AI writes your code at 10× speed. Prelint makes sure it's the right code - it reviews every PR against your ADRs, docs and past decisions, and catches product drift before it ships. On teams using several AI reviewers, ~40% of the issues fixed before merge are caught by Prelint.
Hi Product Hunt, I’m Wojtek, one of the founders of Prelint.
Coding agents now produce more code than most teams can properly review. The obvious risk is bad code, but the more dangerous risk is good code that quietly builds the wrong product.
We saw this repeatedly in large production projects when we started using agents. A change would clear technical review, pass CI, yet still skip the transactional outbox pattern, introduce an unapproved dependency, change a permission rule or invent a business requirement. Nobody had made that decision, but it was now part of the product.
Prelint catches these decisions before they ship. It reads each change alongside your specifications, tickets and existing product context, then explains what the agent decided, what the consequences are and how difficult the choice will be to reverse. Your team can approve, correct or replace the decision, and Prelint carries that context into the next piece of work.
If you work with ADRs, our clients say it is the best tool they found for enforcing them with agents. On teams running Prelint alongside other AI reviewers, ~40% of the review comments that actually get fixed come from Prelint.
We started in GitHub and now support CLI and MCP, allowing agents to check product decisions while they work instead of waiting for a human to discover the problem at the end.
Prelint is not another technical code reviewer. These tell you whether the code works. Prelint tells you whether you should be building it.
If coding agents are contributing to your product, sign up at https://prelint.com, connect a GitHub repo and see what they've been deciding on your behalf. Then tell us what you like and what you'd love to see on top of it!
Use code: PH100 to get 100$ in additional free credits
AI-generated code will only become more common, so governance tools like Prelint are going to be must-have!
Congrats Wojtek. Did you build this out of your own frustration or what inspired to think of solving this problem?
Congratulations. Does Prelint suggest the closest approved design pattern when it detects a violation?
When you build with AI, product consistency tends to erode gradually. Tools like Prelint can help stop that before it becomes expensive. Congrats on the launch.
the "decision ledger vs check code against docs" framing is what actually clicks for me. i keep a section in my own CLAUDE.md that's a manual, extremely low-tech version of this, not architecture notes, just "already tried this, here's why it didn't work" so the agent doesn't quietly rebuild the same mistake three months later. what i can't do by hand is catch the drift in real time instead of noticing the pattern repeating after the fact.
question on an existing repo: does the ledger backfill decisions from git history, or does it only start learning from the point you connect it?
Prelint is interesting because it seems to be focusing on the product intent. A lot of times AI can take its own direction, catching it soon from drifting by a tool is a great idea indeed!!
Being a SaaS founder, I love this idea. Preventing product drift feels just as important as preventing bugs. 👏
Congrats on the launch! I feel like the opposite is often the case where the ADR/docs etc are out of date and stale. How do you trust the materials it is basing the drift detection on?
When Prelint flags a conflict, can you jump straight to the exact source and version behind that decision? That would make it easier to tell a real conflict from stale context.
CodeParrot used real production traffic to replay against your Pull Request code, automatically finding breaking API and performance changes, but then they just disappeared due to claude and GitHub copilot so how do you think its different from them
AI can generate code quickly, but making sure it stays aligned with product decisions is the harder problem. Probably the first product on PH which is tackling this issue.
The interesting bet here isn't catching bugs. It's catching code that works but quietly contradicts a decision the team made six months ago, and nobody has a linter for that. How much ADR discipline does a team need before Prelint has enough to check against?
Interesting approach. How does Prelint actually understand product context? Does it integrate with tools like Jira, Linear, Notion, or ADRs automatically, and how much setup is required before it starts providing useful feedback?
Congrats on the launch! "Product drift" is a great name for a problem I didn't have a word for. The code compiles, tests pass, and it still quietly isn't the thing you asked for. Catching that at lint time is the right layer. Does it work across any codebase, or are you starting with specific languages?
Hey, I've been using Prelint for the last couple months - I really like that it reviews the product reasoning behind a PR. And it's smart about scaling effort - most small, low-stakes PRs just get a quick approval, while it goes deep on ones that actually touch permissions or auth, even if the diff is tiny. It can be a bit too nitpicky at times, but that's a much better failure mode than rubber-stamping things through.
Quick question - do you charge for one-line PRs, or are those free/exempt from billing?
Congrats on the launch - rooting for you!
Congrats on shipping this! Product drift is such a sneaky problem, the code works fine but the product quietly became something else. Does Prelint only catch drift in new pull requests, or can it also scan an existing codebase for decisions that already slipped through?
About Prelint on Product Hunt
“Prevent product drift in AI-written code”
Prelint launched on Product Hunt on July 29th, 2026 and earned 458 upvotes and 107 comments, earning #1 Product of the Day. AI writes your code at 10× speed. Prelint makes sure it's the right code - it reviews every PR against your ADRs, docs and past decisions, and catches product drift before it ships. On teams using several AI reviewers, ~40% of the issues fixed before merge are caught by Prelint.
Prelint was featured in Software Engineering (42.8k followers), Developer Tools (516.6k followers) and Artificial Intelligence (474.8k followers) on Product Hunt. Together, these topics include over 195.1k products, making this a competitive space to launch in.
Who hunted Prelint?
Prelint was hunted by Rohan Chaubey. 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 Prelint stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Rohan Chaubey
Hi Product Hunt, I’m Wojtek, one of the founders of Prelint.
Coding agents now produce more code than most teams can properly review. The obvious risk is bad code, but the more dangerous risk is good code that quietly builds the wrong product.
We saw this repeatedly in large production projects when we started using agents. A change would clear technical review, pass CI, yet still skip the transactional outbox pattern, introduce an unapproved dependency, change a permission rule or invent a business requirement. Nobody had made that decision, but it was now part of the product.
Prelint catches these decisions before they ship. It reads each change alongside your specifications, tickets and existing product context, then explains what the agent decided, what the consequences are and how difficult the choice will be to reverse. Your team can approve, correct or replace the decision, and Prelint carries that context into the next piece of work.
If you work with ADRs, our clients say it is the best tool they found for enforcing them with agents. On teams running Prelint alongside other AI reviewers, ~40% of the review comments that actually get fixed come from Prelint.
We started in GitHub and now support CLI and MCP, allowing agents to check product decisions while they work instead of waiting for a human to discover the problem at the end.
Prelint is not another technical code reviewer. These tell you whether the code works. Prelint tells you whether you should be building it.
If coding agents are contributing to your product, sign up at https://prelint.com, connect a GitHub repo and see what they've been deciding on your behalf. Then tell us what you like and what you'd love to see on top of it!
Use code: PH100 to get 100$ in additional free credits