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The GeekNarrator · Yesterday · 1 hr 6 min

Agentic Performance Engineering ft. Perfloop

Performance is getting harder to ignore, and Tomás argues that AI is making the problem urgent in ways most teams are not ready for. He explains why AI-generated code, exploding system surface area, and rising infrastructure costs are creating a perfect storm, and why Perfloop exists to turn performance engineering into a rigorous, automated science.Tomás, the creator of Perfloop, breaks down how the product maps your codebase and telemetry into a living model of your system, then hunts for performance anti-patterns with a verification harness that puts every hypothesis through measured, repeatable experiments. Instead of relying on a freestyle coding agent, Perfloop uses structured discovery, deterministic checks, and adversarial verification to produce results you can actually trust.Chapters:00:00 The performance problem behind Perfloop00:39 Why performance work is a battle03:59 How AI agents raise the stakes08:55 Quality control at the scale of agentic development10:34 How Perfloop maps systems and finds opportunities14:32 Using telemetry to prioritize hot paths18:13 Perfloop’s open-source performance wins22:18 How Perfloop measures and verifies improvements25:11 Common performance patterns and bottlenecks28:47 The “apex hunt” for bigger architectural gains30:58 Initiatives and setting high-level performance goals35:21 Connecting code optimizations to customer impact39:59 Why independent verification matters44:36 Choosing the right AI models for each task49:45 What a harness does in Perfloop53:59 The possibility of pre-merge performance reviews57:24 How AI may change the role of performance engineers63:54 Why performance requires measurementImportant links:Patterns: https://app.perfloop.ai/t/oss/patternsPerfloop: https://app.perfloop.ai/t/oss/startFor memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinDon't forget to like, share, and subscribe for more insights!=============================================================================Like building stuff? Try out CodeCrafters and build amazing real world systems like Redis, Kafka, Sqlite. Use the link below to signup and get 40% off on paid subscription.https://app.codecrafters.io/join?via=geeknarrator=============================================================================Database internals series: https://youtu.be/yV_Zp0Mi3xsPopular playlists:Realtime streaming systems: https://www.youtube.com/playlist?list=PLL7QpTxsA4se-mAKKoVOs3VcaP71X_LA-Software Engineering: https://www.youtube.com/playlist?list=PLL7QpTxsA4sf6By03bot5BhKoMgxDUU17Distributed systems and databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4sfLDUnjBJXJGFhhz94jDd_dModern databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4scSeZAsCUXijtnfW5ARlrsNStay Curios! Keep Learning!

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Performance is getting harder to ignore, and Tomás argues that AI is making the problem urgent in ways most teams are not ready for. He explains why AI-generated code, exploding system surface area, and rising infrastructure costs are creating a perfect storm, and why Perfloop exists to turn performance engineering into a rigorous, automated science.Tomás, the creator of Perfloop, breaks down how the product maps your codebase and telemetry into a living model of your system, then hunts for performance anti-patterns with a verification harness that puts every hypothesis through measured, repeatable experiments. Instead of relying on a freestyle coding agent, Perfloop uses structured discovery, deterministic checks, and adversarial verification to produce results you can actually trust.Chapters:00:00 The performance problem behind Perfloop00:39 Why performance work is a battle03:59 How AI agents raise the stakes08:55 Quality control at the scale of agentic development10:34 How Perfloop maps systems and finds opportunities14:32 Using telemetry to prioritize hot paths18:13 Perfloop’s open-source performance wins22:18 How Perfloop measures and verifies improvements25:11 Common performance patterns and bottlenecks28:47 The “apex hunt” for bigger architectural gains30:58 Initiatives and setting high-level performance goals35:21 Connecting code optimizations to customer impact39:59 Why independent verification matters44:36 Choosing the right AI models for each task49:45 What a harness does in Perfloop53:59 The possibility of pre-merge performance reviews57:24 How AI may change the role of performance engineers63:54 Why performance requires measurementImportant links:Patterns: https://app.perfloop.ai/t/oss/patternsPerfloop: https://app.perfloop.ai/t/oss/startFor memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinDon't forget to like, share, and subscribe for more insights!=============================================================================Like building stuff? Try out CodeCrafters and build amazing real world systems like Redis, Kafka, Sqlite. Use the link below to signup and get 40% off on paid subscription.https://app.codecrafters.io/join?via=geeknarrator=============================================================================Database internals series: https://youtu.be/yV_Zp0Mi3xsPopular playlists:Realtime streaming systems: https://www.youtube.com/playlist?list=PLL7QpTxsA4se-mAKKoVOs3VcaP71X_LA-Software Engineering: https://www.youtube.com/playlist?list=PLL7QpTxsA4sf6By03bot5BhKoMgxDUU17Distributed systems and databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4sfLDUnjBJXJGFhhz94jDd_dModern databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4scSeZAsCUXijtnfW5ARlrsNStay Curios! Keep Learning!

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