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Debug and profile agentic app experiences with Instruments
Explore the enhanced FoundationModels instrument in Xcode to inspect behavior and optimize the performance of agentic flows. Learn how to inspect prompts, analyze latency, and trace control flow in advanced use cases that leverage multiple LanguageModelSessions and profiles.
Chapters
- 0:00 - Introduction
- 1:57 - LLM app development mindset
- 3:59 - Inspect and diagnose an agentic experience
- 5:02 - Recording a trace with Instruments
- 6:04 - Navigating the Instruments UI
- 12:07 - Performance metrics
- 13:04 - Next steps
Resources
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- 0:00 - Introduction
Overview of how the Foundation Models Instruments template helps debug and profile agentic app experiences built with the Foundation Models framework, including Dynamic Instructions and tool call loops.
- 1:57 - LLM app development mindset
The three challenges unique to LLM app development: probabilistic output (non-deterministic responses that break standard unit testing), model-to-model communication (coordinating data flow across multiple models), and observability (knowing where things went wrong in a multi-model pipeline).
- 3:59 - Inspect and diagnose an agentic experience
Introduction to the craft companion demo app — a journaling app with an interactive brainstorming feature that uses two sets of Dynamic Instructions: one for idea generation and one for tutorial creation, both backed by the server model on Private Cloud Compute.
- 5:02 - Recording a trace with Instruments
How to start profiling with the Foundation Models template in Instruments — selecting the template, recording a session, and an important note about sensitive prompt data in trace files.
- 6:04 - Navigating the Instruments UI
A walkthrough of the Foundation Models instrument layout: tracks and lanes on the timeline (including the instructions lane and model inference lane with yellow/orange bars), the detail view, and the inspector — and how to use the tree view to inspect sessions, requests, inferences, and tool calls.
- 12:07 - Performance metrics
How to measure and optimize LLM experience performance using three key metrics: time-to-first-token (reduce by shortening prompts), tokens-per-second (benchmark across configurations), and total latency (reduce perceived wait with streaming).
- 13:04 - Next steps
Summary of what was covered, requirements to get started (Xcode 27 and latest OS), and pointers to related sessions on the Evaluations Framework and Agentic App Experiences.