Why we built AgentOS around a context lake
Count the AI tools your team uses. For most companies we talk to, it's more than they'd guess: ChatGPT for writing, Claude for thinking, Copilot because it came with Microsoft, a notetaker, a coding assistant. Each one is good at its job. None of them know your business, and none of them talk to each other.
That's the problem we kept running into at Devcore, and it's the reason AgentOS exists.
Every AI tool starts from zero
Every new chat starts with the same ritual. Who the client is. What we already tried. What we agreed last week. People paste the same background into tool after tool, and the tools still give three different answers depending on who asked and where.
It costs more than patience. Every time a tool re-reads background it should already know, someone pays for those tokens. And the knowledge the team builds up, the best person's prompts, the decisions in last Tuesday's meeting, stays stuck in one person's chat history.
A shared place for what the company knows
The fix isn't another AI tool. It's a shared place for the company's knowledge that every AI tool can draw from. The industry has a name for that idea: a context lake.
The name borrows from "data lake". A data lake holds raw data for analysts. A context lake holds knowledge organized for an AI to use directly: your clients, your docs, your decisions, kept current as the work happens. We didn't coin the term, and it's used in research and infrastructure circles too. We use it in the business sense: one shared place for a company's knowledge, so every AI tool your team uses works from the same picture.
What that looks like in AgentOS
In AgentOS you connect the places work already happens, like email, Slack, your files and your CRM, once. AgentOS keeps that knowledge organized and current. Then ChatGPT, Claude, Cursor and your own bots connect to it and answer from the same company knowledge. You decide what each tool can see and change, and anything that goes out waits for a person to approve it.
Nobody has to give up the tools they like. The tools just stop starting from zero.
Where to start
If you want the longer version, with what a context lake is made of, what to connect first and whether you need one at all, read our guide: what a context lake is, and how it differs from a context layer.
And if you want to try it, AgentOS is free to start. Connect two or three of the tools your team uses every day, then ask ChatGPT and Claude the same question about your company.
Ashtin Dowler, Head of Growth at AgentOS by Devcore
