Sprint One
Discover and Diagnose
Executive interviews, vendor AI audit, and maturity self-rating, conducted remotely. Produces a risk-scored inventory of the AI already running across Septapod and a strategic diagnosis of where the executive team agrees and disagrees on AI to drive the choices to come.
3-4 weeks
$12,500
40h facilitator
4.5h CEO
2.5-5h per exec
Key outputs
- Written strategic diagnosis
- Vendor AI risk tiers
- Maturity baseline
- Governance readiness draft (Decision Rights v0.5)
Open Sprint One prototype →
Sprint Two
Map and Decide
Operational Task Mapping (functional leads break their work down into concrete tasks, tag each for automation, AI assistance, or deliberate human-only handling, producing a ranked set of pilot candidates), then the single on-site workshop at Septapod's headquarters (4-5h single block OR ~6h across two consecutive days, one trip) holding the Playing to Win cascade and pilot selection. Plus the governance readiness assessment and board briefing.
5-6 weeks
$15,000
48-54h facilitator
~9h CEO
6.5-8h per exec
2-2.5h per functional lead (4)
Key outputs
- 3-4 Function Task Briefs (lead-owned printable artifacts; one per function)
- Master task table (Google Sheet, 50-70 tagged tasks across functions, scored on impact and feasibility)
- Ranked candidate set
- Governance readiness assessment (where AI Policy authorities are operational vs. on paper)
- PTW cascade: strategic direction across learning, communications, capacity building, implementation
- Board briefing
- First pilot scoped, eval-defined, launch-ready (selected from the ranked candidate set; rationale captured live during the workshop)
Open Sprint Two prototype →
Sprint Three
Test and Build
Two pilots run during Sprint Three: Brent co-leads the first with the team and advises the second. A third runs independently during the gap period. Distributed governance tested against real decisions.
10-14 weeks
$15,000
46-60h facilitator
9-12h CEO
12-20h governance leads + pilot team
Key outputs
- 2 pilots run in Sprint Three (1 co-led, 1 advised); a 3rd run independently in the gap
- Distributed governance model tested against real decisions
- Written guidance on AI use and member data
- Vendor evaluation criteria (tested against real decision)
- Operational employee communication cadence
- Annual AI Plan taking shape from pilot evidence
- Signal watch-list with assigned owners and trigger conditions
Open Sprint Three prototype →
Sprint Four
Plan and Activate
Gap period evidence drives scaling decisions. On-site board presentation. Annual AI Plan finalized from accumulated pilot evidence, co-created and endorsed by the board and executive team.
5-7 weeks
$12,500
40h facilitator
~4h CEO
3h per exec
2.5h board
Key outputs
- Board-ready Annual AI Plan, co-created and endorsed
- Signal watch-list with assigned owners and trigger conditions
- Capability and confidence to evaluate, pilot, and scale AI from evidence
Open Sprint Four prototype →
What the engagement is like
A look at what the CEO, the exec team, and the organization go through across the four sprints. The test for every activity: what can the team do after it that they could not do before?
Before anything starts
AI is already showing up at the credit union in one form or another. The shape varies widely. Some CUs have policies and active governance. Others have vendors quietly adding AI features no one is tracking. Some CEOs know they need to get serious but haven't yet found a starting point.
What is common across all of them: the CEO does not have a strategic direction that connects what is happening, a shared read on where the exec team stands, or evidence that the current response will hold up under real conditions.
Sprint One: Discover and Diagnose
Week 1: The CEO learns where the team actually stands. An executive survey quantifies how the leadership team sees AI: where they agree, where they diverge, who is ready to move. In a CEO interview, the CEO names things they have been thinking but not yet said out loud.
Weeks 2-3: The full AI footprint becomes visible. A vendor audit catalogs every AI system already operating in the stack and scores each one for risk. A maturity self-rating places the credit union on a readiness scale and surfaces the gaps between how the CEO and the team see it.
Week 4: Brent synthesizes a strategic diagnosis. The diagnosis names what AI is doing at the credit union today, where the risk and opportunity live, where the team is aligned and divided, and the choices the team will need to confront next. The CEO can stop here with a real document, or commit to Sprint Two.
Sprint Two: Map and Decide
Week 1: The CEO picks the functions to study. A short selection conversation applies four written criteria and lands on 3-4 functions for the operational task mapping work.
Weeks 2-3: Functional leads break their work down. Each lead inventories their function as concrete tasks and tags each one: automate, augment with AI, or deliberately keep human-only. Brent calibrates with each lead, then builds a ranked master table of pilot candidates.
Week 4: Each executive's read on AI gets collected before the group convenes. Individual written responses surface real positions before any group dynamic kicks in. Brent synthesizes them into themes and packages a workshop pre-read.
Week 5: The exec team commits to a strategic direction and picks a first pilot. An on-site workshop works through the strategic choices: where AI gets investment, where it does not, what the team is and is not trying to do. The team picks a first pilot from the ranked candidates.
Week 6: Direction documented, board briefed. The strategic direction is written down. Brent leads a board briefing on the direction and the approvals the engagement will surface. Sprint Two ends with a direction the exec team set together, a board that understands it, and a first pilot ready to launch.
Sprint Three: Test and Build
Weeks 1-2: How AI governance works gets defined in practice. The team maps existing functions to AI responsibilities: who decides what, who watches what, where the floor is for member-facing AI. Employee communications launch.
Weeks 3-10: Two pilots run, and the team learns to run them. The first pilot is co-led by Brent and the team, starting in a sandbox before any operational use. The second pilot is led by the team with Brent advising. Both follow the same sandbox-then-controlled-rollout pattern. The CEO joins regular check-ins. The team learns to evaluate AI systems against defined criteria and document decisions.
Weeks 11-14: Evidence accumulates, tools get built. The pilots are evaluated against the criteria set at the start. Vendor evaluation criteria are documented for future decisions. A watch-list names developments worth tracking. A third pilot is scoped for the gap period.
The gap (7-10 weeks)
Brent steps away. The credit union runs the third pilot independently, using the method and governance approach from Sprint Three. Regular check-in calls continue throughout. The gap answers a question worth knowing: can the team run this work without Brent in the room?
Sprint Four: Plan and Activate
Weeks 1-2: How the team did alone becomes visible. The gap-period pilot is evaluated against the same criteria as the Sprint Three pilots. The CEO sees where capability transferred cleanly and where it still needs support.
Weeks 3-5: Scaling decisions get made from evidence. What expands, what retires, what needs more time. The exec team stress-tests the plan against plausible shifts in the environment.
Weeks 6-7: A complete AI strategy gets endorsed. The Annual AI Plan goes to the board for endorsement, built from the direction, the pilot evidence, and the governance testing accumulated across the engagement. The CEO and exec team own a plan with the evidence behind it.
After
The team has the capability to evaluate AI systems, run pilots, and make scaling decisions from evidence. The governance model has been tested against real decisions. The vendor evaluation criteria are ready for the next vendor decision. The watch-list tracks the developments that could change the strategy. When a board member asks "what is our AI strategy," the CEO names the choices the team made, the evidence behind them, and who owns what comes next.
What flows between sprints
Sprint 1 → 2
Strategic diagnosis, vendor risk tiers, maturity baseline, governance readiness draft
→
The diagnosis grounds the function selection for task mapping and frames the workshop. The survey's drag points and the vendor risk tiers feed the function-selection criteria. The maturity gaps carry into the workshop pre-read. The governance readiness draft tells Sprint Two where the AI Policy's authorities need support.
Sprint 2 → 3
Master task table and ranked candidate set, strategic direction, governance readiness assessment, board briefed and aligned, first pilot scoped and launch-ready
→
Governance tested against real decisions during pilots. Remaining ranked candidates inform second and third pilot selection. Strategic direction shapes what gets tried and in what order.
Sprint 3 → 4
2 Sprint Three pilot results (1 co-led, 1 advised), gap-period evidence from the independent third pilot, governance model tested against real decisions, vendor evaluation criteria ready, Annual AI Plan drafted from accumulated evidence, signal watch-list
→
Scaling decisions made from evidence. Plan formalized from accumulated draft sections. Distributed governance already operational.
After Sprint 4
Annual AI Plan, governance model, distributed ownership across functions, signal watch-list, literacy program, member position
→
Septapod can evaluate new AI opportunities, run pilots, make governance decisions, and refresh the plan annually. The engagement succeeds when Septapod has the capability and the confidence to sustain this work.
