AI Delivery Profitability

Turn AI adoption into measurable gains in margin, predictability and quality.

Accelerate software delivery without increasing technical debt, operational chaos or hidden rework.

45 minutesFreeNo generic pitch

You leave knowing where your delivery system is leaking margin — whether we work together or not.

Three benefits. One system.

Where AI adoption shows up in the P&L

The question is not whether teams use AI. It is whether AI adoption moves margin, growth and delivered value — or just activity.

AI adoption without technical debt or review overload

AI can accelerate code and quietly multiply review burden and risk. Guardrails decide which of those you get.

What changes in 30 days and what it costs your teams

Predictable delivery and a clear cost-to-deliver matter more than raw speed. We measure both against a baseline.

Proof

Measured outcomes, with baselines.

Software consultancy
€7M → €9M

A €7M software consultancy grew to €9M in 12 months while improving profit per delivered hour by 15% — through OKRs, delivery discipline and AI-enabled workflows.

Product delivery

Pending client-approved case: “A product team reduced rework by X% and improved delivery predictability from X% to X% in X weeks.” Published only when the client approves the numbers.

B2B software
−74% CAC · +90% leads

A B2B software client cut customer acquisition cost by 74% and increased qualified leads by 90% by fixing positioning before adding spend.

Every number above has a baseline, a timeframe and a client who approved it. That is the only kind of metric we publish.

Pending: client testimonial (quote, name, role, company, team size and country) — plus logo or a 60-second video. Added only once approved.
The problem

AI adoption is not the same as AI impact.

Your teams may already use Copilot, Claude, ChatGPT, Cursor or other AI tools. Some people use them every day. Others barely touch them.

Managers expect productivity gains. Developers worry about quality. Leadership wants ROI. But the core problems often remain:

delivery dates still move
rework still eats margin
senior engineers are still overloaded
AI-generated work creates new review burden
productivity gains do not reach the P&L

The issue is not access to AI. The issue is whether your workflows, quality standards and metrics have changed enough to capture the value.

Our stance

Three lines we don’t cross.

01

No baseline.

No serious transformation.

02

No guardrails.

No safe AI adoption.

03

No measurement.

No proof of impact.

First 30 days

What happens in the first 30 days?

WeekFocusOutcome
Week 1DiagnoseDelivery profitability leak map and AI maturity baseline
Week 2PrioritiseAI use case portfolio and risk map
Week 3GuardrailQuality, security, review and validation standards
Week 4PilotMeasured workflow experiment and go/no-go recommendation

Operational load: your team invests 2–3 hours per week. No workshops that stop delivery. We work inside your existing rituals.

You will know where the opportunity is, what risks need to be controlled, and whether a bigger programme makes sense — or not.

The complete system

AI may be the opportunity. Your delivery system is the whole picture.

Not every profitability problem starts or ends with AI. Sometimes the constraint is unclear product strategy, fragmented priorities, weak delivery flow or an operating model that cannot respond fast enough.

01

Turn AI adoption into measurable improvements in margin, predictability and quality, with baselines and engineering guardrails.

02

Improve how teams plan, collaborate and deliver. Replace ceremony-led change with a measurable roadmap focused on flow, value and business outcomes.

03

Connect customer needs and business strategy to product decisions through discovery, validated learning and value-based prioritisation.

04

Help leadership align strategy, structure, people, processes and technology so the organisation can respond to opportunities faster.

05

Build practical Scrum, Product Ownership, Kanban and Agile Leadership capability through courses applied to real working situations.

The offer

Start with a free Diagnostic. Decide with data.

AI Delivery Profitability Diagnostic

Free · 45 minutes

A 45-minute working session with Nicolás (not a salesperson, not a junior) for CEOs, CTOs, COOs and Heads of Engineering.

You leave with
your top delivery profitability leaks
your AI adoption maturity level
your highest-value AI opportunities
a written 30-day improvement roadmap, delivered within 48 hours

What this is not: a tool demo, a generic sales call, or agile coaching disguised as strategy.

Availability: a limited number of diagnostics per month, run personally.

Book your FREE Diagnostic
What comes after

If there is real leverage, a Pilot Sprint.

If the Diagnostic shows real leverage, the next step is a 4–6 week Pilot Sprint — fixed price agreed before start. No surprises, no scope creep.

Our commitment: if the pilot does not show measurable improvement over the baseline, Optimum Agile recommends not scaling and includes that recommendation in the final report.

If the Diagnostic shows no leverage, this is communicated in the first 20 minutes and the client keeps the roadmap.

Engineering depth

What this looks like inside your engineering team.

The work uses the client’s real delivery system: backlog, pull requests, test strategy, coding standards, review process and Definition of Done.

AI usage policy for engineering teamsAI-assisted PR review checklistClaude / Cursor / Copilot workflow playbooksContext files: CLAUDE.md, AGENTS.md, repo guidelinesAI Definition of DoneTest generation & legacy-code-explanation workflowsRefactoring guardrailsEngineering AI maturity assessment
Pending: real engineering artefact with client data anonymised

Your code and data stay yours. NDA by default. No code leaves your environment. AI usage during the engagement follows your data policy, not ours.

The goal is not to make developers use more AI. The goal is to use AI where it improves quality, speed, learning and control.

Fit

Designed for teams where AI adoption needs to become business impact.

Strong fit

a software or SaaS company with 10–100 engineers
under margin or delivery pressure
already experimenting with AI tools
looking for measurable impact, not generic training

Probably not a fit

an AI inspiration workshop
more tools without changing workflows
forced adoption without developer trust
productivity claims without measurement
FAQ

Questions technology leaders ask first.

Tools create potential. Operating models capture value. Few teams have redesigned workflows, quality standards and metrics around AI.
It can, if adopted without guardrails. That is why review, testing, security and validation standards are built from day one.
Good. Technical skepticism converted into standards and validation is exactly what makes adoption safe.
NDA by default. No code leaves your environment. We adapt to your data policy — including which AI tools are allowed and how.
No. Agile is not the product. AI is not the product. Better delivery economics is the product.
The Diagnostic is free. The Pilot Sprint is a fixed price, agreed before start.
Yes. Delivery & Agile Transformation, Lean Product Management, Business Agility and Professional Training remain available — positioned around measurable business and delivery outcomes, not the adoption of a framework for its own sake.
The Diagnostic identifies the constraint before recommending a service. If AI is not the highest-leverage opportunity, the written roadmap will say so and point to the most appropriate next step.
Lead magnet

Not ready for a conversation? Find your score first.

AI Delivery Profitability Scorecard — a 10-minute interactive self-assessment. Answer online, get your maturity level (1–5) and your top leak immediately.

Take the Scorecard
Scorecard result preview

Find out where your delivery is leaking margin. In 45 minutes. Free.

One 45-minute working session. A written 30-day roadmap. Yours to keep either way.