ServicesService
Production Agentic AI
Getting an agent to demo is easy. Getting it to run all month without burning the budget or asserting things that aren't true — that's the actual job, and it's the part I do.
When you'd call me
- Your agent prototype demos well, but in production the LLM bill keeps climbing and nobody can say which calls are worth the money.
- You need tool-calling that picks the right tool reliably — not a prompt that behaves four times out of five.
- The agent occasionally asserts things that are simply wrong, and in your domain "occasionally" is too often.
- Your team has been circling the same reliability problem for weeks and needs someone who has already paid this tuition.
What I do
- Budget envelopes — every agent run gets a hard cost ceiling enforced in code, not hoped for in a prompt.
- Retry and fallback chains — cheap model first, escalation only when confidence drops, a defined stop instead of an infinite loop.
- Adaptive depth — simple requests take the short path; the expensive reasoning loop is reserved for queries that earn it.
- Model tiering — routing across model sizes by task profile, with the cost difference measured per task instead of guessed.
- Verification layers — claims get checked against sources before a user ever sees them.
Numbers, not adjectives
Nova's agentic tool-selection system started at roughly $4,000 a month for the workload it carried. After budget envelopes, model tiering and adaptive depth, the same workload ran at about $40. That isn't a benchmark from a paper — it's a production bill I watched go down.
Field notes
From $4,000 to $40 a month: the real cost curve of agent guardrailsEach optimization layer, with the numbers attached.Agentic AI guardrails: stopping the while(true) from burning your token budgetThe failure modes that only show up after the demo.The week an LLM hallucinated a political position — and a journalist nearly quoted itWhy I treat verification as a layer, not a hope.
Where we'd start
Discovery, one to two weeks at a fixed fee: I audit your existing agent — call traces, prompt architecture, cost per task — and you get a cost projection plus a concrete plan. If the honest finding is that you don't need an agent at all, that goes in the document too.