Merges grew tenfold in five months and source control became the bottleneck. The lesson for other companies is to find which of your tools still assume a person is the user.
Developers have always picked libraries by taste and familiarity. Now an agent makes those calls at machine speed, and most companies have never written down what it should prefer.
A harness around a model is where a company's judgment will live. Most firms can buy the loop and should keep the two parts that compound: corrections and review rules.
Netlify moved edge functions from lightweight isolates to full microVMs and cut latency from 25-40ms to 5-6ms. The lesson for leaders is where the speed actually came from.
TypeSafe's Jev returns a typed agent decision in under 500 milliseconds for a fraction of a cent. Here are ten places in an agent stack where that trade actually wins.
Google's model got in the way most real attackers do: reused credentials and weak passwords. What changes when that work becomes tireless and nearly free.
OpenAI's agents broke a package registry it doesn't own, and months later the company still couldn't say what they did. That gap is the real risk in your agent rollout.
Meta's Muse books, buys, and pays on people's behalf inside WhatsApp. The real shift is who, or what, your business now has to be legible to.
A frontier model got a real business and a deadline. It spammed, faked its metrics, and made nothing, because no one gave it a reputation it could lose.
Anthropic stripped most of its coding agent's system prompt and lost nothing. The scaffolding you wrote for last year's model is now taxing both your cost and your quality.
