few, yes. And the better the requirements, the better the waterfall or scrum or whatever. But as most people‘s crystal ball seems to be broken, the requirements were accordingly.