IronBee

The Verification and Intelligence Layer for AI Coding Agents

[Serkan Özal @serkan_ozal]

Ever hit your AI coding agent's context limit and had no idea why?

We've all been there — your agent runs out of context or your bill creeps up, and all you can do is complain. The real problem? You can't see where your context and tokens are actually going.

So we built something new in IronBee: a real-time breakdown of an AI coding agent's active context — down to individual MCP servers, tools, skills, rules, and sub-agents. As far as we know, no other product does this at this granularity.

And it's harder than it looks. Just measuring each tool's tokens in isolation misses the real story:
- Tool definitions consume static context every turn, used or not.
- Tool results become chat history — re-sent to the LLM on every turn.
- Each turn, all this static + dynamic content travels to the API as accumulated history.

You can't optimize what you can't measure at this resolution. @ironbee_ai gives you that visibility — plus concrete optimization recommendations to run your agents more effectively and at lower cost.

Our background in observability and instrumentation is exactly what made this possible. Treating an AI agent's context as a system you can profile changes everything.

Tired of guessing where your tokens go? This one's for you. 👇

[IronBee @ironbee_ai]

Hello world ...