Aug 22, 2026

Give the Agent a Budget, Not a Token — Sachin Malhotra, Anthropic

Sachin Malhotra's talk outlines a critical framework for safely deploying autonomous agents in production, moving beyond simple token-based access. He introduces 'asymmetric verbs,' refilling 'rate limits,' 'trip wires' for aggregate monitoring, and the 'undo test' as a lens. A central tenet is that infrastructure (via a proxy) must stamp an agent's identity, preventing agents from circumventing controls and ensuring accountability, thus providing a "budget" instead of an unbounded "token."

Aug 19, 2026

Healthcare’s Agent Bytecode: X12 as the Harness for AI Agents — Vasant Kearney, Onlay

Vasant Kearney presents a nuanced perspective on implementing AI in healthcare, particularly in insurance. He highlights that while AI is evolving rapidly, real-world application requires understanding that solving isolated problems doesn't equate to complex solutions. His core argument is the utility of X12 as a 'harness' for agentic AI, providing a structured, confining framework for LLMs in healthcare. This approach acknowledges that X12 defines the contract between providers and payers, and even phone calls can be seen as X12 transactions. However, he cautions that X12, or any payer data, isn't ground truth due to disparate system origins, necessitating an internal 'semi-correct' representation. Kearney advocates for a balanced "AI pilled and AI skeptical" stance, embracing AI's potential while remaining cautious about its inherent limitations, cost, and the necessity for robust system design and evaluation.

Aug 17, 2026

MCP Goes Stateless | ​John Dellenbaugh & Pankaj Kumar | MCP Release Party - Seattle

This session details the transformation of the MCP protocol to a stateless design, addressing previous scaling challenges by externalizing session state to a database and eliminating the need for sticky sessions and complex infrastructure. The presentation includes a live demo comparing stateful and stateless architectures, highlighting benefits in scalability and simplified deployment. It also covers considerations for security and data resiliency within this new paradigm.

Jul 29, 2026

Your Agent Didn't Fail. Your Harness Did. — Vinoth Govindarajan, OpenAI

Vinoth Govindarajan's talk addresses critical 'harness failures' in AI agents, arguing these, rather than model errors, are the root cause of most production incidents. He introduces the core contract: 'A model proposes, the harness commits, and a receipt proves it,' and outlines five key boundaries (state ownership, ordering, deadlines, authority, user-visible proof) that lead to failures like silent success and incomplete reality. The talk culminates in a practical 'run receipt audit' with five questions to diagnose and ensure reliable agent behavior.

Jul 11, 2026

From Writing Code to Designing Systems: How the Developer Role is Changing — Chris Noring, Microsoft

This talk introduces a paradigm shift in software development, moving developers from pure code producers to system designers and agent orchestrators. It details a new workflow leveraging GitHub Copilot CLI, custom Copilot agents, and explicit guardrails like `agents.md` and skills. The focus is on how to decompose complex problems, delegate implementation to AI, and encode architectural standards and constraints directly, enabling higher consistency, quality, and accelerated delivery through a "human-in-the-loop" delegation model.

Jul 10, 2026

Should AI Engineers Still Read Code in 2026? The Z/L Continuum — Alex Volkov, ThursdAI

Alex Volkov introduces the "Z/L Continuum," a framework for navigating the tension between rapid AI-generated code production and the critical need for human review. He argues that the key lies in understanding that the continuum applies to tasks, not individuals, and presents a pragmatic routing table for verifying changes based on their criticality, highlighting the shift towards engineering systems that build and verify code, rather than meticulously inspecting every line. The talk also touches on emerging capabilities like Fable and "loops" and the importance of flexibility and human judgment in the evolving AI engineering landscape.