AI Agents Need a Living Understanding
An assistant can find an old email. Can it tell what changed since then? Why Team0 gives agents a way to work from the situation as it stands now.
Say a customer asks you to send a proposal by Friday. You say yes. On Thursday, you send an email saying it's attached. It isn't. On Monday, you send the actual document.
Now ask your AI assistant: do I still owe them the proposal?
It can find all three emails and still get the answer wrong. It might see Thursday's “sent it” and close the matter too early. Or it might keep reminding you about Friday's deadline long after Monday's delivery. Search found the messages. It didn't keep up with what happened.
That's the problem we're trying to solve with Living Understanding. Team0 keeps the original evidence, but also keeps track of the people, decisions and changes those sources point to. When something changes, an authorized agent should get the newer picture and be able to show where it came from.
Finding the email isn't enough
An inbox tells you what someone wrote. It doesn't tell you whether they were right, whether you agreed, or whether a later message changed the situation.
Team0's World Model connects people, claims and relationships to the sources behind them. Team0 also keeps track of what still holds, what has changed and what remains disputed. An agent gets only the part of that picture it is allowed to see.
How Team0 works
How a new event can change the next answer
Connected sources
Original evidence
Where it came from, who sent it and when
World Model
People, decisions, relationships and corrections
New evidence can confirm or change an earlier conclusion.
Current picture
What still holds, what changed and what remains unclear
The agent's answer
Only what this agent is allowed to know
New information goes back into Team0. An agent's own answer is not proof that it got something right.
A map of the system. It can only work from sources you connect, and each agent sees only what you allow.
We keep those steps separate for a reason. A stranger can write “urgent” in an email. That is evidence that the stranger feels urgency. It isn't evidence that this person matters to you. We ran into exactly this distinction while working on first-contact emails.
What would settle the proposal?
Go back to the missing attachment. Thursday's email is real, but it didn't deliver the proposal. Monday's email might settle the matter if it went to the right person and contained the document you owed them. A meeting about the proposal would not, on its own, prove delivery either.
The answer needs a trail you can inspect: which account the message came from, who sent it, when it was sent and what later evidence changed the conclusion. Team0 also records when it learned about an event. An email sent on Tuesday and connected on Wednesday is still a Tuesday event. Arrival order should not rewrite what happened.
A request can stay in the history after you fulfill it. What changes is the answer to “do I still owe this?” Team0 can follow that change when it has captured the promise. Here's the proposal example in more detail. Connecting an agent alone doesn't turn every promise in your inbox into a tracked task.
Different agents, different access
An agent preparing you for a meeting may need the full background. A coding agent might need only the decision that changed a feature's priority. A public-facing agent should not see your private email at all.
Each agent can draw from the same understanding without seeing the same private details. You can connect an agent and set what it may see. We're still adding support for more agents.
The question to ask of any AI memory system is simple: when the world changes, what changes in the agent's next answer? And can it show you why?
Continue reading
Read next
Living Understanding
Beyond the Knowledge Base: How a Company Learns to Understand Itself
Search can find the message. It can't always tell whether the work is done, who knows the answer, or what changed. What a Company Brain needs beyond search.
Living Understanding
The Four Levels of Agentic Understanding
Remembering an old answer is easy. Noticing that it stopped being true is harder. Four things an AI assistant needs to do well.
Living Understanding
Your Agent Needs a Model of Your World, Not a Longer Chat History
A chat history remembers what was said. It doesn't reliably know which meeting moved, who made a promise, or what changed afterward.