Developer builds prompt optimization tool using 500M tokens, seeks community input

A developer has spent approximately 500 million tokens and significant effort building a prompt optimization tool. They experimented with various large language models, including General Language Model, DeepSeek, GPT, and Claude, but found their built-in agent features to be inadequate for refining the optimization pipeline. The developer is now seeking community feedback on how to fundamentally improve the core optimization loop and identify valuable features beyond the basics for such a tool. AI

IMPACT This project highlights the ongoing challenges and community-driven innovation in developing effective prompt engineering tools.

RANK_REASON Developer's personal project building a tool, not a company release.

Read on dev.to — LLM tag →

• Claude
• DeepSeek
• General Language Model
• generative pre-trained transformer

• product
• other

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