GenAI for Engineering Teams
A hands-on half-day workshop that takes engineering teams from understanding the AI-assisted development landscape through to agentic coding, quality guardrails, and plan-driven workflows. Your team leaves with practical skills and concrete actions they can apply on Monday.
Learning Objectives
What your team will understand and be able to do after the workshop
The Evolution of AI-Assisted Development +
Understand the spectrum from code completions through chat-based coding to fully agentic workflows. See live demos of each approach so your team can calibrate where they are and where the field is heading.
Agentic Coding in Practice +
Move beyond copy-paste prompting. Learn what it means for an AI agent to plan, execute, and iterate on code autonomously, and build hands-on experience with agentic coding tools.
Quality Guardrails for AI-Assisted Code +
Common failure patterns when working with GenAI, and three practical guardrails your team can adopt immediately: rules-based constraints, plan-driven development, and AI-assisted code review.
Plan-Driven Development +
How to direct AI agents with clear plans, test-first thinking, and structured workflows. Move from "vibe coding" to repeatable, reviewable engineering processes.
AI-Assisted Code Review +
Techniques for using AI self-critique alongside human review. Learn to spot agent deflection patterns and build review workflows that catch what humans miss and what AI misses.
When GenAI Is (and Isn't) the Right Tool +
Honest assessment of current capabilities and limitations. Where GenAI accelerates engineering work today, and where the hype outpaces reality.
The Experience
Designed for how engineers actually learn
Collaborative, Not Lecture-Based
Team exercises, pair work, and structured reflection. Your team learns together and leaves with shared understanding and agreed actions.
Concept-Practice-Reflect
Every concept is followed by hands-on practice and team reflection. No death by slides.
Tailored to Your Team
We start with your team's learning objectives and adapt the emphasis accordingly. The core curriculum stays the same, but the depth shifts to what matters most to you.
The Programme
Context & Capability
- The evolution of AI-assisted development
- Live demos: completions, chat coding, agentic coding
- Hands-on: vibe coding exercise with team checkpoints
- What makes agentic coding Fast, Autonomous, Ambitious, Fun, and full of Optionality
Quality & Control
- Common failure patterns in AI-assisted code
- Three guardrails: rules, plans, and review
- Hands-on: writing effective AGENTS.md and project rules
- Plan-driven development and test-first workflows
Review & Action
- AI self-critique and agent deflection patterns
- Team swap code review exercise
- Individual reflection and team action planning
- Concrete next steps for your engineering workflow
What You Walk Away With
- Clear mental model of the AI-assisted development spectrum
- Hands-on experience with agentic coding tools
- Three quality guardrails you can adopt in your team on Monday
- A plan-driven workflow for directing AI agents effectively
- Techniques for AI-assisted code review alongside human review
- Concrete team actions agreed during the workshop
Who It's For
- Software engineers and developers
- Senior developers and tech leads
- Engineering managers
- Platform and DevOps engineers
- Teams adopting AI-assisted development
The Agentic Engineering Singularity
New models like Opus 4.6 and Codex 5.3 have fundamentally changed what engineering teams can build with AI agents. Our 2026 curriculum reflects this shift, with deep hands-on coverage of the tools and patterns that matter now.
Introducing Claude Code
- ▸ Skills — extend Claude Code with reusable, shareable capability modules
- ▸ Subagents — spawn focused child agents for parallel, scoped work
- ▸ Task Management — structured workflows with plan-driven agent execution
- ▸ Agent Teams — coordinating multiple agents across a single project
Agent SDKs & Ecosystem
- ▸ Claude Agent SDK — build production agents in TypeScript and Python
- ▸ OpenAI Codex — comparing approaches across the agentic ecosystem
- ▸ MCP Servers — connecting agents to your tools, APIs, and data
- ▸ Model Selection — when to use Opus 4.6, Codex 5.3, Sonnet, or Haiku
The Rise of Multi-Agent Orchestrators
Orchestrating teams of specialised agents, each with their own tools, context, and goals. We are developing hands-on curriculum for building, testing, and operating multi-agent systems in production engineering workflows.
Ready to Upskill Your Engineering Team?
We tailor each workshop to your team's stack, domain, and goals. Half a day is all it takes to build real GenAI confidence. Let's talk about what your team needs.
Frequently Asked Questions
Do we need prior AI or LLM experience? +
No. The workshop is designed for experienced engineers at any point on the AI-assisted development spectrum, from those just getting started to those already experimenting with agentic tools. We meet your team where they are.
What tools do we need installed? +
We provide setup instructions before the workshop so your team is ready to go on the day. We use agentic coding tools for hands-on exercises. All you need is a laptop with a terminal.
Can we customise the programme for our team? +
Yes. We start by understanding your team's learning objectives and adapt the emphasis accordingly. The core curriculum stays the same, but the depth and focus shifts to what matters most to your team.
Why half a day instead of a full day? +
Half a day is enough to build real understanding and hands-on confidence without losing momentum. Every concept is followed by practice and reflection. Teams leave with practical skills and concrete team actions they can apply immediately.
Is this a lecture or is it interactive? +
Highly interactive. The workshop follows a concept-practice-reflect structure with team exercises, collaborative coding, peer review, and structured reflection throughout. No death by slides.