01
Tailored live sessions
No lectures. Sessions are designed around your artefacts — your emails, your reports, your pipeline, your policies — and run live so people practise on the real thing.
Product 02 / Implementv.2026.AI
AI Adoption &
Implementation Sprint.
Surgical, tangible, finite. A scoped engagement around one workflow or one team: deep role and workflow audits, ROI-based mapping, then real automations and vibe-coded builds — delivered through live sessions and challenges, never lectures.
The promise
Why a sprint works
Most teams have watched enough demos. What they're missing is the felt experience of shipping something real with AI, alongside their colleagues, inside their own stack. A Sprint manufactures that experience on purpose.
It is deliberately finite: a defined workflow or team, a defined set of builds, a defined end date. You get the audit, the ROI map, the sessions, the builds and the artefacts — and you own all of it. Nothing is held back to create a dependency on us.
Audit & ROI mapping
Before anything is built
- 01
Role-by-role and workflow-by-workflow audit of the team in scope — where the hours actually go.
- 02
ROI-based mapping: every candidate use-case sized by hours saved, revenue touched and risk carried.
- 03
A shortlist of builds we can finish inside the engagement, agreed with you before we start.
- 04
A fluency baseline for the team, so the change is measurable and not anecdotal.
How we run it
Sessions, challenges, builds
02
AI challenges & vibe-coding rounds
Friendly competition against a real business problem. Teams build, demo and get scored. Engagement stops being something we hope for and becomes something we design.
03
Coached builds
Automations, agents and vibe-coded internal tools built with the team, on your stack, and left running in your accounts.
What you leave behind with
Deliverables
- 01
Working automations and vibe-coded tools, deployed in your accounts.
- 02
A prompt and workflow library documented for reuse.
- 03
A named internal AI owner for every artefact shipped.
- 04
The ROI map and a ranked backlog of what to do next.
- 05
Responsible-AI guardrails for the workflow: data rules, approval steps, human-in-the-loop checks.
- 06
A 30-day review cadence already in the calendar.
Outcomes
What changes
2–4
Weeks, start to finish
3+
Builds shipped live
100%
Artefacts owned by you
1
Named internal owner
- The team runs its own AI review after we leave, without being asked.
- Work that used to be queued to a specialist gets done in the team, same day.
- People can say what AI is bad at, not just what it's good at — that's what makes usage safe.
- Leadership has an ROI number they trust, because they watched it get built.
The team who runs it
The bench
Led by an operator. Staffed by practitioners who've shipped AI in production.
Every engagement is led by Joao Alves, a second-time founder who has worked in AI since 2020 — most recently inside a leading fintech company at a $7B+ valuation doing over $500M ARR, helping regulated firms put AI into production.
Joao is supported by a small bench of senior practitioners drawn from financial services, VC-backed AI startups, and risk and governance teams. Engagements are staffed for fit — every workshop, team challenge and governance program is led by people who have done the work, not delegated it.
- AI operators since 2020
- Fintech, regulated industries
- Shipped, not just advised
- Workshops on 3 continents
- Bench scales with the brief
Next step
When one team proves it, the Transformation Programme takes it across the org.
Ready to compound?
Most engagements start with a 30-minute scoping conversation. No deck, no pitch — just your context.