PromptQL

the correction/lock mechanism answer covers factual mistakes well, but what about genuine disagreement that isn't a mistake at all - two senior people with different but equally valid judgment calls on how something should work. does the shared thread surface that as visible tension (both views, both names attached) or does it end up flattening into whichever answer got approved first, making the other person's actual position invisible to everyone who reads it later?

how big does a company have to be to start feeling the value of @PromptQL ?? cc: @rajoshi_ghosh

The "shared-brain updates so context compounds" framing is different from other team AI tools. One thing I'd be curious about—when corrections and learning flow back into the context, how do you prevent authoritative corrections from overweighting domain expertise that was already in the system? Like, if someone corrects a nuance mid-thread, does it need peer review before it locks in, or is the cost of outdated shared context higher than the cost of wrong-but-quick updates?

What's a use case you think most people don't know PromptQL can support but is really helpful?

Congrats on the launch! I like the core bet: humans own context, agents do the work.But Slack is a muscle memory at this point. How do you see that playing out? Is full migration the goal, or is the real win that team context becomes queryable and agents act on it, and chat just happens to be where it lives? Let's say that my team’s stuff lives in Notion, Google Drive, Jira, and Slack. What does week one look like? Do we move in fully, or does PromptQL read from those tools while we ease over?

Been a user of PromptQL and it's an amazing re-invention of collaboration!

I think this is genuinely one of the best apps I've seen so far. or at least dreaming about this kind of apps for whilewhere everything is in one place, and you can actually work with other people, without having to share documents back and forth. You just share the chat, and their agents keep working on their own tasks. That's genuinely amazing.

Oh wow!! 🤩
This is the coolest AI tool! It’s actually helping unblock me now that I can work faster. And I don’t feel like I’m losing context. It tells me what is happening in other parts of the company in real time. And I’m not gonna break someone else’s flow by pinging them.

Amazing 😻

@rajoshi_ghosh

the scopes/permissions part is the sharp edge - if someone corrects an answer in a restricted-scope thread, does that correction ever bleed into the shared-brain for people outside that scope, or does it stay siloed to who saw the original thread?

This is neat. Does each thread have its own AI context or does it pull from the team's full history?

biggest strength here is the cross model switching. biggest risk is lock-in once the wiki gets deep.

interesting idea. what made you take on slack?

I work at PromptQL, so obviously biased, but here's how I actually use it day to day.Anyone who lives in Slack knows the FOMO: interesting discussions happening in ten channels at once, and you can't be everywhere. Curing that yourself normally means dedicated engineering time to build something and keep it running. Here it's just... the default. Whatever's interesting or relevant finds you, full context always at your fingertips. You just start a thread and ask PromptQL to find things that might be interesting (define THE interesting ofc) and it just silently works and keeps you updated.Works outside work too. I use it to trace how a news story actually unfolded instead of getting the echo-chamber version from my feed.But my favourite thing is how a product gets built now. A thread and the learning becomes the RFC itself. You, your teammates, stakeholders and the AI hash out everything in one place: UX, backend constraints, cost, the actual implementation. One thread, full lifecycle of a feature. I've had the pain firsthand of answering the same questions over and over, explaining why some decision was made months ago, digging through old threads to reconstruct context. Now the feature itself can be Q&A'ed with AI because it watched the whole thing happen. What's more pleasing to a feature builder than not fielding every how/why question, and only getting pulled in when it actually matters?Even the boring part of shipping (watching adoption, catching issues) gets easier. Hook up PostHog and Grafana and it quietly takes on the operator role. You just approve when needed.

What is nuts about working with PromptQL is how easy is to say:“Is this thing a problem? Show me data”“Right, what should we do to fix it”“Yeah that looks like a good fix, let’s iterate a bit and then deploy it”“Monitor the problem data every day and let’s check we fixed the problem”When “doing things” is cheap, making sure you’re not doing useless things is key, and that’s so easy for me now.

Building shared context instead of forcing everyone to constantly repeat the same information feels like the real unlock for AI at work Most AI tools make individuals faster but PromptQL makes the whole team smarter That is a much bigger shift Looking forward to seeing where this goesCongrats on the launch @rajoshi_ghosh