C
Caveman
The token-efficient stack for agent-native development that cuts 65% of AI costs.
74k GitHub stars#1 on Hacker News65% fewer output tokensOpen source MITTrusted by 10,000,000+ professionals
Opportunity score
63/100
Strong developer traction and a clear cost-saving pitch, but monetization is unproven and competition is intense.
Founder verdict
MAYBE
Caveman has strong open-source traction and a compelling cost-saving story, but monetization and competitive defense are unproven.
What is Caveman?
Caveman is an AI infrastructure startup offering a layered 'efficiency operating stack' that compresses, caches, and routes LLM traffic to reduce token usage and cost. According to its website, the open-source skill claims 65% fewer output tokens while preserving code and errors byte-for-byte, and the project reports 74k GitHub stars and a #1 Hacker News position. The stack spans a free MIT skill, a free local proxy, a TypeScript Agent SDK, a managed Cloud gateway (waitlist), and on-prem Enterprise (in development). Revenue and growth are not publicly disclosed. The main thesis is that observability tools show AI spend, but Caveman actually applies optimizations and proves savings. This is a developer-led open-source motion aiming to convert free users into managed cloud and enterprise customers.
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The complete reverse-engineering — what to copy, what to avoid, and exactly what to build instead.
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- The real problem & why customers pay
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