If it weren't implemented by cloudflare natively, would you be ok using a library or something that wraps or hooks onto your IaC to wrap entry points with a worker (proxy or circuit-breaker, conceptually) with various types of limits (real-time estimated spend, or just counts of operations, or just a on/off switch wired to an email alert). I'm pulling a few of these threads at the moment since I've been ramping up my cloudflare usage.
I do think it is important to have autonomous discoverability with domain-anchored trust, whether through .well-known or DNS records or DNS over HTTP. It looks like cloudflare has already added a bunch of observability into their products around this area, and I am investigating too [1]. It seems like the number of services needing these, and the amount needed per org should both go up with more agentic use cases.
I believe auth.md is also a recent example that uses .well-known
I've been getting tired of implementing webhooks and sync the same old way.
https://webpoke.sudoscience.dev/ seems simpler.
I did a poc using s2.dev and val.town [1] and am using the general idea to explore with TLA+ to see how it would model it to falsify the claims.
Premiered May 14, 2026
Ron Minsky discusses Jane Street's approach to AI adoption throughout their SDLC at Bug Bash 2026.
Ron stakes out their position that AI workflows should maximize human effectiveness and understanding rather than replacing humans entirely. At Jane Street, many traditional (aka pre-Claude) software engineering practices have become more important rather than less. Type systems help provide fast feedback and enforce invariants that agents can understand. Expect tests allow developers to see system behavior and create deterministic simulations at the library level. Code review remains crucial for maintaining code quality and human understanding, even though agents change the dynamics. Finally, he touches on Jane Street’s growing interest in formal verification, and the impact of agents making previously expensive approaches, like formal methods, more practical.