GitHub Copilot • Claude Code • Microsoft Copilot Shallow tool usage
Most developers use AI for autocomplete. This program shows how to work with AI on complex, multi-file, and multi-step engineering tasks - the level where real productivity gains happen.
GitHub Copilot • Claude Code • Microsoft Copilot Remote or On-site 2-Day Intensive
AI for Developers & Engineering Teams
Go beyond autocomplete. Master AI-assisted development, agentic coding, and enterprise-grade governance.
Most developers already use AI to write code. Few use it well. This 2-day intensive workshop focuses on what actually matters in a professional environment: effective tool mastery across GitHub Copilot, Microsoft Copilot, and Claude Code - combined with governance, security, and the agentic frameworks that let AI handle real multi-step engineering tasks.
Format
2-Day Intensive
Practical stack
Tools your team will use
Practical tools, live workflows and a clear review path.
-
GitHub Copilot
Use the tools your organisation has approved, with clear task boundaries.
-
Claude Code
Turn one live business task into a reusable workflow your team can own.
-
Engineering quality guardrails
Verify outputs, protect sensitive information, and keep the final decision human.
Decision support
Who is this program for?
This isn't an intro course. Participants already write code and use AI tools. The focus is on mastery, governance, and the agentic layer - taught by practitioners who build with these tools every day, not trainers working from slides.
- Software engineers and developers using or planning to use AI coding tools
- Engineering leads responsible for AI tool adoption and team standards
- IT and DevSecOps teams managing governance of AI-generated code
- Technical architects evaluating agentic AI for development workflows
What this workshop helps your team do
AI for Developers & Engineering Teams is a facilitator-led corporate workshop for teams that need usable skills and governed workflows. Most developers already use AI to write code. Few use it well. This 2-day intensive workshop focuses on what actually matters in a professional environment: effective tool mastery across GitHub Copilot, Microsoft Copilot, and Claude Code - combined with governance, security, and the agentic frameworks that let AI handle real multi-step engineering tasks.
Exercises are adapted to your approved tools, real workflows, data boundaries, and the decisions that must remain under human review.
Delivery is available on-site, hybrid, or online in France, including Paris, Lyon, Marseille, Bordeaux, and Toulouse. The agenda can be adjusted for one function, a cross-functional cohort, or an executive group.
This workshop is designed for software engineers and developers using or planning to use AI coding tools Engineering leads responsible for AI tool adoption and team standards IT and DevSecOps teams managing governance of AI-generated code Technical architects evaluating agentic AI for development workflows Teams using GitHub, Azure DevOps, or Microsoft 365 environments
Your team leaves with evidence of learning and reusable outputs, including Prompt library for coding workflows (Copilot-first + Claude Code variants), AI code governance framework (review checklist, security guardrails), Agentic workflow templates for common engineering tasks, and Team adoption playbook with role-based guidelines. Before delivery we confirm objectives and sensitive-data rules; after the session you receive the agreed workshop artefacts and next-step recommendations.
01
Who is this program for?
- Software engineers and developers using or planning to use AI coding tools
- Engineering leads responsible for AI tool adoption and team standards
- IT and DevSecOps teams managing governance of AI-generated code
- Technical architects evaluating agentic AI for development workflows
- Teams using GitHub, Azure DevOps, or Microsoft 365 environments
02
What this program addresses
Security and compliance gaps
AI-generated code introduces real risks: hallucinated libraries, leaked credentials, license issues, and policy violations. We cover how to catch, prevent, and govern these at scale.
No standard for AI use across the team
Individual experimentation produces inconsistent results. We help teams define shared standards, review processes, and prompting conventions that work across the whole engineering org.
Agentic AI still feels out of reach
Autonomous agents that handle full task chains - from spec to PR - are here now. This program gives developers hands-on experience building and governing real agentic workflows.
03
What makes this program different
This isn't an intro course. Participants already write code and use AI tools. The focus is on mastery, governance, and the agentic layer - taught by practitioners who build with these tools every day, not trainers working from slides.
What your team takes away:
- Prompt library for coding workflows (Copilot-first + Claude Code variants)
- AI code governance framework (review checklist, security guardrails)
- Agentic workflow templates for common engineering tasks
- Team adoption playbook with role-based guidelines
- 30-day implementation roadmap
04
Program overview (2-day remote workshop)
Group size: 8-15 participants Format: live remote sessions, hands-on exercises on real codebases Tools: GitHub Copilot, Claude Code, Microsoft Copilot, VS Code Pre-work: optional IT context audit to confirm environment compatibility
Day 1 - Module 1: AI Tool Mastery (GitHub Copilot, Claude Code, Microsoft Copilot)
- How each tool differs and when to use which
- Context injection, multi-file awareness, and working with large codebases
- Advanced prompting patterns for code generation, refactoring, and debugging
- Claude Code for longer reasoning chains and complex tasks
Outcome: Developers can use all three tools effectively for real engineering work - not just line completions.
Day 1 - Module 2: Security, Compliance & Code Governance
- Common risks: hallucinated dependencies, credential exposure, GPL-tainted code
- Internal policy alignment: what AI can and cannot touch in your environment
- Code review workflows adapted for AI-assisted development
- Practical red/amber/green guardrails for the team
Outcome: A shared governance standard your team can adopt from day one.
Day 2 - Module 3: Agentic AI for Developers
- What agentic frameworks are and how they work (Copilot Workspace, Claude Agents, custom agents)
- Task decomposition: breaking engineering tasks into agent-executable steps
- Hands-on: building a simple agentic workflow for a real use case
- Limitations, failure modes, and when not to use agents
Outcome: Participants can design and run basic agentic workflows for engineering tasks.
Day 2 - Module 4: Team Standards & Structuring AI Use at Scale
- Defining AI usage tiers across your org (who uses what, and how)
- Prompt libraries and shared conventions for consistency
- Measuring the impact of AI tool adoption
- Onboarding new developers into an AI-enabled workflow
Outcome: A team-level structure for sustainable, governed AI-assisted development.
05
Optional add-ons
Business & Internal Teams Track (Half-day)
- • Basic to advanced prompting with ChatGPT Enterprise
- • Deep Research, web search, and specialised modes
- • Use-case mapping for non-technical roles
- • Session designed for groups of ~10
AI Champions Program
- • 2-3 internal champions trained to run agentic AI independently
- • Champion playbook and internal enablement kit
- • Ongoing support to sustain adoption after the workshop
06
What we practise together
- Refactor a legacy function using Copilot with a defined style guide
- Generate a test suite from a spec with Claude Code
- Audit AI-generated code for security issues and dependency risks
- Run an agentic task from ticket to pull request
- Build a shared prompt library for a specific engineering workflow
- Define team guardrails for AI tool use in production code
07
What your team will achieve
- Faster development cycles with AI used at the right depth, not just for autocomplete
- A shared governance standard that reduces security and compliance risk
- Real experience with agentic workflows - not just theory
- Internal champions who can sustain and grow AI adoption after the workshop
- A clear team policy: what AI can touch, how it's reviewed, and who is responsible
08
How it works
- 1
Optional pre-work: IT context audit to confirm tool compatibility and environment constraints
- 2
Day 1 (remote): AI tool mastery and security/governance - live sessions with real coding exercises
- 3
Day 2 (remote): Agentic AI and team structuring - hands-on agent builds and adoption planning
- 4
Aftercare: governance framework, prompt library, team playbook, and 30-day follow-up
{ FAQ }
Frequently Asked Questions
GitHub Copilot vs. Claude Code vs. Cursor: which do you teach?
We cover the ecosystem as a whole. We focus on mastery of the tools your company uses while comparing current reasoning-capable models for complex engineering tasks.
How do we handle security and IP when generating code with AI?
We teach 'Secure-by-Design' AI coding, covering context filtering, VPC-only environments, and how to prevent secret leaks or GPL-tainted code from entering your repo.
Does this workshop cover AI agents and agentic frameworks?
Yes. Day 2 is focused on the move from 'autocomplete' to 'agentic.' We show how to build and govern agents that handle multi-step tasks from Jira to PR.
Do participants need to be senior developers?
No. The program is valuable for junior to senior levels. We focus on engineering patterns and the new 'architectural' way of thinking required for AI-assisted development.
Is this delivered on-site or remotely for engineering teams?
Both. While remote works well for distributed engineering teams, we offer on-site 2-day Intensives in France for high-bandwidth collaborative learning.
{ AI }
Ready to book this workshop?
Tell us about your team, location, and goals. We will send a tailored quote and help you plan the session.
{ AI } · Alternate formats
Markdown for LLMs and citations, PDF to share internally.