The hard part of AI coding isn't generating code — it's controlling quality, safety, and drift. Kaushik and Iury break down harness engineering: the five pillars for shaping an agent's environment and what it looks like when teams build custom harnesses from scratch.

Full shownotes at fragmentedpodcast.com.

Show Notes

Why it matters

Harness Engineering -
OpenAI's post on building their Codex codebase (~1M lines of code, 1,500 PRs
merged, zero manually written)

Shaping the harness

The Feed's Lost and Found -
Iury's newsletter consolidating harness engineering themes

Agent legibility
Closed feedback loops
Persistent memory
Entropy control
Blast radius controls

Building the harness

Minions: Stripe's one-shot, end-to-end coding agents -
Stripe forked Goose to build custom agents for their codebase
Goose - open-source coding agent from Block
Superpowers by Jesse Vincent - skills
that enforce a proper software engineering process
Open Code - open-source coding agent you can fork and
customize

Other resources

Agent Harness Glossary -
Latent Patterns
Towards self-driving codebases -
Cursor
Agentic Workflows -
GitHub Next
Future of Software Development -
ThoughtWorks

Get in touch

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We want to hear all the feedback: what's working, what's not, topics you'd like
to hear more on.

Co-hosts:

[!fyi] We transitioned from Android development to AI starting with
Ep. #300. Listen to that episode for the full story behind
our new direction.

307 - Harness Engineering - the hard part of AI coding