Agentic engines
Systems that read live state and return a decision you can act on, not a paragraph you have to interpret.
An agent that writes prose is a demo. An engine that emits a typed decision with a confidence and a reason code is something a downstream system can consume, log, and be held to.
The build is a classifier or router over live state, with the plumbing that makes it safe: a fixed output schema so nothing downstream has to parse free text, confidence tiers with defined behaviour at each level, and a fallback that is explicit rather than whatever the model happened to say.
Guardrails come first. Every decision is logged with the inputs that produced it, so a surprising output can be traced rather than argued about.
What you get
- Typed decision output with a fixed schema
- Confidence tiers with defined downstream behaviour
- Explicit fallback and refusal paths
- Full input and output logging for every decision
- Evaluation harness so changes can be measured