The agent in the boardroom

Kirin Holdings CoreMate

In July 2025, Kirin Holdings made room for a new participant in its Group Executive Committee: CoreMate. It was not a thirteenth decision-maker. It was an AI adviser built to test proposals and surface better questions before executives made the call.

Design-before-build case

Why this case matters

In a conservative setting, design came first.

A weaker version of the story would be “Kirin put AI in the boardroom.” The stronger reading is an operating-design choice: CoreMate was given a role, not authority. What appears to have mattered before it arrived were the decisions about what it would touch, what it would say, and where human judgement would stay in charge.

Introduced
July 2025
Architecture
12 AI personalities
Knowledge base
10 years of board and committee records
2026 status
Rolled out to operating companies

The case

A thirteenth chair, not a thirteenth vote.

In an executive committee, the valuable work often happens before anyone decides: a proposal is stress-tested, hidden assumptions surface, and weak options fall away. CoreMate is positioned in that moment. Proposal owners can spar with it before the meeting; executives can see selected discussion points during the meeting.

Kirin says CoreMate was built from ten years of Board and Group Executive Committee data, other internal materials, and the latest external information. Those materials are expressed through 12 AI personalities, each bringing a different management perspective.

That is why the case works as a canvas example. The model is not the story. The design of the role is the story: what CoreMate may see, what it may say, what it may never decide, and who remains accountable when its questions enter the room.

Why it matters

The canvas turns a headline into an operating model.

Without the canvas, CoreMate can sound like a quirky corporate AI story. With the canvas, the design question becomes sharper: what kind of participant are we creating, and where does that participant stop?

The operating model then snaps into view. CoreMate has cognition through the model, control through the meeting process and AI policy, and reach through the knowledge sources and display channels it can use. Its power comes from the combination, not from the model alone.

The filled canvas

Turning the story into nine design decisions.

The entries below are intentionally compact. A canvas should not read like a requirements document; it should make the load-bearing choices visible enough for a team to argue about them.

Worked example

Kirin Holdings CoreMate

Agentic AI Design Canvas
designtheagent.com

North Star

What business outcome must this agent ultimately achieve?

Improve the quality and pace of Kirin Group executive decisions by adding source-grounded challenge before and during senior meetings.

Target Workflow & Success Metrics

Which workflow will it improve, and which metrics will show it worked?

Workflow: Group Executive Committee preparation and live deliberation. Metrics: proposal readiness, new perspectives surfaced, medium- and long-term discussion, decision cycle time.

01

Users & Stakeholders

Who uses it directly, and who is affected by what it does?

Direct users: executives, proposal owners, facilitators, and secretariat. Affected: operating companies, employees, consumers, partners, shareholders, and society.

02

AI Role & Autonomy

What role should it play, and where should its autonomy stop?

Role: advisory executive partner. Autonomy: advise. It challenges, frames, and suggests questions; executives keep decision rights.

03

Performance Needs

What accuracy, explainability, speed, and cost standards must it meet?

Relevant, source-grounded, concise, and timely. Low-noise output is critical: only the strongest questions should enter a senior meeting.

04

Context & Knowledge

What information is available to support its work, and which sources should it trust?

Trusted context: ten years of Board and Group Executive Committee data, internal materials, management philosophy, proposal materials, and current external signals.

05

Tools & Action Channels

Which tools or systems can it read from, write to, or act through?

Reads knowledge sources, supports pre-meeting sparring, and displays selected discussion points in meetings. No autonomous external action appears in public sources.

06

Rules & Boundaries

What must it always do, and what must it never do, even when asked?

Always follow Kirin AI Policy: human-centric, safe, fair, private, secure, transparent. Never present AI output as a binding decision.

07

Memory & Learning

What should it remember, what must it forget, and how will it improve over time?

Remember institutional records and approved feedback. Update external signals. Define what confidential meeting material is retained or forgotten.

08

Oversight & Accountability

Who oversees it, when must it hand off to a person, and who owns the outcome?

Executives own decisions. Proposal owners and facilitators decide what enters the room. Governance sits with Kirin policy and management oversight.

09
Purpose · why & for whom Capability · how it works Governance · Control & Trust

What to notice

Four lessons travel beyond Kirin.

Cell 03

The role is the product.

CoreMate's most important design choice is not the model. It is the word “advise”: challenge, frame, and suggest, while executives keep decision rights.

Cells 04 & 06

Executive attention is scarce.

Twelve personalities are useful only if the system filters them ruthlessly. The design problem is selecting the few questions that deserve the room.

Cell 05

Knowledge makes it specific.

The generic version is “an LLM in a meeting.” The valuable version is an LLM grounded in Kirin's history, proposal context, internal materials, and external signals.

Cells 08 & 09

Learning is a governance decision.

Post-meeting feedback can make CoreMate better, but it also raises what should carry forward. Memory, access, and correction are design choices, not afterthoughts.

Coach audit

We ran this canvas through the coach.

Not as an outside fact-checker saying “be careful,” but as an executive assistant asking the one question that matters: if CoreMate is going into the next senior meeting, what would make its questions worthy of the room? Here is what came back.

Coach review · round one

Minor gaps

What holds together

  • One coherent story at the chosen autonomy: an advise-level role, read-only tools, and human decision ownership all pull the same way.
  • The role is disciplined. CoreMate challenges, frames, and suggests; executives keep the decision.
  • The knowledge base is concrete enough to design around: ten years of senior records, internal materials, external signals, and twelve perspectives.

What pulls apart

  • Cell 01. A cycle-time metric rewards speed, the opposite of the North Star's “better decisions.” Measure decision quality instead, such as the share of proposals where a risk was caught before the vote.
  • Cell 07. The Kirin AI Policy is named; workflow-specific never-dos are not. Spell out what CoreMate must never raise live, such as a named individual's performance or an undisclosed M&A target, and when a question must be withheld entirely.
  • Cell 08. Ten years of board records cannot sit as open memory. State what persists after a meeting, for how long, who can query it, and how feedback is fed back.
  • Cell 09. When a flawed question reaches the room, “governance structures” is not a name. Say who is accountable for catching it.
“What would tell you, six months in, that the decisions coming out of these meetings were actually better, not just faster?”The coach, on Cell 01

Sources

What we can say publicly.

Only public-source claims are treated as facts. Anything about internal thresholds, exact prompt-routing rules, or approval workflows should be read as a design implication unless Kirin confirms it.