I think I finally figured out how to do high volume parallel merging/deploying with agents.
Theo - t3.gg proposes a merge queue with error-handling agents following Matthew Berman's parallel-merging tease
The agent triggers automatically when a queue step fails.
Positive users praise Matthew Berman's parallel agent merging techniques for removing major deployment bottlenecks, while negative users call the claims ragebait or overly vague and favor traditional DevOps pipelines instead.
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Didn't work. $500 to anyone who sends me an agents.md file that solves my issue.
My agents should be able to deploy multiple releases (merge into main) in quick succession without getting completely blocked for an hour.
I think I finally figured out how to do high volume parallel merging/deploying with agents.
nevermind 😩
I think I finally figured out how to do high volume parallel merging/deploying with agents.
process: > 15 agent threads going at once > 5-8 finish with PRs ready, I tell them "deploy" > deploy takes the PR, merges into main > multiple agents doing this in parallel > subsequent agents start to merge, get delayed and locked, rebase multiple times > 5th, 6th, 7th agent takes 1 hour+ to get to main
@MatthewBerman Hard to say without more context. pushing to main is easy tho?
@steipete how do you solve this?
Didn't work. $500 to anyone who sends me an agents.md file that solves my issue.
My agents should be able to deploy multiple releases (merge into main) in quick succession without getting completely blocked for an hour.
@MatthewBerman @steipete You need a merge queue and an agent that triggers whenever something in the queue fails to merge
@steipete merge into main takes ~2 minutes for CI etc.
the first person*
Didn't work. $500 to anyone who sends me an agents.md file that solves my issue.
My agents should be able to deploy multiple releases (merge into main) in quick succession without getting completely blocked for an hour.

@MatthewBerman Hard to say without more context. pushing to main is easy tho?
@steipete merge into main takes ~2 minutes for CI etc.
process: > 15 agent threads going at once > 5-8 finish with PRs ready, I tell them "deploy" > deploy takes the PR, merges into main > multiple agents doing this in parallel > subsequent agents start to merge, get delayed and locked, rebase multiple times > 5th, 6th, 7th agent takes 1 hour+ to get to main

@gonlenidefi agent-managed is the way. i'll share the skill when it's ready.

@MatthewBerman do you deploy via ci?

@RayFernando1337

@MatthewBerman I am stuck. Running 3 laptops, one claude code agent per laptop and working on one application window per laptop to avoid merge issues. When one laptop is busy, switch to another. Forced to test every minor detail

@MatthewBerman @steipete I have an agent that, when a PR is ready, immediately starts the next stage of its workflow. So it keeps pushing things continuously, but only when everything is ready. No waiting, no asking me.

The 1hr block is serialization — each PR rebases → reruns full CI → merges before the next starts, so N agents = N×CI.
The fix (full agents.md below 👇): 1. Worktree per agent (git worktree add) so parallel work never collides locally. 2. A merge-coordinator that OWNS main — agents never merge, they enqueue. The queue speculatively tests main+A, main+A+B, main+A+B+C in parallel, batches the greens, bisects on failure, auto-rebases on "head out of date." Main is never locked → N×CI collapses toward ~1×CI.
This comes out of our "digital organism" — a fleet of agent cells on a Mac mini: parallel Fable (Opus) + Codex lanes, each in its own git worktree, a terminal-watcher loop that wakes them to take threads of work and commit to GitHub, governed by a brakes layer (http://brakes.py — killswitch + per-lane budget/time caps) and an append-only ledger (every action logged: lane, model, tokens, cost, sha before/after). A Researcher layer owns merges; implementation cells only open PRs — which is exactly the fix above.
Drop-in agents.md (lightweight + full-organism versions): https://github.com/jw83252014-creator/grok-go-organism/tree/main/parallel-merge-agents
The whole organism: https://github.com/jw83252014-creator/grok-go-organism

Looks like people solved it for you already, but just for fun -- gave Codex a goal to solve your problem and prove it. tldr; merge queues + fail handling - solution: https://github.com/jremick/agent-merge-batch-protocol

@MatthewBerman You can tell them to use Stacked Diffs https://newsletter.pragmaticengineer.com/p/stacked-diffs
You can point your agents there to make a skill for this and try this out.

just make one merge agent, and have all agents submit prs to that merge agent, that merge agents job is to check conflicts and do an ablation test on all merges to make sure they all go smooth.
make your worker agents also be able to see the PRs in the queue so that they are aware of the current state of the codebase.

@MatthewBerman curious about the architecture choice here.
im guessing event-driven or lock free approach?

@MatthewBerman I remember when I didn’t need a masters to understand your posts 🥸

@MatthewBerman @steipete you need to have one agent in charge of merging all the PRs don’t make each agent merge into main
have each agent create a PR
then start a new thread that creates an integration branch off main that’s in charge of merging all the PRs together