Beyond MMLU: The Shift to "Tool Correctness" Metrics
Why standard LLM benchmarks fail for agents, and how to measure real tool usage in production.
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From Silicon to Strategy. The latest thinking from the frontlines of building AI.

A hands-on tutorial using Google ADK and TypeScript to score agent workflows with custom eval rubrics.
Read Full ArticleWhy standard LLM benchmarks fail for agents, and how to measure real tool usage in production.
Fixed dashboards are the legacy interfaces of 2024. Your users are no longer satisfied looking at pre-canned charts; they expect the interface itself to adapt to the context of their query.
Deep dive into the agency as an r&d saas incubator.
Comparing raw memory management strategies for infinite-context enterprise agents.
Your beloved stateless Kubernetes architecture is fundamentally at war with the massive, stateful memory requirements of long-context LLM inference. We need a truce.
If your GPUs are idling at 40% utilization during inference, you are burning capital on memory bottlenecks, not computation.
When to return structured JSON cards vs streaming raw html to the frontend.
An organic, decentralized mesh of democratic agents reads brilliantly in an academic paper. But in enterprise production, democratic agents lead to infinite loops and massive API bills.
Deep dive into measuring tool use correctness & plan adherence.
You don't jump blindly from full 'Human-in-the-Loop' safety to completely autonomous API execution. You engineer a dial—and you turn it up one notch at a time.
How to use an "Adversary" agent to stress-test your autonomous systems before they reach production.
Deep dive into gitops for multi-agent workflows.
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