Hi

Hide – A Headless IDE for Coding Agents

Hacker News

Hide – A Headless IDE for Coding Agents

After making several attempts to make coding agents work I noticed the same pattern: the better the tools you give to agents, the better outcomes they produce. So I thought what if I gave them a proper IDE except it would be headless since agents don’t need a UI? That’s how I came to build Hide, a headless IDE for coding agents. Hide is built on top of existing tools and standards for coding like devcontainers and LSP. When given a code repo, Hide spins up a devcontainer, installs the dependencies, and provides APIs for codebase interaction. Developers can craft custom toolkits using Hide APIs or use Hide's pre-built toolkits for popular frameworks like Langchain. The project is still a work in progress but it can already be tried. I’m curious to hear what you think.

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Actual performance

4points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, using · Missing: mac, macos, cursor
97%97% 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: exist, existing, ide · Missing: https docs, excited, just released
74%74% 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
64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
39%39% 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
37%37% 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
17%17% 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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