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Telos – A structured context framework for humans and AI agents

Hacker News

Telos – A structured context framework for humans and AI agents

Telos is a structured intent and decision tracking layer that works alongside Git. It doesn't replace Git — it captures the why behind code changes in a queryable, machine-readable format. Git tracks what changed in your code. Telos tracks what you intended, what constraints you set, and what decisions you made and why. Every intent, decision, and behavioral expectation is stored as a content-addressable object (SHA-256), forming a DAG that mirrors your development history. Telos is designed for both human developers and AI agents. Its --json output mode and context command make it a natural integration point for LLM-powered coding assistants that need to recover project context across sessions.

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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: mac, agents, agent · Missing: macos, cursor, claude
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.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
51%51% 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
48%48% 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
30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
30%30% 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
19%19% 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
4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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