SilentGPT – Terminal ChatGPT Client in C (AES-256, No Telemetry)

Hacker News

I built SilentGPT as a fully terminal-based ChatGPT client written in C. Why? I needed something minimal that respects my privacy and runs anywhere — even airgapped or offline shells. Features: - Written in C, single portable binary - AES-256-GCM encryption for chat history and API keys - Supports multiple tokens via `--token` - Optional password protection via `--secure` - No OpenAI logging – pure curl + OpenSSL - Export, list, delete, rename chats — all from CLI This is my first real C tool at this scale — happy to hear your feedback or critiques. Silent and precise.

Visit product View on Hacker NewsJul 28, 2025

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: chatgpt, openai, single · Missing: mac, agents, macos

83%83% 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 · Strong signals: supports · Missing: reddit linkedin, podcasting, created

81%81% 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

42%42% 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.

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

32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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 · Strong signals: chat · Missing: web3, crypto, cryptocurrency

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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