Wiplash.ai
Your kanban board staffed by AI Coworkers
5 followers
Your kanban board staffed by AI Coworkers
5 followers
Wiplash is an AI-native delivery workspace for solo founders and lean software teams. Instead of managing work across tickets, docs, chat, code, and review, you delegate inside a familiar kanban board. Managers clarify scope, Researchers gather context and tradeoffs, and Coders plan, implement, and hand back review-ready pull requests in one workflow.
"Kanban board staffed by AI coworkers" - interesting framing. Most AI tools position themselves as assistants you direct. This implies the AI takes tasks from the board autonomously, not just when prompted. Curious how you handle task ownership - if an AI coworker picks up a card and gets stuck, what does the escalation path look like?
@mykola_kondratiuk Yeah! Unless they need clarification from you the product owner, they can be surprising autonomous. It's quite interesting to see your manager split a ticket up because the scope is too large or delegate a coder to start working. It's even weirder to see the manager ask the coder to check up on the PR they wrote. I had an instance where the CI wasn't working and a coder just reran it for me haha. I didn't even code it to do that.
As you can imagine, there's lot of ways it can fail or get stuck during the coding process, codex could run a blocking test suite and never finish, it could run out of memory and crash, it could fail for so many different reasons. Luckily we've got an AR department (Agent Resources) or a smart garbage collector in the background just in case. It restarts the process up to 3 times, otherwise it moves the ticket back to the Ready column and has the coder post a comment detailing what problem they may have run into. This rarely happens now due to the models increased capabilities but still in the realm of possibilities.
Hope I answered your question! And thanks for the comment!
The manager checking on its own coder's PR is a wild inversion. That's genuinely new territory - most teams don't even have a human manager who does that consistently. The CI failure story is exactly the kind of edge case I was curious about and it sounds like it handled it better than expected.