For sales and revenue teams

Every rep's AI quotes the price you approved this quarter.

Reps draft emails, proposals and call prep with AI. When each one works from their own saved prompts and old decks, prospects hear three versions of your pricing. Put the approved version in one place and every rep's AI reads it.

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In their words

What sales 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 →

“A prospect got last quarter's pricing from a rep's AI.”
“Two reps sent the same prospect different answers about a feature.”
“Competitive positioning lives in one person's head and one old deck.”
“Every proposal starts from whatever the rep found in the drive.”

Your team's shared brain

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

What goes in

Current pricing and packaging
Objection handling and talk tracks
Competitive positioning, with dates
Approved case studies and claims

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

Call prep

Builds a one-page brief for a meeting from approved positioning.

Never sees: Other customers' deal notes.

Proposal drafter

Starts proposals from current pricing and approved claims.

Never sees: Retired price sheets.

Objection coach

Suggests answers from the approved talk tracks.

Never sees: Unapproved competitor rumors.

Get started

Three steps to a working start.

1
Start a nest from the sales starter
Folders for playbooks, competitive intelligence and enablement, ready to fill.
Terminal
```
$ npx @promptowl/contextnest-cli init --starter sales
```
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2
Add pricing, talk tracks and positioning
Whoever owns pricing approves the price sheet. When it changes, every rep's AI picks up the new version.
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. Prove it
2. Get oriented
3. Map it
4. Save as a draft

The prompt

My team is the sales 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.

See every team See how it can help

Start with your team. Free.

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