7-9 October, 2026 Prague, Czechia View More Details & Registration Important Note:Timing of sessions and room locations are subject to change.
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Development teams are seeing a rapid increase in code contributions, many of them from AI tools and pair-programming copilots. As AI-generated code increases, human reviewers can quickly get overwhelmed.
The instinct to throw "an AI reviewer" at the problem mostly doesn't work. A single agent produces shallow comments, misses context, and either over-flags or under-flags depending on how it's prompted.
This talk presents a pattern that works better, built and demonstrated from scratch: three specialized reviewing agents in parallel, followed by a developer agent that applies the fixes. One reviewer focuses on architecture, one on security, one on test coverage. When all three finish, a fourth agent rewrites the code to address each issue and opens a new PR for human sign-off.
The architecture is adaptable: teams with data sovereignty requirements can swap the hosted model for a self-hosted open-weight alternative (Llama 3, Mistral) served via vLLM or Ollama.
Attendees leave with a concrete, working pattern they can adapt to their own projects, and a clearer picture of where AI can genuinely reduce review bottlenecks.
