CodeGuide

Product Hunt

Generate PRDs, specs and wireframes your AI understands.

CodeGuide turns your idea into structured specs your AI coding tools can actually use. Generate PRDs, tech stacks, wireframes, and user flows from plain language or map an existing GitHub codebase so AI understands what it's building on. Works with Cursor, Lovable, Bolt, and 200+ more. Better context in, better code out. No more hallucinations. No more drifting outputs.

Visit product View on Product HuntMar 10, 2026Productivity Developer Tools Artificial Intelligence

Actual performance

126upvotes

7comments

Made the leaderboard

Traction signals

Makers1

Launch Intel predictions

Analyze your own launch →

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

94%94% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

36%36% 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

32%32% 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

15%15% 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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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