AI Harness Engineering

A harness gives agents the rules of the work: what context to gather, which policies apply, what artifacts to produce, when humans approve, and what evidence proves the output is ready.

These are representative examples, not the full set.

1. 01

   Scoped request

   A product, modernization, or engineering request enters the harness with goals, constraints, and known risks.

2. 02

   Profile & policy

   The run resolves its domain profile, repo context, guardrails, and allowed tool capabilities.

3. 03

   Contract bundle

   Fail-closed contracts define required artifacts, schemas, handoffs, and completion checks.

4. 04

   Research

   Agents gather code, design, search, brand, prior decisions, constraints, and risks against the contract.

5. 05

   Plan

   A written run plan maps findings to implementation steps, verification scope, and open decisions.

6. 06

   Human gate

   Human approval gate

   I or the team review, redirect, or approve the bounded plan before implementation moves forward.

7. 07

   Implementation

   Agents, engineers, skills, and templates work inside approved paths using the harness constraints.

8. 08

   Verified

   Verify & improve

   Tests, manual checks, tracing, documentation, and review close the loop for the next run.

• Created a reusable harness pattern that turns agent-assisted work into scoped plans, governed implementation, and reviewable evidence.
• Applied the Greenfield Harness across client-facing Next.js + TypeScript builds with other engineers and agents, helping select projects move from design to production in under two weeks.
• Extended the same pattern into a broader harness portfolio spanning product, search, brand, analytics, accessibility, performance, security, compliance, documentation, and QA workflows.