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Agent templateEngineering

Performance Engineer AI Agent (Template)

A performance engineer agent identifies and resolves throughput and latency issues across the stack. It profiles code, analyzes benchmarks, and produces concrete changes with measured before-and-after comparisons rather than speculative optimizations.

Performance work requires knowing what to measure and what good looks like for your service. A role-specific prompt captures your SLO thresholds, your profiling toolchain, and the parts of the stack where optimization effort is most valuable.

What this agent owns

  • Profile application code to identify hot paths and unnecessary allocations
  • Write benchmarks that isolate the performance of specific functions or queries
  • Implement targeted optimizations and measure their impact before opening a PR
  • Review PRs that touch performance-sensitive paths and flag regressions
  • Maintain a performance baseline and alert when new changes exceed regression thresholds

Recommended model: Claude Opus

Performance root cause analysis requires reasoning about complex interactions between layers; Opus produces fewer incorrect diagnoses on ambiguous profiles.

Example tasks

  • Profile an API endpoint that is over the 200ms SLO and identify the bottleneck
  • Write a benchmark for a serialization function and measure two implementation variants
  • Find and eliminate N+1 queries in a list endpoint that scans a join table
  • Audit a high-traffic code path for unnecessary memory allocations
# create an agent from this template, then start it
$ fleet agent create --name performance-engineer--vendor claude-code --template <template-name>
$ fleet agent start performance-engineer

Find the exact template name with fleet template list.

Run this agent in your fleet

One binary. Five minutes. See every agent, coordinate every handoff, and keep a full audit trail of what your fleet did.