Bestie, a coding agent that respects you

Hacker News

hi friends! this year, i've been working on a general purpose, native terminal coding agent harness. i remember being absolutely struck the first time i ever used claude code and it could just do things. i'm also a big fan of crush and pi. it's pretty early on. i still have yet to build all the higher-level behaviors that make something go from a harness to a proper agent. it turns out, making a coding agent is incredibly hard because you have to strap a development environment to an llm. in my hubris, i had thought "oh—it's just a terminal app that calls some api's!" i'm trying to provide all the things that i think an agent should have out of the box: subagents, sandboxing, compaction, cross-platform support, a beautiful interface, etc. i would be absolutely delighted if you'd give it a go (as far as safety goes, the sandbox tends to be too restrictive rather than too lenient—i'm trying to figure it out as i go). i made bestie because i don't like it when agents do things and don't tell you what they're doing. or when the harness itself won't provide visibility into things. so bestie is architected around being able to inspect anything that happens in an inspector pane that shows you the inputs/outputs of every tool call, background job update, and shell process.

Visit product View on Hacker NewsSep 8, 2026

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

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

79%79% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

59%59% 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, interface, calls · Missing: plus, intuitive, reviews

40%40% 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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