LLMOps in Action: Using Opik Traces, Evals, and Prompt Optimization to Improve Agent Performance
dl_weekly · x · 2026-08-16
Part 3 of The Observable Job Agent series covers LLMOps in practice: using Opik traces, evals, prompt optimization, and Ollie to diagnose failures and improve agent performance.
More from coding & agent
- Using Grok to generate detailed coding prompts for 3D scenes — techartist_ · 2026-08-16
- Generating reference images for code implementation, not pixel copying — techartist_ · 2026-08-16
- Cross-Vendor Agent Teams: Isolating Reviewer Context Improves Code Review — rehanalliii · 2026-08-16
- What's Hardest to Test in LLM Apps? Developers Discuss Pitfalls Beyond the Model — Financial_Ad_7297 · 2026-08-16
- AI coding requires stronger processes; MCP Server introduces trust bootstrap — RealSharpNinja · 2026-08-16
- Building an AI agent that diagnoses problems before solving them — the_underdog_9133 · 2026-08-16