Gravel – allow non-engineers to make prompt PRs

Hacker News

Hi HN, I'm Yousef. I've built a lot of agents for vertical AI startups in the past few years, and I've become convinced that prompts are code, so must be kept in git . The startups that decouple do so because engineers build agents with git, and non-engineers (lawyers/clinicians/etc) align agents outside of git. So the problem of coordination and versioning shifts to out-of-sync docs and platforms. This is why I built Gravel. An open-source library that embeds a prompt editor straight into your app. Your prompts have a single source of truth (your codebase). After a minute of setup: 1. Your team can make prompt PRs without knowing what a PR is 2. They can review outputs straight from your production traces 3. Those reviews create prompt change suggestions and evals If you're building vertical agents, would love your feedback on it!

Visit product View on Hacker NewsMay 26, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, single · Missing: mac, macos, cursor

98%98% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, reviews · Missing: plus, intuitive, host

33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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