Distributed systems

AI in GTM at Notion — Flora Liu

AI in GTM at Notion — Flora Liu

Flora Liu from Notion's GTM engineering team discusses transforming a fragmented Go-to-Market system into a unified, agent-driven platform. She details how Notion tackles challenges like dispersed customer data and unstructured insights by building a four-layered architecture (Know, Decide, Act, Learn) where humans and AI agents operate on the same substrate, leveraging Snowflake, DynamoDB, and Notion itself to create durable, self-improving workflows and boost sales and marketing effectiveness.

Stateless, Yet Durable: MCP Tasks v2

Stateless, Yet Durable: MCP Tasks v2

Cornelia Davis explores the evolution of MCP Tasks, detailing the transition from v1 to v2. She highlights how v2's stateless protocol design supports durable, long-running agentic workflows by shifting durability responsibilities to the client and simplifying elicitation. The presentation includes a demo of a purchase order process and discusses future scalability enhancements through a notification-based approach.

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

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.

Taking Reinforcement Learning Cross Datacenter — Nan Jiang, Modal

Taking Reinforcement Learning Cross Datacenter — Nan Jiang, Modal

Nan Jiang introduces "Adam absorption" to revolutionize RL model synchronization. By exploiting finite precision serving and small Adam steps, less than 1% of served model weights actually change, allowing for 500MB patches instead of 500GB checkpoints. This enables a distributed "bulletin board" architecture, decoupling trainers from global rollout fleets and unlocking elastic, cross-region GPU capacity for RL.

The New Primitives: Building AI Native Software — Kwindla Kramer, Daily

The New Primitives: Building AI Native Software — Kwindla Kramer, Daily

Kwindla Hultman Kramer argues that current AI agents are akin to 1995 web pages – a foundational primitive, not the ultimate destination. Drawing a historical parallel, he predicts the emergence of "AI native software" that will build upon and surpass agents, much like web applications evolved from simple web pages. He illustrates this through computing history, highlighting transformative shifts like VisiCalc's impact on accounting and the vision of Apple's Knowledge Navigator, and concludes by showcasing a game, Gradient Bang, that demonstrates the core primitives of this future AI native software.

MCP Tasks (async): Why Aren't Any Agents Supporting Them? — Cornelia Davis, Temporal

MCP Tasks (async): Why Aren't Any Agents Supporting Them? — Cornelia Davis, Temporal

Cornelia Davis explains why the MCP tasks specification, designed for durable, long-running, and interactive operations, hasn't seen widespread adoption. She details V1's architectural flaws, particularly concerning scalability and stateful human-in-the-loop interactions, and introduces V2's shift to a stateless core, client-initiated updates, and a clearer path for client-side durability, while outlining future work on scaling and adoption.