Blogs

Every technology choice is a trade-off, yet most teams argue over options that lose on every axis. A century-old idea makes the real decision visible.

A DeepMind researcher argues LLMs can reason and prove but never originate. That boundary decides where AI multiplies your team and where it just recycles the past.

AI collapses the cost of maintaining software you didn't write, so part of the buy column becomes buildable. The catch is the forks you now have to govern.

An MIT and Stanford study found AI gives sound financial advice, but the gains went to sophisticated users. Closing that gap is a product decision, not a literacy problem.

A team ran an AI cost-routing layer for four months, then shut it off. The savings had not vanished. They had moved to a budget nobody was measuring.

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.

Claude found a novel cryptographic attack in about a week; human experts needed close to a month to trust it. That gap, not model quality, decides where AI pays off.

Cookie banners produced 90% opt-in and almost no real consent. As Europe tries to fix them with a browser signal, the same design mistake is being wired into AI rules.

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.