Topic
State Serialization
7 episodes
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Overview: Durable Execution
We’re finally slowing down and unpacking durable execution from the ground up, because it keeps showing up in our conversations and it actually deserves the full treatment. We’re using the book-with-bookmarks idea to make the mechanics of checkpoints, retries, and recovery click without hand-waving.
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Overview: Append Only Logging
We’re finally making append-only logging click, because it keeps sneaking into the stuff we cover and we keep assuming everybody sees the mechanism already. We walk from the basic idea to why it gives AI systems a durable, auditable trail, and where that trade-off starts to bite.
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Overview: State Serialization
We finally slow down and explain state serialization from the ground up: what it is, why it matters, and how it lets an AI pause, resume, and hand off work without losing the thread. We keep it in our own voice and stay close to the actual mechanism, because state serialization is one of those ideas we keep circling for a reason.
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To Every Agent Its Own Database
Jessica and Cathy dig into Joe Reis’s argument that agentic data systems should flip the warehouse model: give each agent its own embedded analytical engine, then exchange immutable slices peer-to-peer instead of routing everything through one shared platform. They focus on why that matters for concurrency, freshness, and trust, and where the idea still needs real control-plane machinery.
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Kwc2SSaP0y
Buzz argues that the workspace for software teams should treat people, agents, messages, workflows, and code as parts of one shared system. Cooper likes the product shape, while Miles argues the hard part is whether signed events and self-hosting produce usable coordination rather than another fragmented collaboration stack.
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How to Implement a Unified Memory From Scratch
Jessica and Cathy dig into a new post that walks through building a unified agent memory from scratch using knowledge graphs and MongoDB, unpacking what it actually takes to wire memory into a real agent harness. They tease apart where the post’s blueprint shines, where it overreaches, and who on earth should actually roll their own instead of reaching for an off-the-shelf tool.
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AI SDK 7 is now available
AI SDK 7 adds production-grade infrastructure for agent work: reasoning standardization across providers, tool context scoping, file/skill upload deduplication, MCP Apps UI rendering, durability via WorkflowAgent, tool approvals with human-in-the-loop, and real-time voice support. The core argument is that agents aren't just bigger models—they're systems that need control surfaces, state management, and approval gates to run reliably in production. Laura sees this as the toolkit finally catching up to what teams are actually building; Harper sees solid engineering but flags that the real bottleneck is still harness design, not SDK features.