A sober read on agentic AI inside regulated firms in 2026: what is genuinely in production, the governance patterns supervisors now expect, and where the frontier actually sits.
Neither keyword nor vector search retrieves reliably on its own. Fuse BM25 and dense vectors with reciprocal rank fusion, and prove the lift on your own queries.
Give every agent a token, action-rate and money budget enforced centrally at the gateway, checked before each call, so autonomy fails closed when a limit is hit.
A software SBOM captures your libraries but says nothing about the model, its weights or its training-data provenance. Here is how to build a machine-readable AI bill of materials that answers what model, trained on what data, is running where.
In most firms, prompt and chain changes ship with no regression testing at all. An LLM eval gate built with Promptfoo scores every change in CI and blocks the quality drop before a customer sees it.
New Zealand’s Biometric Processing Privacy Code sets proportionality, transparency and use limits for facial and voice technology. Existing deployments must comply by 3 August 2026.
There is no comprehensive US federal AI law and state rules keep shifting. A certified ISO 42001 AI management system is the pragmatic anchor that answers state documentation demands and customer diligence at once, with clear limits.
How to score groundedness continuously in a production RAG system using a natural-language-inference model, so hallucination becomes a monitored signal rather than a user-reported failure.
You rarely see an AI agent being manipulated in real time. Plant detectable bait — jailbreak canaries and honeytokens — so a compromised agent trips an alarm the moment it breaks its rules.
A cross-encoder reranker sharply lifts retrieval precision, but only if it fits inside your latency budget. How to add rerank to a RAG pipeline and keep it there.