Two movements meet: AI is getting production responsibilities, and production data is flowing through AI. Anthropic’s September report, malicious routers, training data provenance and model drift show what to verify before an AI reaches production.
DHH’s account of AI coding raises a workflow question, not a universal ranking of developers. I separate requirements from implementation preferences and set out a practical review process.
Local inference gives control over weights and configuration, not a guarantee of political neutrality. A practical guide to evaluating framing, sizing KV memory and enforcing hybrid routing boundaries.
OpenRouter put numbers on a pattern agent builders already use: a panel of models with a judge synthesizer beats the best single model, and a budget panel matched frontier quality at half the cost. What that means for your AI platform.