How we slashed an AI Agent's latency by 80% in 60 minutes
Building an AI agent is fun. Fixing its production latency when it's juggling live data, RAG, and text-to-speech? Not so fun. In the latest episode of the AI Agent Clinic, we sat down with developer Sami Maghnaoui to debug PlaybackIQ, a football / soccer agent he built to provide pre and post match analysis with text to voice, and minute-by-minute match insights with interactive UI. The app was awesome, but under heavy "match day" data loads, the wait times were killing the UX. Here’s how we fix
Building an AI agent is fun. Fixing its production latency when it's juggling live data, RAG, and text-to-speech? Not so fun.
In the latest episode of the AI Agent Clinic, we sat down with developer Sami Maghnaoui to debug PlaybackIQ, a football / soccer agent he built to provide pre and post match analysis with text to voice, and minute-by-minute match insights with interactive UI.
The app was awesome, but under heavy "match day" data loads, the wait times were killing the UX.
Here’s how we fixed it:
The Bottleneck: We implemented OpenTelemetry on the Agent Platform to trace exactly where the LLM calls and data retrieval were hanging up.
The Scale: We shifted the deployment to Cloud Run to properly handle concurrent traffic.
The Result: We managed to slash the agent's latency by 80%.
If you're dealing with sluggish LLM response times in your own apps and want to see what a production-grade fix looks like, we recorded the whole teardown and rebuild.
🎥 Watch the teardown here:
[https://youtu.be/G7olcqETSn8]
(Let me know in the comments what your go-to stack is for tracing LLM latency!)
