PromptQL
Curating context is a second job nobody wants. PromptQL is the team brain that organizes itself. Work with your team in multiplayer AI threads, and PromptQL turns the context you generate into suggested edits to your wiki - interconnected pages that span skills, knowledge, and the semantic layer. Yo
PromptQL launched on July 23, 2026 with 411 votes, #45 of 24,623 launches that month and more than 99% of that year's launches.
In plain words
PromptQL is a team collaboration platform that combines shared AI chat with integrations for databases, SaaS apps, and coding tools. It allows teams to work together in threaded conversations with Claude or ChatGPT, tagging teammates to review and refine answers while preserving reasoning. The platform connects various data sources and automatically captures institutional knowledge, suggesting updates to keep team context current. Permissions and scopes ensure appropriate information access across team members.
written from the facts on this page · September 2026
From the sources
Stop splitting team knowledge between Slack and everyone's private AI chats. PromptQL is multiplayer AI for teams: think Claude or ChatGPT in shared threads. Tag teammates to review, correct, and refine answers without losing the reasoning. Connect databases, SaaS apps, coding agents, and events. PromptQL captures tribal knowledge and suggests shared-brain updates so context compounds. Scopes and multi-user permissions keep the right context accessible to the right people.
Curating context is a second job nobody wants. PromptQL is the team brain that organizes itself. Work with your team in multiplayer AI threads, and PromptQL turns the context you generate into suggested edits to your wiki - interconnected pages that span skills, knowledge, and the semantic layer. You just accept.
So PromptQL does it. It's a multiplayer AI agent — think Claude or ChatGPT, but with shared threads and a shared brain. Point it at the context you already have. Correct it once and it sticks — for everyone. PromptQL learns by being corrected. It starts from the context already scattered across Slack, docs, tickets, CRM, and warehouse tables, and on every task it shows its work — the sources it pulled, the assumptions it made. Correct it once, or pull in the teammate who knows. That becomes shared context: a reusable skill (“exclude test accounts from revenue”), team knowledge, or a semantic-model change. Nobody wants to update the wiki. Everyone wants their work done. PromptQL turns that…from promptql.io
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