Harness Engineering

Straighten the path from prompt to production. Find friction in your agent traces and engineer the skills, rules, and context that let agents do more on their own.

Improve with every trace

0insights

developmentcode reviewprod

session

code-review commenthuman edit

incidentchurn

Continuous improvement, built on data — not vibes

Run on the platform

Hook into key moments in the lifecycle of AI-code, and continuously improve the effectiveness of your agents.

Skill generator

on_session_ended

Spots the workarounds agents keep repeating and writes them up as reusable skills.

Harness evals

on_schedule(weekly)

Checks whether last week's skills and rules actually made agents more autonomous.

Documentation updates

on_pr_synced

Updates the docs each PR touches so they match what actually shipped.

AGENTS.md maintainer

on_pr_merged

Keeps AGENTS.md current with the rules your agents lean on most.

Session summarizer

on_session_ended

Records why each change was made, so the next agent doesn't have to guess.

Friction report

on_schedule(Friday, 10am)

Every Friday, shows where agents stalled, retried, or handed work back to a human.

Workflow experiments

on_schedule(nightly)

Tests workflow changes overnight and reports what cut tokens or raised autonomy.

Related code

on_pr_commit

Maps each change to its upstream and downstream so agents see the blast radius.

Code standards

on_pr_opened

Checks every PR against your standards before a human reviews it.

Update review agent

on_review_comment

Turns the review comments you keep leaving into automatic checks.

Build the software that builds your software

Mine agent sessions across your team to build and continuously improve the skills, rules, and context that help agents work more autonomously.

Mine for friction

Analyze agent sessions across your whole team to surface the friction that keeps coming back — the moments where agents stall, retry, or hand work back to a human.

Sessions

stallretryhand-back

Repeated friction

Missing test fixtures

×14

Vague API contracts

×9

Local env setup fails

×6

Build workflows and skills

Create reusable skills and workflows — then see how often they're used and what impact they have on token efficiency, agent autonomy, and acceptance rates.

Track skill activation and impact
Measure the impact of workflows like spec-driven development

Team skills

/extract-component

/add-tests

/migrate-api

+19%

more autonomous

+34%

Code Review accepted

Build your own agents

Build and improve your team's code review, maintenance, and documentation agents — and everything in between. Replace vibes with real data.

+58%

agent autonomy

trailing 90 days

time →

Compound context

Generate rules and skills, and capture the important context from your team's prompts — so your agents start where the last one left off.

Requirements

Architecture

Decisions

Straighten the path from prompt to production

Git AI helps your team save tokens, shorten cycles, reduce re-work, and improve code quality.

promptproduction

31−71%

Human turns

840K−38%

Tokens

211−76%

Tool calls

Autonomy

Build your team's agentic SDLC

Git AI gives you the data you need to reduce token spend, increase agent autonomy, and improve software quality across every repo.