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Agents write code. Help your team plan, understand, ship, and run it. 10 MIT-licensed tools for agent workflows, codebase learning, local CI, observability, tenant isolation, RPC access, log redaction, messaging, and GitHub attachments.
Your agents write code faster than your team can review and ship it.
So review becomes the bottleneck. And the code that does get merged isn't always code your engineers fully understand.
Today we're open-sourcing 10 engineering tools. It's how we work with agents ourselves.
Review that keeps up
- Agentic Workflow Kit brings fresh reviewers into Claude Code and Codex every few commits and carries each change through to a reviewed PR.
Understand what your agents shipped
- Codebase Trail turns your code and merged PRs into practice questions, so engineers understand what their agents shipped.
What AI-written code still has to get right
- 8 tools for local CI, Go linting, tenant isolation, log redaction, reliable messaging, observability and PR evidence.
If you tried Agent Desk, Session Intelligence or Tetriz Harness from our earlier launches: those show how your agents are set up and how their sessions go, and keep that setup current. These cover the work itself.
Where to start: Agentic Workflow Kit, if review is your bottleneck.
All 10 are MIT-licensed. Read the code, run it on a real branch, and tell us what breaks.
One question for teams building with coding agents: when do you bring in a reviewer? Every commit, every PR, or only when something looks off?
The review bottleneck framing rings true — I have found the hardest part is not generating code, it is trusting what got merged a week later. The Codebase Trail idea is the part I would reach for first: turning merged PRs into practice questions seems like a much better way to build real understanding than just re-reading diffs. I am curious how it handles a large, fast-moving repo — does it focus on recent changes, or try to cover the whole codebase at once?
About Tetriz Engineering Kit on Product Hunt
“Open-source tools for everything around AI coding”
Tetriz Engineering Kit was submitted on Product Hunt and earned 5 upvotes and 2 comments, placing #46 on the daily leaderboard. Agents write code. Help your team plan, understand, ship, and run it. 10 MIT-licensed tools for agent workflows, codebase learning, local CI, observability, tenant isolation, RPC access, log redaction, messaging, and GitHub attachments.
Tetriz Engineering Kit was featured in Open Source (69.1k followers), Developer Tools (522.8k followers), Artificial Intelligence (483.2k followers) and GitHub (41.5k followers) on Product Hunt. Together, these topics include over 281.2k products, making this a competitive space to launch in.
Who hunted Tetriz Engineering Kit ?
Tetriz Engineering Kit was hunted by Prasanna R. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Tetriz Engineering Kit stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Prasanna R
Hey Product Hunter,
Your agents write code faster than your team can review and ship it.
So review becomes the bottleneck. And the code that does get merged isn't always code your engineers fully understand.
Today we're open-sourcing 10 engineering tools. It's how we work with agents ourselves.
Review that keeps up
- Agentic Workflow Kit brings fresh reviewers into Claude Code and Codex every few commits and carries each change through to a reviewed PR.
Understand what your agents shipped
- Codebase Trail turns your code and merged PRs into practice questions, so engineers understand what their agents shipped.
What AI-written code still has to get right
- 8 tools for local CI, Go linting, tenant isolation, log redaction, reliable messaging, observability and PR evidence.
If you tried Agent Desk, Session Intelligence or Tetriz Harness from our earlier launches: those show how your agents are set up and how their sessions go, and keep that setup current. These cover the work itself.
Where to start: Agentic Workflow Kit, if review is your bottleneck.
All 10 are MIT-licensed. Read the code, run it on a real branch, and tell us what breaks.
One question for teams building with coding agents: when do you bring in a reviewer? Every commit, every PR, or only when something looks off?
Code:
https://github.com/tetriz-ai/agentic-workflow-kit
https://github.com/tetriz-ai/codebase-trail
https://github.com/tetriz-ai/local-ci
https://github.com/tetriz-ai/wvet
https://github.com/tetriz-ai/observability-as-code
https://github.com/tetriz-ai/pgtenant
https://github.com/tetriz-ai/protoauthz
https://github.com/tetriz-ai/logredact
https://github.com/tetriz-ai/outbox-comms
https://github.com/tetriz-ai/ghattach
Built by the Tetriz team.