For the leader turning AI ideas into outcomes

Take AI from
concept to value

One oversight layer that designs the operating model, and three execution tools that run the work inside it. Enter any door for the need at hand — or start at the Operating Model and build a cohesive enterprise AI transformation.

Prioritize the backlog → Assess & plan each workflow → Monitor the live portfolio
First time here? Start with the Operating Model → design the governance spine, then the three tools run the work inside it.
Oversight & org structure
The toolset — run the work inside the model
WSWSWSWS
The frame · design layer
Operating Model
Workstreams · forums · gates · standards
Start here to build a cohesive program — or jump to a tool.

Design the structure your AI work runs inside, then populate it with your own people. It flags the gaps as you fill it, and its standards flow down into Assess.

1 2 3 4 5
Step 1 · Concept in
Prioritize
Rank the backlog
Start here if you have a list of AI ideas to rank.

Score your AI ideas on value, feasibility and risk — with dependencies — and get a Now/Next/Later board so you fund the right few, in the right order.

Step 2 · The chosen few
Assess
Assess & plan one workflow
Start here if you want a deep evaluation of a single workflow.

For a chosen workflow: an honest fit verdict and autonomy call, then the build plan, the enablement plan (the 70%) and the NIST-aligned governance pack.

Step 3 · To value
Monitor
Track the live portfolio
Start here if you have live initiatives to track and visualise.

The AI lead's cockpit — every initiative's stage, value-vs-target and governance status, with a death-by-pilot watch that catches stalls early.

New Toolkit — plain-English explainers & decision aids for when you're the one everyone asks: prompt vs RAG vs agent, and what an AI agent actually is  →
Why a stack, not a platform

One operating model, not one big platform

The heavyweight platforms ($50k+) are overkill for a team still finding its first agents. These are focused, fast, and opinionated — built on the frameworks that actually work. Design the operating model up top, then run the work inside it with Prioritize, Assess and Monitor — the whole stack, or just the one you need.

What this stack does

Gives you the structure for the whole thing — design the operating model (workstreams, forums, decision rights, gates, standards), then prioritize the backlog, pressure-test each workflow, and watch the portfolio for stalls. Opinionated scaffolding you populate with your own reality, that flags its own gaps.

What stays yours

The authority and the hard calls. The tools help you design and pressure-test; ratifying the model through real governance, making the funding decisions, building the org, signing risk off with legal and security, and proving board-grade value stay with you. A structure to think and decide with — not a system of record.

An agentic-AI deployment method NIST AI Risk Management Framework The 10·20·70 principle The ADKAR change model
The walkthrough

How an AI leader runs week one

Not a feature tour — the exact sequence an AI leader would run with the leadership team, on four real workflows: AP invoice intake, customer-support email triage, spare-parts forecasting and contract review.

  1. 1

    Rank the backlog — and respect dependencies

    All four go into Prioritize. High-value invoice intake is deliberately pushed to Later — it's blocked by a “clean vendor master data” foundation owned by Procurement. You don't start with the shiny one that's blocked; you start with the quick win that isn't.

    Open Prioritize →
  2. 2

    Pressure-test the top pick

    Assess reads customer-support email triage in plain English and returns a tailored verdict — “Strong first agent”, a hybrid call (AI only for the hard, language-heavy judgment), an autonomy level tied to how reversible a mistake is, and a least-privilege access spec. Configure-before-build is the default.

    Open Assess →
  3. 3

    Stress-test your own verdict

    One click runs a devil's-advocate pass that argues the strongest case against — here, that you can't call “sensing an at-risk customer” a human judgment call and then let the agent auto-send. Governance attaches to the workflow's risk, not to whether you built it or switched it on.

    See the challenge →
  4. 4

    Put it on the radar — and act when it stalls

    The assessed workflow lands in Monitor at the “Assessed” stage with its lineage intact (why it was prioritised, what Assess concluded). If it later stalls in pilot, Monitor doesn't just flag it — it surfaces specific, copyable next moves a VP would actually take in a staff meeting.

    Open Monitor →

One sequence, four tools, one defensible story: design the model, rank the work, pressure-test each call, and catch the stall before it quietly kills the program.