Everyone on your team is using AI. Cursor, Copilot, Claude, ChatGPT. Individually, they work really well.
But here's the thing. Every AI session is a solo conversation. Your teammate asked Claude about the error handling. You asked GPT to scaffold the API. PM used ChatGPT for the requirements. Three separate contexts. Nobody sees each other's work.
PR review comes. It doesn't match what was discussed. "Wait, when did we decide that?" Rework starts.
The problem isn't AI itself. It's that there's no team layer on top of it.
Why I started building this
I'm a product designer, been working in enterprise for over 10 years at places like Morningstar and JLL. I saw this pattern way before AI tools existed. Decisions live in Slack threads, Notion docs, someone's head. AI just made the gap worse because now everyone moves faster, but in different directions.
I wanted to fix what happens between "we agreed on this" and "the code actually ships."
What Scindo does
It's a workspace where your team discusses, plans, and ships with AI agents in the same thread.
- Chat → Agent and team discuss together. Edge cases come up in the conversation, not in PR comments later.
- Plan → Agent drafts a plan from what was discussed. Team reviews it.
- Build → Developer opens their editor with the plan loaded.
- Ship → Agent opens the PR. Reviewer sees the plan and the code diff together.
There are different agent roles, Engineer, QA, Security, Designer, Product. Connects to GitHub, Jira, Notion, Linear, Figma. Works in VS Code and CLI too.
Pricing is per-workspace, not per-seat. Because the whole point is getting the whole team in.
Where we are
Three weeks since launch. Small group of early users. Free tier is 50 AI responses/month, 1 workspace, up to 3 members. Enough to try it on a real feature.
Curious how other small teams handle this. How do you go from "we agreed on this" to "the code matches what we agreed on"?
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