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CheepCode – Write tasks in Linear/Jira/etc. Get PRs in GitHub. $1 each

Hacker News

CheepCode – Write tasks in Linear/Jira/etc. Get PRs in GitHub. $1 each

Hi HN, while I made a new account recently, I've been a member of the community for over a decade. In that time, I've learned an incredible amount from all of you. One of the most important lessons is that, if you're not (at least slightly) embarrassed of your first version, you waited too long to ship. Well, I realized yesterday that I had waited too long anyways! My headless coding agent, CheepCode, went into private beta a few weeks ago. I was putting together some demo apps and the last few things I wanted to have ready before launch, when OpenAI dropped their coding agent last Friday. Then as GitHub, Anthropic, and Google launched on Monday, well, I knew what I had to do. I scrambled, scratched off the necessary to-do items, and have emergency-launched CheepCode to public release: https://app.cheepcode.com if you want to poke around (first 5 runs are free, no credit card required). CheepCode connects to your project management app (we support Linear today) and picks up unassigned tasks. It will move the task to "In Progress" and start working on it, then submit a PR in GitHub when it's done. Using CheepCode, I "code" on my phone, creating Linear tasks and checking the PRs when they roll in minutes later (or hours later when I'm available). CheepCode works in a fully-integrated Linux development environment. It can browse the web, use Docker, install packages, and recursively problem-solve to work around issues. It is incredibly resilient and submits quality code changes, often exactly what I would have written myself (with ~15 years of professional software development experience). While I'm still working on quantifying the output quality, I find that in practice it doesn't fall prey to the common problem of "doing too much" that people report with other tools. CheepCode also uses a journal to help you understand its process. It's entirely headless, so you can't interact with the agent while it's working, but you can still see how its thoughts and intermediate progress for debugging/optimization. With all that said, please keep in mind it is still incredibly early for CheepCode! There are tons of features I'm eager to build, like responding to pull requests (this one should be done in the next week or so!), notifications, and more integrations (GitLab, Jira, Asana, Monday, etc). If you read this far, thank you so much! It's a huge honor to be launching on HN today. I'll be around to answer any questions. - Max

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Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: agent, google, apps · Missing: mac, agents, macos
96%96% 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.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
91%91% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: apps, google, way · Missing: mobile apps, ios, personal
35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit
14%14% 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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