Agentic Shift, the deployment program by Atelier Agentic

Your developers already use Claude Code or Cursor, each in their own way.

In 6 to 8 weeks, the team turns it into a collective practice, on its own code. For CTOs, Heads of Engineering and tech leads who see the gap widening between their best developers and the rest of the team, and want gains that stay when the consultant leaves.

The problem

Without a collective framework, the organization does not capitalize on individual experiments.

Individual usage, not team practices

Cursor and Claude Code are adopted informally. Result: uneven levels and no shared standard.

Gains that aren't captured

The good workflows stay in people's heads. The organization doesn't progress at the pace of its best developers.

Organizational debt that builds up

The more scattered the adoption, the more standardization will cost. The time to act on the foundations is before habits set in.

Tools alone, without a framework

  • A temporary productivity dip before the gains: the DORA 2026 ROI calculator assumes −15% for three months by default.
  • High-adoption teams merge 98% more PRs, but review time increases by 91%.
  • AI-produced PRs wait 4.6 times longer for their first review: review becomes the bottleneck.

With a team framework

  • The biggest returns come from the organizational system, not the tools: internal platform, workflow clarity, team alignment.
  • When adoption is instrumented and measured, throughput becomes visible: +66% epics delivered per developer across 22,000 developers tracked.
  • Realistic adoption target: 80% monthly active users within six months, measured, not self-reported.

Sources: Google DORA, The ROI of AI-assisted Software Development (2026) · Faros AI Engineering Report 2026 · LinearB, 8.1M pull requests (2026). The program's duration, 6 to 8 weeks, is that of the J-curve: we come out of it together, not each on our own.

The walkthrough

Three steps, one real project. No contrived demo, no slides.

WeeksStepWhat we doWhat comes out
1FrameInterviews with the team, inventory of current usage, maturity level, technical context. Choice of the project that will serve as support, with its real constraints.A scope, measurable goals, an honest starting point. And a decision: we continue, or we stop there, one week billed.
2 to 6Work in the fieldWorkshops and pair programming in your codebase. Context, skills, sub-agents, workflows, verification. From skeptic to convinced, each at their own pace.A real piece of work shipped to production. The first conventions, tested.
7 to 8FormalizeWhat worked becomes team practices: usage rules, review, permissions, per-task budget. Setting up adoption and cost tracking.The playbook, the dashboard, a team that carries on alone.

What the team gets

Concrete things, tested on your project, that remain after the engagement.

1
A team playbookValidated workflows, conventions, high-leverage use cases. A living document the team evolves on its own.
2
An adoption and consumption dashboardFour indicators, no more: share of PRs produced with agents, task cycle time, rework rate after review, consumption per developer per week (tokens on Enterprise, Bedrock or API; usage on a seat-based plan).
3
A governance frameworkUsage rules, agent permissions, mandatory human review, secrets management.
4
Shared agents and skillsYour conventions encoded as reusable instructions, for Claude Code, Codex, Cursor or Kiro.
5
A pilot project deliveredA real piece of work from your codebase, built and put into production during the engagement.
6
Prioritized recommendationsThe next use cases, based on your stack and maturity, to keep going without me.

What you'll see at the end

Two objects, not slides. The playbook is written by the team during the program; the dashboard runs on your data.

playbook-agentic.mdteam [name], v1
1Scope: what we delegate to agents, what we don't
2Context conventions: CLAUDE.md, rules, what goes in and what doesn't
3Team skills: six reusable instructions, each with an owner
4Task workflow: spec, plan, tests, implementation, verification, review
5Permissions and guardrails: allowlists, isolated execution, secrets
6Human review: checklist for reviewing an agent-produced diff
7Models and consumption: which model for which task, budget per task
8Metrics: the four KPIs, where they live, who watches them
9Next use cases, in order of leverage
Adoption and consumptionmockup, sample data
[xx] %of PRs produced with agents
[x.x] dmedian cycle time
[xx] %rework after review
[xxx] ktokens per dev per week
Front team
Back team
DevOps

Share of tasks run through the workflow, by team, week [n]. Sample values.

What we work on together

The building blocks that make an agent produce reliable work at team scale.

Context managementCLAUDE.md, rules, memory: the right context, without overload.
Models, tokens, costsWhich model for which task, at what price.
Security and guardrailsPermissions, sandbox, review on sensitive actions.
SkillsYour conventions as reusable instructions.
Agents and sub-agentsDelegate to specialized agents, in parallel.
Workflows and orchestrationChain several agents with checkpoints.
MCPConnect agents to your tools and APIs.
Spec-driven and verificationSpec before code, tests before implementation.

At Trusk, in 2026

Two cohorts, front then back and DevOps, 11 engineers, trained on their own codebase through to the production release of the v2 billing engine.

“We called on Alexandre for training in agentic development, and the result exceeded our expectations. His teaching is clear and accessible, and you immediately sense that he has deep mastery of his subject. Beyond the theory, the workshop approach let us build a real project during the training. I recommend him without hesitation.”

Nicolas, CTO at Trusk
Logistics platform, 3,000 orders a day
Translated from French

Who is involved

Me, at every step. No delegated instructor.

Portrait of Alexandre Ollivier

Alexandre Ollivier, freelance Forward Deployed Engineer, AI for Engineering

Ten years of full-stack TypeScript, three as VP Engineering on a platform of 3 million patients. In 2025, a complete EAI shipped to production in 20 weeks, 100% of the code produced by agents and 100% reviewed. The program is that workflow, handed over to your team.

Frequently asked questions

Is it training?

No. A two-day training course is a good starting point, not a framework: it delivers no project, no playbook, no measurement. Agentic Shift is a deployment program, on a consulting or run budget. If your company wants to fund a training component through an OPCO, it can go through a partner Qualiopi-certified provider.

Do we need to already use Cursor or Claude Code?

No. The framing identifies the team's real starting point, whether it is already experimenting informally or structuring its first usage.

What about 20 teams?

The shift runs on two to three teams in parallel, with a clear end. Sustaining a program across twenty teams is a different need: ongoing support, on a quarterly time-and-materials basis, where I train referents in each team and onboard new ones as we go. One can come before the other, it is not mandatory.

What is the final deliverable?

The playbook, the adoption and consumption dashboard, and a piece of work shipped to production. Everything is produced by the team during the program, not delivered afterwards.

What about code confidentiality?

The program runs on your accounts and your terms: Claude Enterprise or API, Bedrock, Vertex, or models hosted on your side. Usage rules, permissions and secrets management are part of the delivered framework, not an appendix.

How much does it cost?

A fixed price per team: from €15k excl. VAT for six weeks, framing included, quote after the first call. Week 1 is an exit point: if we stop, it is billed €3k and nothing else. Two or three teams in parallel at most.