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I've always thought there should be a way to more efficiently provide prompt for LLMs, especially when the latest models consume a lot of them for complex work. Hopefully this will eventually result in less usage rate and higher limits.
Product Hunt • ProductHunt • Use case: Efficiently providing prompts for LLMs to manage token consumption in complex work.
If the compression holds under real production loads, this could become default infra in most LLM stacks.
Product Hunt • ProductHunt • Use case: Evaluating Edgee for potential integration as a standard infrastructure component to compress/optimize LLM tokens.
For developers using AI coding agents (Claude Code, Cursor, etc.) that make heavy API calls during development, does Edgee support integration at the agent workflow level? Specifically, can we route AI agent requests through Edgee to compress tool call contexts and reduce token consumption during iterative coding sessions?
Product Hunt • ProductHunt • Use case: Exploring integration for AI coding agents (like Claude Code) to compress tool call contexts and reduce token usage during development.
this is exactly the kind of infra that makes shipping AI features viable without stressing about the bill
Product Hunt • ProductHunt • Use case: Managing and reducing AI API costs across multiple projects to make shipping AI features financially viable.
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