Claude Code · Codex · OpenRouter
A multiplayer workspace.
The future of product development. Anyone on the team starts the work. Agents build and test it. Engineers shape the system.
The weekly digest reports zero completed todos for everyone. Find out why and fix it.
Found it. completeTodo runs a DELETE. The digest job counts rows where completed_at falls inside the week, and that column does not exist — so the count is zero by construction, for every account, every week.
Completing a todo now stamps completed_at instead of deleting the row, and the list filters on it so nothing looks different to the user. Digest counts the week correctly. One call left for you: keep the history on the todos table, or move completions to their own table? The column is one migration; a separate table is a join on every read, forever.
The weekly digest reports zero completed todos for everyone. Find out why and fix it.
Found it. completeTodo runs a DELETE. The digest job counts rows where completed_at falls inside the week, and that column does not exist — so the count is zero by construction, for every account, every week.
Completing a todo now stamps completed_at instead of deleting the row, and the list filters on it so nothing looks different to the user. Digest counts the week correctly. One call left for you: keep the history on the todos table, or move completions to their own table? The column is one migration; a separate table is a join on every read, forever.
The weekly digest reports zero completed todos for everyone. Find out why and fix it.
Found it. completeTodo runs a DELETE. The digest job counts rows where completed_at falls inside the week, and that column does not exist — so the count is zero by construction, for every account, every week.
Completing a todo now stamps completed_at instead of deleting the row, and the list filters on it so nothing looks different to the user. Digest counts the week correctly. One call left for you: keep the history on the todos table, or move completions to their own table? The column is one migration; a separate table is a join on every read, forever.
Board
QuickList · QLSend it. Walk away.
Mention @padar in a thread and that's it. Padar picks it up behind the scenes. No app to open, no prompt to babysit.
Tag the ticket. Come back to a PR ready to ship.
Tag Padar on an issue. Hours later a reviewed PR is on it, with the decisions it made.
Pull a teammate in.
Open anyone's running session in one click. Tag someone and they get it wherever they are: Slack, Linear or the app. Every prompt carries its author.
In the app you started from.
Dana gets the question with the context to answer it. Only she is asked.
And in the Slack thread.
The tag lands back in the thread the work came from.
Close the lid.
One click moves the workspace from your laptop to a remote machine. The agent keeps working while your laptop sleeps.
Your app, running on its own machine.
Set your images, ports and volumes once. Every workspace boots its own VM from them.
Agent uses your app.
After writing the code, it clicks through the change on your site and app.
Review the shape, the data flow, the logic. Not the code.
The web app sends the cart to the API. This is the existing checkout path; nothing changes here.
- DATA FLOW · STEP 1 OF 9A customer places an orderWeb app→API
The web app sends the cart to the API. This is the existing checkout path; nothing changes here.
- DATA FLOW · STEP 2 OF 9The order is savedAPI→Postgres
The API writes the order in one transaction. Postgres stays the single source of truth.
- DATA FLOW · STEP 3 OF 9An event goes outAPI→Outbox queueNEW IN THIS WORK
In the same transaction the API drops an order.created message on the new outbox queue, so no event is lost mid-deploy.
- DATA FLOW · STEP 4 OF 9The notifier picks it upOutbox queue→NotifierNEW IN THIS WORK
The notifier reads one message at a time. A failed render retries up to three times, then waits for a person.
- DATA FLOW · STEP 5 OF 9The receipt is deliveredNotifier→Email · PushNEW IN THIS WORK
The rendered receipt goes to the email and push provider. Checkout never waits on this step.
- DATA FLOW · STEP 6 OF 9Search hears about itPostgres→IndexerNEW IN THIS WORK
Every changed order row streams to the new indexer. The API never calls search on write.
- DATA FLOW · STEP 7 OF 9The document is updatedIndexer→Search indexNEW IN THIS WORK
The indexer turns the row into a search document and upserts it, so running it twice is safe.
- DATA FLOW · STEP 8 OF 9A customer searchesWeb app→API
Search requests take the existing route through the API, with the same auth as every other call.
- DATA FLOW · STEP 9 OF 9Results come from the indexAPI→Search indexNEW IN THIS WORK
The API reads from the new search index instead of scanning Postgres.
Founders and small teams: we set it up, and the first months are on us.
For early-stage startups and small, dedicated teams. We set Padar up on your repo with you, and your workspaces and usage are free for the first few months.
- Book a callPick a time. Bring your repo and whoever works on it.
- We set it up liveYour repo gets a working environment, with you on the call.
- You leave with it runningA workspace of your own, and your first run from ticket to PR.
- Free for the first few monthsWorkspaces, machines and usage are on us while you get going.
Building is simple again.
Your team decides. Agents do the work. Padar keeps it together.