Xebia AI Enablement
Shaping Tomorrow with AI Today
The Offer

AI
Enablement

Move one team up a level of AI-in-SDLC maturity — in 8 weeks.

ScopeA single team
FocusThe build phase of the SDLC
Duration8 weeks
© 2026 Xebia · Confidential
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The Starting Point

Every engineer
already has AI.
Almost no organization
sees the effect at scale.

The tools are everywhere. The shared way of working that turns them into delivery is not.

What we propose

One level up. Eight weeks.
On your real backlog.

More than a one-off course or a new set of tools — teams learn a new way of working that stays after we leave.

+1
Maturity level
8
Weeks
1
Team · its own project
01

Trainer-led, hands-on

An expert works alongside the team through every sprint — not a one-off workshop.

02

Your own codebase

Practiced on the team's real tasks and code, never on throwaway exercises.

03

Confirmed by metrics

Before/after numbers prove the shift — the change is measured, not assumed.

Where we work · Scope

The build phase — where AI pays off fastest.

Build is the joint work of everyone who delivers — analysts, developers and QA — not coding alone.

In scope · the build phase
Analysis Development Testing

Across all delivery roles — BAs, developers, QA.

8 One trainer per 8 team members, max.
Out of scope

Infrastructure and areas where AI adds little.

Classic optimization of existing SDLC and engineering practices — available as a separate engagement.

Maturity model

It's a journey towards Software Factory.

Consecutive levels of automation and autonomy in delivery operations.

Level 1

Manual operations

Humans only. Minimal digital support.
Human 90% · AI 10%
Level 2

Assisted operations

Human as collaborator, AI as assistant.
Human 70% · AI 30%
Level 3

Semi-automated

Human as supervisor, AI as doer.
Human 50% · AI 50%
Level 4

Automated

Human as orchestrator, AI as system.
Human 30% · AI 70%
Level 5

Autonomous

Human as governor, AI as workforce.
Human 10% · AI 90%
An AI-powered software lifecycle

Agentic Engineering Enablement Framework.

A coherent program that guides your engineering organization in adopting agentic engineering — modular, so selection can be tailored to your needs.

Diagnose

Readiness Assessment

  • Diagnose where the team stands today
  • Agree the target level and project slice
  • Set the baseline to measure against
Transform
Capability — per team

Upskill with trainings — set knowledge foundations, establish vocabulary, share current industry practices.

Embedded Practice Leaders — Xebia experts integrated into your teams, deep change live on real work.

Platform — shared across teams

Golden path, playbook skeletons, skills & MCPs, project templates — built incrementally.

Agentic code review Cost & governance Auto quality gates Task-specialized skills Knowledge base
Sustain

Keep it running

  • Live ROI reporting
  • Governance
  • Ongoing updates to the asset library
  • Platform improvements & new innovations
  • Maintain the platform
Before you commit

Start free — see where you stand.

A free pre-assessment, before the program begins — two inputs that give an initial read on your starting point and let us tailor Enablement more precisely.

AUTO

Automated code analysis

Assesses your application's current status.

INPUT

Team questionnaire

Completed by the team.

The result

An initial picture of your starting point.

See where you stand today — and we tailor the Enablement program to it before it begins.

Free · no commitment
Phase 1 · Weeks 1–2 of 8 · the program begins

The AI Assessment — the mandatory entry.

It's the foundation the rest of the program rests on.

01

Diagnose the real maturity level

Joint work, observation on current tasks, and short 1:1 conversations. No rankings, anonymous surveys, or reports on individuals.

02

Inventory the tools

What's in use today, and how it's used.

03

Pick a real project slice

Chosen with the team lead — the remaining 7 weeks run on it.

04

Set the metrics baseline

Measured again at the end — a before/after comparison.

ResultStarting level + recommended target (start + 1)
ResultFoundation gaps to address
ResultSelected project slice + metrics baseline
If critical foundations aren't ready, we recommend a short prep phase — or rescaling the goal, so we don't aim too high.
Eight weeks · four phases

We lead first — then you take over.

Phase 1 · W1–2

Assessment & Calibration

Diagnose the level, pick the slice, set the baseline.

Phase 2 · W3–5

Trainer-Led Delivery

Knowledge sharing, live demos, pairing — the first real PRs with the new method.

Phase 3 · W6–7

Team-Led Execution

The team works on its own; Xebia reviews and raises the bar.

Phase 4 · W8

Synthesis & Offboarding

Measure, document, hand over ownership.

◀ Xebia leads · Weeks 3–5
Your team leads · Weeks 6–7 ▶

Everything runs on a real fragment of your code. The hand-over in Weeks 6–7 is what makes the new way of working survive after we leave.

Results & artifacts

What stays with you after Week 8.

A team that can work one level higher — plus the artifacts to keep it going on its own.

A trained team

Working one maturity level higher — and able to keep climbing.

Team platform

Playbooks, skill & brief repositories, tool config, review checklist.

AI Coding Governance

What AI may do alone, what needs approval, what's off-limits.

Before/after metrics report

The change, in the data from your own tools.

Readiness checklist + roadmap

What to meet before starting the next level.

Before / after

We measure the change — not just claim it.

The same set of indicators at entry (Week 1) and exit (Week 8) — read on three layers.

01
Leading criterion

Qualitative

Does the team operate at a new maturity level?

Transition exit criteria — the target-level readiness checklist. E.g. 2→3: each developer comfortably runs 3+ agents in parallel; AI-generated PRs pass a redesigned review; governance in place and used.

02
Supporting evidence

Quantitative

Is the change visible in the data from your tools?

Lead TimeThroughput (DDM)AI adoption · % devs, % PRsToil reduction

Source: your own data — Git, CI/CD, IDE telemetry.

03
Directional

Business

Does it translate into value?

Estimated value of time gained — from toil reduction and throughput — set against program and license cost. Shown as a trend, not a single guaranteed number.

We measure the delta on your own data — baseline in Week 1, the same set in Week 8. We don't promise a number up front; we show the change.
Foundations & conditions

Eight weeks is necessary — not sufficient.

Every level up rests on technical and organizational foundations. We verify them in Phase 1 — and if critical ones are missing, we run a short prep phase first.

Technical

On the code, environment and process side — e.g. test coverage, CI/CD.

Organizational

On the side of the team and its surroundings. Requirements rise with the target level.

Start now: legal & security approval of AI tools is usually the longest single blocker — begin it even before Week 1.
Xebia ↔ your team

Co-led — you keep ownership throughout.

Activity
Xebia
Your team
Assessment & level diagnosis
Leads & diagnoses
Provides access, participates
Project slice
Advises
Decides & owns
Tools & environment
Leads & configures
Grants access, validates
AI-first work on functionality
Coaches & reviews
Builds & delivers
Governance & review
Structures & proposes
Approves & applies
Playbook & artifacts
Compiles & delivers
Co-creates & owns
Ownership stays with you — decisions, code and artifacts are yours.
The weight shifts — Xebia leads W3–5, your team leads W6–7.
Accelerators

We bring tools that speed the work.

A few examples — not the full list. We match the toolset to your stack and target level.

Portfolio Manager

Drop a codebase in, get a dashboard — assess and prioritize a whole portfolio.

  • Auto due-diligence — quality, security, tests, tech debt.
  • AI-readiness assessment, stack-aware.
  • Voice-bot interviews with tech leads.

Modernizer

GenAI-enhanced legacy modernization across the full migration lifecycle.

up to 70%
effort saved vs. traditional
  • Investigation + auto documentation.
  • Technical-debt detection in minutes.
  • Code conversion at scale, consistently.

ACE · AI-led Digital Engineering

Structured AI agents that unify the SDLC from discovery to operations.

  • Unified orchestration — one layer, not scattered tools.
  • Product-level context of your codebase.
  • Enterprise scale, legacy included.
Next step

Start with the free pre-assessment.

A questionnaire and an automated code analysis — an initial read on your starting point, no commitment. The 8-week program begins when you're ready.

Book the pre-assessment
In parallel: kick off legal & security approval of AI tools — it's the longest lead-time item.
Shaping Tomorrow with AI Today