For leadership and operations

Every team's AI works from what leadership actually decided.

Priorities change in a meeting and reach people a week later. Agents never hear about it at all. Put decisions, priorities and the operating rhythm in one governed place, with an owner for each, and every agent reads the current version.
In their words

What leadership and operations teams say when AI starts to drift.

Each of these has the same cause: the knowledge your AI needs has no governed home that every agent reads from. Find your problem →

  • “Agents are still acting on last month's priorities.”
  • “Nobody can find where a decision was made, or by whom.”
  • “Each department's AI has its own idea of the plan.”
  • “We can't show what our AI was reading last quarter.”
Your team's shared brain

What goes in, and the agents that run on it.

What goes in

  • Decisions, with who made them and when
  • This quarter's priorities and goals
  • Operating rhythm: meetings, reviews and owners
  • Policies every team follows

Each area gets an owner who approves changes, so agents read the version your team signed off on.

Weekly brief

Summarizes what changed in priorities and decisions this week.

Never sees: Board-only material.

Policy answerer

Answers 'are we allowed to' questions from approved policy.

Never sees: Drafts under review.

Decision finder

Finds the decision behind a rule, with its owner and date.

Never sees: Personnel files.

Get started

Three steps to a working start.

Use the executive starter for leadership, and the team starter for shared processes and handbooks.

  1. 1

    Start a nest from the executive starter

    Folders for strategy, operations and leadership, with a decision framework to fill in.

    Terminal
    $ npx @promptowl/contextnest-cli init --starter executive
    Get PromptOwl free →
  2. 2

    Record decisions as you make them

    Each decision gets an owner and a date. Retire the old one when it changes, and agents stop using it.

  3. 3

    Connect your agent and ask it to map how it can help

    In Claude Code, add the ContextNest plugin (or use the Connect button in a hosted nest), then paste the prompt below. It reads your nest, proves it, and drafts an opportunity map for you to approve.

    In Claude Code
    $ /plugin marketplace add promptowl/contextnest
    Then
    $ /plugin install contextnest
Map how it can help

Ask your agent what it could do for your team.

Paste this into Claude Code once it's connected to your nest. The agent proves it can read your knowledge, then drafts an opportunity map for you to approve.
Claude Code · a fictional support team's nest
Example
  1. 1. Prove it
  2. 2. Get oriented
  3. 3. Map it
  4. 4. Save as a draft
The prompt
My team is the leadership and operations team.

You're connected to my ContextNest nest. Before anything else, prove it: search the nest, open two or three documents, and tell me their titles and one line from each. If you can't read real documents, say so and stop. Don't guess what's in the nest.

Use search and single-document reads. If one way of reaching the nest fails, try the other tools you have (the ContextNest MCP tools, the ctx command line or the REST API) before you give up.

If the nest is empty or nearly empty, ask me three questions first: what my team does, which questions people ask us most, and which documents we'd trust an agent to answer from. Then work from my answers.

Then build me an opportunity map:
1. Five things you can do for me today with what's in the nest. For each one, name the documents it relies on.
2. What's missing: the documents or decisions that would let you do three more things, and who on my team probably owns each one.
3. The agents you'd run on this nest: what each one does, and what each one should not be allowed to see.

Save the map back to the nest as a draft titled "How AI can help us: opportunity map". Don't publish it or share it anywhere. Ask me before you publish anything.
One shared brain

Every team adds its own area.

Start with one team. The next team starts from what's already approved.

Start with your team. Free.

Connect the AI tools you already use, and approve what they're allowed to rely on.