Brendan O'Leary has looked at trillions of tokens of real agent usage. His conclusion should change how you run your next vendor evaluation: developers adopt agents they trust, whatever the benchmark says. The rest of today is thinner. One serious conversation about agent autonomy in finance, one useful research idea and one paper you can skip.
1. Agent adoption is a trust problem, and the failures are in your own stack
What happened: At InfoQ, Brendan O'Leary set out a four-rung 'AI adoption ladder' based on real developer usage data. The title says 25 trillion tokens and the abstract says 40 trillion. Either way, it's a large sample.
Why it matters: If you're choosing a coding or agent platform from a leaderboard, you're answering the wrong question. O'Leary puts the failure points in context construction, multi-model routing and similar plumbing. Your engineering team owns that layer. The model vendor doesn't.
I'd ask two things this quarter. Which rung are your teams actually on? And who owns the context and routing layer? If nobody can name an owner, a model upgrade won't move adoption, because better models don't fix that layer.
2. OpenAI, Anthropic and banks are drawing the line on agent autonomy
What happened: At AI Engineer New York, frontier labs and financial firms discussed how much autonomy to give agents while keeping consequential decisions under human control.
Why it matters: Regulated firms are now discussing agent autonomy openly, and your organisation should decide where it stands before a pilot decides for you. Write down which actions an agent may take alone and which need a human sign-off, and do it before procurement starts.
3. Don't send every agent step to a frontier model
What happened: The EdgeWise paper runs long-horizon agents on smaller edge models and passes only the hard steps to frontier models in the cloud.
Why it matters: It's only a paper, but the routing logic is worth copying now.
The bottom line: Today is mostly about agents and how organisations take them up. Harness^2, a paper on recursive self-improvement of agent harnesses, is interesting research with nothing for you to act on yet, so I've left it out. My one recommendation is to name an owner for the context and routing layer of your agent stack and put the autonomy boundaries in writing. Teams that have done both will adopt agents faster than teams waiting for the next model release.
— Daniel · usqrd.com · reply to this email, I read everything