# On "AI Brendans" or "Virtual Brendans"

DevFeed: [On "AI Brendans" or "Virtual Brendans"](<https://devfeed.tech/articles/on-ai-brendans-or-virtual-brendans-13608.md>)

Original publisher: [Read original article](<http://www.brendangregg.com/blog//2025-11-28/ai-virtual-brendans.html>)

Published: 2025-11-27T13:00:00Z

Content type: opinion

Language: en

Sources: [Brendan Gregg's Blog](<https://devfeed.tech/sources/brendan-gregg-s-blog.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [eBPF](<https://devfeed.tech/topics/ebpf.md>), [systems](<https://devfeed.tech/topics/systems.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-agents](<https://devfeed.tech/tags/ai-agents.md>), [blog](<https://devfeed.tech/tags/blog.md>), [ebpf](<https://devfeed.tech/tags/ebpf.md>), [opinions](<https://devfeed.tech/tags/opinions.md>), [performance](<https://devfeed.tech/tags/performance.md>)

## AI overview

Brendan Gregg discusses AI performance-engineering agents and "virtual Brendan" systems trained on his publications. He distinguishes agents that interpret flame graphs and eBPF metrics from systems intended to emulate his expertise, and argues that these tools have limited scope, may become outdated, and are difficult to price and evaluate.

## Source excerpt

There are now multiple AI performance engineering agents that use or are trained on my work. Some are helper agents that interpret flame graphs or eBPF metrics, sometimes privately called AI Brendan; others have trained on my work to create a virtual Brendan that claims it can tune everything just like the real thing. These virtual Brendans sound like my brain has been uploaded to the cloud by someone who is now selling it (yikes!). I've been told it's even "easy" to do this thanks to all my publications available to train on: >90 talks, >250 blog posts, >600 open source tools, and >3000 book pages. Are people allowed to sell you, virtually? And am I the first individual engineer to be AI'd? (There is a 30-year-old precedent for this, which I'll get to later.) This is an emerging subject, with lots of different people, objectives, and money involved. Note that this is a personal post about my opinions, not an official post by my employer, so I won't be discussing internal details about any particular project. I'm also not here to recommend you buy any in particular. Summary There are two types: AI agents. I've sometimes heard them called an AI Brendan because it does Brendan-like things: systems performance recommendations and interpretation of flame graphs and eBPF metrics. There are already several of these and this idea in general should be useful. Virtual Brendan can refer to something not just built on my work, but trained on my publications to create a virtual me. These would only automate about 15% of what I do as a performance engineer, and will go out of date if I'm not training it to follow industry changes. Pricing is hard, in-house is easier. With a typical pricing model of $20 per instance per month, customers may just use such an agent on one instance and then copy-and-paste any tuning changes to their entire fleet. There's no practical way to keep tuning changes secret, either. These projects are easier as internal in-house tools. Some claim a lot but