No AI silos
between product
and engineering

Every agent and every person across your product lifecycle works from one context graph of what your org decided.

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DECISION RECORD Illustration. A decision record in Brief: the why, cited to where it was decided, and the agents in product and engineering working from it.
KestrelDecisionsD-241

D-241 Pending CPO sign-off

Seat-based pricing for Checkout v2

WHY

  1. Enterprise buyers budget per seat.1
  2. Finance wants revenue it can predict.2
  3. Per-seat billing ships after CPO sign-off.3
Owner
Dana Ruiz, CPO
Open since
Sep 26
Supersedes
Per-order fees

AGENT ACTIVITY ON D-241

  • Claude · Product read the decision → drafting the pricing PRD
  • Claude Code · Checkout eng asked before writing code → holding the API change
  • ChatGPT Enterprise · PMM read the decision → writing the launch brief
  1. Slack · #product-leads · Sep 24 “Seat-based for enterprise? Their buyers budget per seat.”
  2. Pricing review notes · Sep 26 Finance wants revenue it can predict.
  3. GitLab · MR !1182 Per-seat billing in the price API, held for sign-off.

The why never reaches the agent

“The people and agents doing the work can’t easily reach the ‘why’ behind a decision, so they build the wrong thing or re-litigate settled questions.”

A VP of AI product at a global bank

  1. MEETING PRICING REVIEW

    Seat-based pricing, because enterprise buyers budget per seat.

    WHOLE

  2. SLACK #PRODUCT-LEADS

    Seat-based pricing, because enterprise buyers budget per seat.

    PARTIAL

  3. SPEC CHECKOUT V2

    Seat-based pricing, because enterprise buyers budget per seat.

    GONE

  4. TICKET CHK-412

    Seat-based pricing because enterprise buyers budget per seat.

    GONE

  5. CODING AGENT WHAT IT RECEIVES

    > Add per-seat pricing to the checkout API.

    RECEIVED

CONTEXT DECAY Illustration. One pricing decision across four handoffs. The what survives. The why does not.

Every AI tool you bought starts from zero

Coding agents, assistants, and notetakers each do their job. None of them holds what your org decided.

  • YOU ALREADY BOUGHT: Coding agents Claude Code, Cursor, GitHub Copilot

    WHAT IT DOES Write the code

    WHAT IT CAN’T SEE Why the ticket exists, or what product decided last week

    WHAT BRIEF GIVES IT The decision behind the ticket, before it writes code

  • YOU ALREADY BOUGHT: Assistants Claude, ChatGPT Enterprise, M365 Copilot

    WHAT IT DOES Draft PRDs and updates

    WHAT IT CAN’T SEE Last quarter’s decisions. Every chat starts over.

    WHAT BRIEF GIVES IT Every decision and its history, in every chat

  • YOU ALREADY BOUGHT: Meeting notetakers Gong, Granola, Otter

    WHAT IT DOES Capture the conversation

    WHAT IT CAN’T SEE Which decision it changed, or who owns it now

    WHAT BRIEF GIVES IT The decision the meeting changed, and its owner

  • YOU ALREADY BOUGHT: Your agent harness Built in-house, or Factory and Devin

    WHAT IT DOES Runs agents at scale

    WHAT IT CAN’T SEE A graph of product decisions. You are building it yourself.

    WHAT BRIEF GIVES IT The graph, ready to query, so you stop building it

THE GAP The AI stack a transformation team already owns, and the layer none of it carries.

Built into the harness you’re standardizing on

Brief reads Jira, Confluence, GitHub, GitLab, Linear, and Slack. Your agents and pipelines call it the way they call everything else.

  1. $ claude
  2. > Build the Android payment sheet
  3. Marker 1, MCP in the IDE: ● brief_ask payment sheet spec
  4. D-231 confirmed: one checkout spec for mobile and web.
  5. Marker 2, One knowledge graph: D-214 superseded Oct 2, so I won’t build to it.
  6. Building to the shared spec.
  8. Marker 3, CLI in your harness and CI: $ brief ask "does MR !1182 touch an open decision?"
  9. Yes. D-241, seat-based pricing, is pending CPO sign-off.
  10. Owner: Dana Ruiz. Flagging the merge request.
MCP AND CLI Illustration. One session: a coding agent over MCP, then a CI check over the CLI, both against the same graph.

  1. MCP in the IDE Claude Code, Cursor, Windsurf, and VS Code ask Brief before they write code.

  2. One knowledge graph Every decision with its owner, status, and history, including what it superseded.

  3. CLI in your harness and CI Internal harnesses and pipelines query the same graph from any terminal.

CASE · GLOBAL RETAILER

The AI team was standardizing engineering and product on one harness over Claude Code. Product had “zero Confluence,” and the team was building the knowledge graph themselves.

Autonomy only works if agents follow your decisions

Same agents, same 8 tasks, 41 decisions the team had already made. The only change was access to Brief.

Read the benchmark

  • Merge-ready on the first pass, out of 8 tasks

    With Brief: 8 of 8

    Without: 2 of 8

    Change: +6 tasks

  • Team decisions followed, out of 41

    With Brief: 95%

    Without: 46%

    Change: +49 pts

  • Cost per merge-ready task

    With Brief: $0.66

    Without: $2.07

    Change: −68%

BENCHMARK Benchmark, April 2026. 3 runs per configuration. Planned with Claude Opus 4.6, coded with Claude Sonnet 4.6, scored from git diffs by a blind reviewer.

We build your internal pitch with you

Rolling this out is your job, and your execs want proof. Begin with a single team, then take a case built on your own numbers up the chain.

  1. Pilot

    One team and one product line, with an engineer from Brief alongside.

    A working team on one shared graph

    Talk to us about a pilot (opens in new tab)

  2. Your numbers

    The case built on your token spend, hourly rates, and cycle time.

    A one-page business case

  3. Exec demo

    Built with you, on your own decisions and tickets.

    A custom demo for the exec visit

  4. Security review

    Brief runs in our cloud by default. On the Enterprise plan:

    • Private VPC added cost
    • Your own model keys incl. Amazon Bedrock
    • SSO admin controls
    • Self-hosted GitLab
    • Teams, SharePoint, Webex
    • Aggregate-only reporting

    Documentation in the Trust Center

Give every agent the context
your org already decided

One context graph for every agent and every person in your product org.

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