---
title: "Two Roads to Durable Agents: Replay vs. Snapshot — Eric Allam, Trigger.dev"
url: https://daily.dev/posts/two-roads-to-durable-agents-replay-vs-snapshot-eric-allam-trigger-dev-2h2zopif0
source_url: https://www.youtube.com/watch?v=svCnShDvgQg
type: video:youtube
source: "AI Engineer"
published: 2026-05-10T20:01:24.615Z
updated: 2026-07-16T02:13:03.364Z
tags: ["ai-agents", "llm"]
reading_time: 16
upvotes: 0
comments: 0
language: en
---

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# Two Roads to Durable Agents: Replay vs. Snapshot — Eric Allam, Trigger.dev

**[AI Engineer](https://daily.dev/sources/aidotengineer)** · 16 min read · 0 upvotes · 0 comments

## Summary

Eric Allam (Trigger.dev co-founder) explores two approaches to making AI agents durable in production: the replay model (caching side effects as steps in a journal) and the snapshot/restore model. He argues that replay, which underpins 30 years of stateless backend infrastructure, breaks down for long-running agents because the journal grows unboundedly. Instead, durable agents need two things: a persistent append-only context log (all LLM messages and tool calls) and execution-layer snapshots. Trigger.dev evolved from CRIU-based process checkpointing to Firecracker microVMs, achieving sub-second snapshots and ~200ms restores, compressing 512MB VM state down to ~14MB. They are open-sourcing this as a Docker-like CLI tool called FCRun, capable of 15,000 VM starts per minute.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.youtube.com/watch?v=svCnShDvgQg>

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---

Tags: [#ai-agents](https://daily.dev/tags/ai-agents), [#llm](https://daily.dev/tags/llm)

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