Articles
On agent optimization.
Deeper writing on what makes production LLM agents reliable — context economy, tool quality, verification design, and the patterns behind continuous improvement.
Context engineering
Context Bloat: Too Much Context Makes Agents Worse
Agent prompts grow every turn: old messages, raw tool results, documents fetched just in case. This buildup makes agents slower, costlier, and less accurate. Here is how to trim it without losing information the agent still needs.
Niyaz Puzhikkunnath· July 24, 2026AI observability
From Traces to Decisions: AI Observability Data Pipeline
Instrumentation makes agent behavior visible; data engineering makes it understandable at scale.
Faiz Vadakkumpadath· July 15, 2026Agent evaluation
How to Evaluate AI Agents in Production: A Practical Framework
In one public benchmark we analyzed, 22% of runs confidently told the customer the job was done without ever calling the real API. A guide to evaluating agents beyond the pass rate.
Niyaz Puzhikkunnath· July 14, 2026Article
Agent Optimization vs. Observability: Why Watching Isn't Fixing
Your dashboard saw the bad run and did nothing. The gap isn't between having data and not — it's between seeing what happened and knowing what to change.
Macy Mody· June 17, 2026