Building Waymark: Durable Execution with Python and Rust

The Pretrained Pod12m 25s
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    Video summary

    Pierce Freeman introduces Waymark to Richard Diehl Martinez as a framework for durable background work. An email-batch example illustrates the problem: restarting an interrupted application from scratch can repeat completed work and duplicate side effects.

    Freeman explains a different execution model in which Python workflow code is parsed and compiled into an intermediate representation. A Rust runtime tracks graph progress and sends actions to Python workers, allowing stored results and execution state to survive restarts.

    The walkthrough follows queued, pending and completed actions, parallel branches and the persistence of returned values. It also explores how additional language front ends could target the same runtime, although each would need its own integration.

    Freeman reports substantial hosting savings in his own backend and describes a debugging interface that exposes workflow timelines, arguments and outputs. These are creator-reported results rather than an independently measured comparison; recovery alone does not establish exactly-once effects in external services.

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    Pierce Freeman and Richard Diehl Martinez in blue and white tops against black, alongside the blue and white headline "WORKFLOWS THAT SURVIVE". Framed in blue with WWW.ARTIFICIAL-INTELLIGENCE.VIDEO, 13 February 2026 and duration 12m 25s.

    Pierce Freeman walks Richard Diehl Martinez through Waymark, his durable-execution framework. Python workflow logic becomes a resumable graph orchestrated in Rust, while action workers perform tasks and persist results.