Devplan – Generate specs and coding prompts with deep context

Hacker News

Hi, I’m Chris and my partners and I are building Devplan, an AI product development tool that helps teams go from idea to working code faster. What Devplan does: - Creates deep contextual understanding from Github and the web with our open source context engine: https://github.com/devplaninc/contextify - Generates right-sized PRDs, user stories, and tech design based on company context - Gives a ballpark effort and complexity estimate for every user story - Breaks down requirements into structured coding prompts for tools like Claude Code, Cursor, Windsurf, or JetBrains Junie - Integrates with Linear and Jira to push generated project docs and tickets to your tracking system - Lets you kick off projects with images to refine specs with mocks, diagrams, or screenshots - Exports detailed coding prompts as standalone files or use our CLI to work with them directly Why we built it: We believe the next generation of product development will be built with AI at its core. But we’ve seen first-hand how the current tools fall short: - Docs from ChatGPT or Claude are useful but too general and lack context for real workflows - AI coding agents lose context quickly in large repos and generated code often requires re-work - Most approaches to planning for AI coding takes too long and isn't shared or reviewed, which slows teams down AI should remove that friction, not create more of it. We built Devplan to make planning and execution one connected flow. It starts with outcomes, adapts to the size of your project, and produces structured inputs for the coding tools you already use. Instead of bouncing between AI assistants, PM docs, and code editors, Devplan ties it all together so you can move faster without losing context. We have an MVP template for side projects, but the platform is being built for real teams who want to ship product with confidence while staying lean. We are still early and we’re iterating quickly. Would love to hear feedback from other builders. What’s working for you when it comes to planning and building with AI? P.S. If you want to try it, public beta is open: https://www.devplan.com

Visit product View on Hacker NewsAug 28, 2025

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

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.

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

60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: open source, ide, io · Missing: https docs, excited, just released

44%44% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

23%23% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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

Correct prediction on native model

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