Multi-Agent Teams in AI-Assisted Development: A Glimpse Into the Future of Programming
FORMAT: WorkshopLEVEL: All levelsLANGUAGE: English
Programming has gone through a quiet but radical transformation in the last few years. We went from writing every line, to autocomplete, to AI proposing whole functions, to reviewing and steering AI-generated code. What comes next? Multi-agent systems, where you have a team of specialized agents working in parallel. This workshop is a hands-on, honest look at what that shift means today, and what it points to tomorrow.
We'll start by mapping the current landscape together: what tools exist, how they approach multi-agent orchestration, what each one gets right, and where the real tradeoffs are. The goal isn't to pick a winner — it's to build a shared vocabulary and a realistic picture of the state of the art.
From there, we'll move into live demos. Rather than polished showcases, these are honest explorations: what these systems can actually do today, where they break down, and what those breakdowns tell us about the deeper challenges in multi-agent coordination. Token costs, context limits, agent miscommunication, and the question of how much to trust your agents — these are real problems worth examining together.
The talk closes with the bigger question: what does all of this mean for us as developers? What skills are becoming more important, which ones are becoming less so, and how do we stay relevant as the abstractions keep deepening? Not predictions, but a grounded reflection based on what's already visible in these early systems. The practical question isn’t whether this future is coming; it’s how to get ahead of it.
Audience takeaways:
A clear mental model for what multi-agent coding actually is (vs. single-agent tools and vs. orchestration frameworks)
A working setup guide for multi agent works effectively
Practical demos actually showcasing what to do with these tools
A grounded perspective on what these experimental systems tell us about the next years of AI-assisted development and programming
Suitable for: Python developers with some familiarity with AI tooling. No deep ML background required — this is a practical developer talk, not a research talk.
