Su

Suzerain – How much autonomy do you give your AI coding assistants?

Hacker News

Suzerain – How much autonomy do you give your AI coding assistants?

I built a simple CLI that analyzes your Claude Code session logs locally and shows you how much autonomy you give the AI vs. how much you intervene. I've noticed on myself that bash command acceptance is where all the variance is. Every other tool (Read, Write, Edit) gets approved ~100% of the time. Bash is the one place people actually say no. Based on that signal, it classifies your style into a governance archetype (Delegator, Autocrat, Strategist, etc.). Fun lens, not a psychometric test, the thresholds are calibrated on mostly MY OWN usage so far. Would love to hear feedback and gather more datapoints. pip install suzerain suzerain analyze Zero external dependencies, stdlib only, Python 3.10+. Nothing leaves your machine unless you opt in. https://github.com/TheApexWu/suzerain

Visit product View on Hacker NewsJan 29, 2026

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

80%80% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

43%43% 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

29%29% 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

28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

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

22%22% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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.

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