Oct 18, 2026

Stop Telling Agents How — Dan Barrett, Raymond Weitekamp & Jose Montes de Oca, OpenProse

The OpenProse team presents a declarative approach to multi-agent workflows, where developers and domain experts write contracts in plain markdown that any harness can compile and run. The talk covers event-driven jobs triggered by webhooks and pull requests, a grumpy-senior PR reviewer demo, a bank model-documentation workflow, composing contracts, pinning successful runs into deterministic workflows, and how the approach contrasts with DSPy.

Oct 16, 2026

Why AI Can Write Code But Can’t Keep It Running (Yet)

Grepr CEO Jad Naous talks with a16z's Martin Casado about how coding agents have changed a 10-person engineering team, with projects that once took six months now finishing in about ten days. They examine whether AI can reason about and troubleshoot production distributed systems, why operations is a harder problem than code generation, and where AI adoption is likely to go next.

Oct 06, 2026

Advanced Workshop: Mastering AI Observability — Doug Guthrie, Braintrust

Doug Guthrie showcases how Braintrust connects observability with AI agent improvement. Using a support agent, he demonstrates setting up tracing, establishing evaluation baselines, and publishing custom scorers. The workshop delves into Braintrust's Topics feature for discovering unknown failure modes, configuring online automations, and importing real-world traces. A key focus is on automating the improvement cycle: using the Loop assistant for SQL-based trace analysis, integrating coding agents with Braintrust CLI skills to propose code changes, add regressions, run evals, and generate pull requests, thereby closing the feedback loop from production to development.

Sep 29, 2026

AI Can Write the Proof. Who Checks It? — Leonardo de Moura

Leonardo de Moura discusses Lean's journey, from its strict "cathedral model" of core development to its current extensibility. He reveals insights from the Collatz exploit, showcasing AI's role in uncovering kernel vulnerabilities and the critical need for robust formal verification. The conversation highlights AI's transformative impact, from generating complex, optimized code (like the zlib proof) to its limitations in true creativity, emphasizing the enduring human responsibility in defining specifications, curating knowledge, and maintaining trust in an AI-assisted future for software and mathematics.

Sep 26, 2026

We Let Claude Code and Codex Race Human Researchers — Elie Bakouch, Prime Intellect

Elie Bakouch, a research engineer at Prime Intellect, reports on setting Claude Code and Codex loose on the community Optimizer Speedrun, a race to train a GPT-2-level model in the fewest steps. Both agents beat the human record, but they behaved very differently, and none of them invented a new optimizer. The talk closes with a proposed AlphaEvolve-style discovery loop and an argument for doing this research openly.

Sep 18, 2026

Total Recall: Agent Memory and Harness Engineering — Ignacio Martinez, Oracle

Ignacio Martinez's workshop delves into agent harness engineering, emphasizing that while LLMs are a 'frozen' reasoning core, the surrounding harness is where control and reliability are established. He outlines a seven-layer architecture for building robust agent harnesses, covering critical aspects like hybrid storage solutions, advanced memory engineering (including in-database embeddings and context card management), the semantic layer (Umwelt), agent loops, and context engineering. The session also explores continual learning through 'skill promotion' and addresses practical challenges like managing vast tool sets and optimizing model interactions.