Supercharged profiling: Finding performance bugs with agents | DEM300
Key Takeaways
Using Visual Studio and AI-powered agents for profiling and debugging performance issues in distributed systems
Original Description
Modern performance problems are harder than ever to diagnose: distributed systems, async code, and massive data make traditional profiling insufficient. In this demo-driven session, watch how Visual Studio combines advanced diagnostics with AI-powered agents to surface bottlenecks, explain root causes, and guide fixes faster than ever. From CPU and memory issues to “it only fails in production” bugs, you’ll see how profiling evolves in an agentic world.
Seating for this session is first-come, first-served. Add it to your schedule to plan your day and arrive early to secure a spot.
To learn more, please check out these resources:
* https://aka.ms/build26/DEM300
𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀:
* Nik Karpinsky
𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻:
This is one of many sessions from the Microsoft Build 2026 event. View even more sessions on-demand and learn about Microsoft Build at https://build.microsoft.com
DEM300 | English (US) | Developer tools & frameworks
Demo | (400) Expert
#MSBuild
Chapters:
0:00 - Using Visual Studio Profiler to identify performance issues
00:02:30 - Creating benchmarks for accurate performance testing
00:04:55 - Cloning the repository and opening the solution in Visual Studio
00:06:19 - Explanation of in-memory CSV setup to isolate enumeration performance
00:09:01 - Review and refinement of Copilot-generated benchmark code
00:12:05 - Profiling trace captured and loaded into Visual Studio for analysis
00:15:01 - Benchmark re-run shows marginal improvement; discusses measuring impact and continued optimization
00:17:52 - Copilot as a Learning Tool for Software Engineers
00:18:33 - Transition to Presentation – Encouraging Reproduction of Performance Results
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Chapters (9)
Using Visual Studio Profiler to identify performance issues
2:30
Creating benchmarks for accurate performance testing
4:55
Cloning the repository and opening the solution in Visual Studio
6:19
Explanation of in-memory CSV setup to isolate enumeration performance
9:01
Review and refinement of Copilot-generated benchmark code
12:05
Profiling trace captured and loaded into Visual Studio for analysis
15:01
Benchmark re-run shows marginal improvement; discusses measuring impact and co
17:52
Copilot as a Learning Tool for Software Engineers
18:33
Transition to Presentation – Encouraging Reproduction of Performance Results
🎓
Tutor Explanation
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