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Agents are Robots Too: What Self-Driving Taught Me About Building Agents — Jesse Hu, Abundant

Agents are Robots Too: What Self-Driving Taught Me About Building Agents — Jesse Hu, Abundant

Drawing surprising parallels between AI agents and robotics, this talk argues that the agent development community is repeating a key mistake from the self-driving industry: underestimating the difficulty of action and over-focusing on reasoning. It covers essential robotics concepts like DAgger, MDPs, simulation, and the critical importance of a robust offline infrastructure, explaining why perfect reasoning doesn't guarantee successful execution in the real world.

Backlog.md: Terminal Kanban Board for Managing Tasks with AI Agents — Alex Gavrilescu, Funstage

Backlog.md: Terminal Kanban Board for Managing Tasks with AI Agents — Alex Gavrilescu, Funstage

Alex Gavrilescu introduces Backlog.md, a Git-based project management tool designed to structure AI-driven development. By breaking down features into Markdown tasks and using a multi-step review process, it helps prevent AI agents from running out of context or deviating from requirements, enabling a more predictable and efficient workflow.

Compilers in the Age of LLMs — Yusuf Olokoba, Muna

Compilers in the Age of LLMs — Yusuf Olokoba, Muna

Yusuf Olokoba, founder of Muna, details a compiler-based approach to transform Python AI functions into self-contained native binaries. This talk explores the technical pipeline, including custom AST-based tracing, type propagation, and the strategic use of LLMs for code generation, enabling a universal, OpenAI-style client for running any model on any platform.

The Unbearable Lightness of Agent Optimization — Alberto Romero, Jointly

The Unbearable Lightness of Agent Optimization — Alberto Romero, Jointly

This talk introduces Meta-ACE, a learned meta-optimization framework that dynamically orchestrates multiple strategies (context evolution, adaptive compute, hierarchical verification, and more) to maximize AI agent performance. The framework profiles each task to select an optimal strategy bundle, overcoming the single-dimension limitations of previous methods.

Vision: Zero Bugs — Johann Schleier-Smith, Temporal

Vision: Zero Bugs — Johann Schleier-Smith, Temporal

This talk explores the history of high-assurance software, from the near-perfect code of the NASA Space Shuttle to the Airbus A320. It argues that while these rigorous engineering and formal verification practices were once too expensive for mainstream use, the economic shift brought by AI and agentic coding can make aerospace-level reliability a practical reality for a wide range of applications, solving the key quality limitations of current AI-generated code.

Fully Connected 2025 kickoff: The rise (and the challenges) of the agentic era

Fully Connected 2025 kickoff: The rise (and the challenges) of the agentic era

Robin Bordoli of Weights & Biases explores AI's exponential growth, from past achievements to the current agentic landscape. He discusses the rise of reinforcement learning, the challenge of productionizing reliable agents, and highlights how foundational issues in AI development persist even as model capabilities soar.

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