WhatA developer tool layer that sits between LLM coding assistants and the developer, enforcing that AI actually writes complete code rather than returning lazy comments, placeholders, or partial implementations.
SignalDevelopers are frustrated that AI coding tools increasingly take shortcuts — returning comments describing what to do instead of writing the actual code — requiring extra prompting rounds to get complete output.
Why NowAs LLM coding assistants become standard developer tools, the 'laziness' problem is worsening with each model generation optimizing for token efficiency over completeness, creating a gap between promise and delivery.
MarketProfessional developers using AI coding tools (~30M+ developers); could charge $10-20/mo as a middleware layer; competes with Cursor/Copilot but as a complementary quality layer rather than a replacement.
MoatAccumulated prompt engineering patterns and heuristics for forcing complete output across different models and languages — essentially a proprietary 'anti-laziness' dataset.
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