Agent harness build

Turn one brittle AI step into a controlled production workflow.

For teams that know the workflow they want to automate, but need the AI step to produce typed, validated, repairable output before anything downstream happens.

service=agent-harness-build source=service_page

The problem

The model is not the system. The harness is.

A useful response is not enough for production. The workflow needs to know what was extracted, where it came from, whether it passed validation, what failed, what was repaired, and whether it is safe to hand off.

The controlled loop

Input workflow event
Tools API calls
Model LLM output
Validate schema check

Accepted output moves to downstream handoff. Failed output enters repair or human review.

What I build

A controlled loop around one high-value workflow slice.

The engagement is not a vague automation bundle. It produces one working harness around the AI step: tool calls, model routing, typed output, validation, repair behavior, and a clean handoff contract.

Buyer outcome: one real workflow path can run through the harness and show why an output was accepted, repaired, or held for review.

Harness boundary

  • request
  • tool adapters
  • model route
  • typed schema
  • validators
  • repair path
  • event log
  • downstream handoff
Accepted schema + evidence checks pass
Repair missing fields or unsafe handoff

What you get

  • Workflow boundary and handoff contract.
  • Tool/API adapter design.
  • Structured-output schema and validation rules.
  • Repair, retry, fallback, and human-review paths.
  • Basic tracing/event log for each run.
  • Deployment-ready implementation notes.

How the project usually runs

  1. Scope Choose one workflow slice.
  2. Build Wire tools, model, and schema.
  3. Test Run examples and repair cases.
  4. Handoff Document the safe operating path.

Bring one workflow. I will turn it into a controlled slice.

The call starts with the workflow boundary, the action that depends on model output, and the failure cases you cannot afford.