How to share project context with your team's AI agents

To share project context with your team’s AI agents, put the brief and relevant sources in a shared project space. When work passes to another person, include the current output, open questions, and next owner. In TalentOS, a Room provides that shared space while personal chats and memory stay private.

You probably know the pattern. Someone uses an agent to do good research. They paste the answer into a team chat. A teammate asks where the numbers came from. The original person goes back to their private chat, asks for sources, and pastes another answer. Then someone else needs a deck.

The agents are doing their jobs. The humans spend the afternoon carrying answers between them.

Why does your team keep repeating itself?

Imagine a founder, an operator, and an engineer evaluating a new service. The founder’s agent has customer context. The operator has cost assumptions. The engineer uses Claude Code or Codex to explore what is feasible.

Three individually useful answers can still disagree about the customer, the budget, or what “ready” means.

Before asking for more output, agree on the shared job. For example: “Recommend whether we should offer this to our first ten customers, with an explicit list of what we would need to build.”

Now each contribution has something to connect to.

1. Put the brief and sources in a shared Room

TalentOS is a multiplayer AI workspace where people and their existing agents work together in Rooms. A Room can hold the conversation for this evaluation while people keep their personal AI work private.

Add the actual participants. Share the brief and the sources they need. State what the Room should produce and who will decide whether it is good enough.

Everyone in the Room can read what is shared there. That is the useful boundary: the team gets common working context, and personal chats, memory, private runs, and approvals stay owner-only.

Do not dump an entire private conversation into the Room just because it contains one relevant paragraph. Share the paragraph, the source, and the decision it supports.

2. Use a handoff template when work changes hands

Here is a reusable format:

Goal: Decide whether to launch a small paid pilot.

What changed: We now have a draft scope and a first cost estimate.

Sources: The agreed customer notes and pricing assumptions linked below.

Work to review: The saved proposal version linked below.

Still uncertain: Support effort and one external dependency.

Next owner: Sam checks feasibility, then Maya decides the pilot scope.

Copy this into a Room message or your next project update. Fill in the fields and include the sources and saved output. The next person can start with the decision instead of reconstructing the history.

Ask your agent to prepare this handoff when it finishes a meaningful chunk of work. Review what it plans to share. An agent acting for you should not expose private notes simply because they helped produce the answer.

3. Name the person responsible for the next step

“The AI said yes” is a weak approval process. Someone needs to own the recommendation and the action that follows it.

In TalentOS, each AI acts for one person. AI-written Room replies remain attributed to that human owner. The owner’s approval rules still apply when work moves from discussing an action to taking it.

That gives a teammate a better question to ask: “Maya, are we ready to send this?” It also separates agreement on a draft from permission to take an external action.

Measure the interruption you removed

Try this with one handoff this week. Count how often the recipient needs to ask for missing context, a different file, or the name of the decision-maker. You do not need a dashboard to notice that the same clarification arrives three times.

If the handoff still creates confusion, improve the brief or the output. Adding another agent will not fix an undefined decision.

For the next step, read how to get Claude Code and Codex working together. If the answer is useful but the deliverable is missing, start with artifacts you can hand over.

When someone new joins the project, use a short onboarding brief and first task. For agreements that should survive the next handoff, keep shared project memory current.