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last write wins vs crdt conflict resolution field merge
Field-level merge for free, without a CRDT library
Modeling state as (table, row, column) cells instead of whole rows means concurrent edits to different fields both survive automatically, with no merge code.
This is one of the things Offline Sync Engine already handles. Let your app keep working with no internet, then merge the changes correctly when it reconnects.
Is this you?
A sync design built around whole-row last-write-wins treats any two concurrent edits to the same row as a conflict, even when they touch entirely different fields -- one device updates a status, another updates a note, both offline, and whole-row LWW picks one edit and silently discards the other, even though there was no actual disagreement about anything.
Why this one is easy to get wrong
"Sync a row, resolve conflicts by timestamp" is the mental model most conflict-resolution explanations start from, because it's simpler to reason about than a cell-level model -- reaching for per-field granularity (or a full CRDT library) requires recognizing up front that most real conflicts in CRUD-shaped apps are actually non-conflicts between different fields, which isn't obvious until you've already built the whole-row version and watched it discard changes it shouldn't have.
What you get instead
The pack's unit of state is a cell -- (table, rowId, col) -> (value, hlc) -- so concurrent edits to different columns of the same row simply both apply; no merge code exists for that case because it was never a conflict at the storage level. Only a genuine same-field conflict falls back to LWW on the HLC, which the pack states plainly is the right tradeoff for CRUD-shaped data and the wrong one for collaborative rich text, where a CRDT library like Yjs or Automerge is the correct tool instead.
Source: ARCHITECTURE.md 'Core model: a synced cell store' — checkable in the pack you receive
How you actually use this
You don’t install a library or wire up an SDK. Your own coding agent builds the code in your project, and you keep it — no runtime dependency on us.
Step 1
Download and unzip
You get a folder: the docs that tell an agent what to build, a starting skeleton, and the test suite that decides when it's done.
Step 2
Open it in Claude Code or Cursor
Point your coding agent at the folder. Nothing to install, no account with us, no API key.
Step 3
Paste one prompt
The pack contains the exact prompt. Paste it as your first message and leave it alone — it works through the build itself, choosing a cheaper or stronger model per task.
Step 4
Run ./verify.sh
One command. It prints a pass or fail for every check. Green means the build is done — the same script we ran to produce the receipt on this page.
Typical build: about 12 minutes of your agent working, mostly unattended. Then you integrate the working module into your app the way you would any code you’d written yourself.
Why you can believe this
2 of 3 runs passedWe ran this pack from an empty folder 3 times and published exactly what happened — every check, the model, the token cost, the wall time. Not a testimonial, and not our opinion: the same verify.sh you run yourself. Read the full receipt →