ICYMI 2026-06-27: Honor Expertise
Our weekly roundup of signals from the AI noise, for humans leading change.
Ford is rehiring engineers
Has your organization laid off its greybeards “because AI”? Soon, it might have to reverse that decision. Ford just did: after trying to replace experienced engineers with AI, the company realized its hard earned knowledge went out the door — and AI won’t work without it. As one manager explained, “Mistakenly we thought that by just introducing artificial intelligence and ingesting the design requirements that we had, that that would produce a high-quality product.” Alas, in most organizations, expert knowledge is latent. AI will only work if it’s made explicit and architected. But as Greg and I have long argued, it’s best to use the technology to augment humans rather than replace them. If your leadership is still considering replacing experts with AI, send them this post.
CTO Report on cognitive debt
This feels ai-written, but I still found it useful: an informal report from a gathering of CTOs on what they’re seeing on the field. TL;DR: the AI free ride (i.e., unlimited budgets) is over; it’s time to invest in architecture. If your leadership is still suggesting replacing complex workflows with AI, send them this one.
Building Reliable Agentic AI Systems
An in-depth case study on how Bayer built a reliable AI research assistant for their (highly regulated) business. They turned decades of latent data in unstructured PDFs into highly structured context, implemented specialized agents to use that data, and created mechanisms to anticipate and correct the inevitable failures. Bottom line: it’s not enough to give LLMs access to your data; reliability requires architecture.
Big-time self-disruption
Tide is P&G’s biggest brand. Every thirty years or so, they risk it by introducing a new form factor (e.g., pods.) This cycle is about to start again with new detergent “tiles” — a bold risk. How far is your organization willing to go to disrupt itself? You likely don’t have a $2b annual R&D budget, like P&G does. They also have structures in place (including decades-long brand equity) that allow them to make such bets. The challenge for the rest of us? AI makes innovative moonshots more feasible, but bold bets without support structures and solid market signals aren’t reinventions, they’re expensive gambles.
The Birth of the Flywheel
If you and I have spoken at length, there’s a good chance we ended up discussing the Walt Disney Company. I’m a big fan, and have written about what we can learn from them when designing complex information environments and beyond. But this four-plus hour episode of the Acquired podcast goes much deeper, diving into the company’s history up to the early 1980s. The focus? Disney’s (accidental?) discovery of the synergistic business model they exemplify. It’s a history lesson on the successful merging of art, commerce, and technology. Takeaways: 1) build a diversified yet cohesive business model that creates self-reinforcing loops and 2) honor the Walts (i.e., creative geniuses) in your team willing to bet the farm — so long as you have Roys (financial geniuses) keeping the company alive. (The business model, you can design for. The geniuses… not so much.)
See you next week!
— Jorge