Your Team's AI Development Workflow, Transformed in 90 Days
A hands-on coaching program that embeds AI-centred development practices into your engineering team. Bespoke to your team. Measurable velocity gains. No fluff.
Bespoke programs tailored to your team size and skill level
The AI Adoption Gap Is Widening
Tools Without a System
Your team has Copilot licenses but no methodology. AI suggestions get accepted blindly or ignored entirely — neither moves the needle.
The Knowledge Bottleneck
One developer figures out a productive AI workflow and keeps it in their head. The rest of the team stays at tutorial-level prompting.
Resistance Disguised as Scepticism
Senior engineers dismiss AI as “not production-ready” because they've only seen it fail without proper guidance and methodology.
90 Days. Three Phases. One Transformed Team.
Foundation
- ✓Full-day kickoff & environment setup
- ✓Claude Code & Cursor workspace configuration
- ✓Requirements-first methodology introduction
- ✓First AI-assisted feature shipped
Acceleration
- ✓MCP server development for your codebase
- ✓Sub-agent orchestration patterns
- ✓Test-driven AI development workflows
- ✓Parallel execution with 10+ agents
Ownership
- ✓Internal knowledge base & documentation
- ✓Team leads coaching sessions independently
- ✓Automation & CI/CD integration
- ✓Full handover — zero ongoing dependency
1
Kickoff Day
12
Weekly Sessions
6
Fortnightly On-Sites
Four Deliverables You Can Measure
Velocity Increase
Measured before/after sprint metrics showing 3–4x throughput improvement on AI-assisted tasks.
AI Dev Environment
Every developer set up with Claude Code, Cursor, and a configured workspace tuned to your stack.
Internal MCP Server + Knowledge Base
A custom Model Context Protocol server that gives AI tools deep context about your codebase, plus internal documentation your team maintains.
Cursor Workspace Configuration
Project-specific rules, snippets, and prompt templates baked into your repo so every team member gets consistent AI assistance.
This Is What We Actually Teach
Claude Code Mastery
Terminal-first AI development. Multi-file edits, slash commands, context management, and when to use Claude Code vs Cursor.
MCP Server Development
Build custom Model Context Protocol servers that give AI tools deep access to your databases, APIs, and internal systems.
Requirements-First Methodology
Write specs before code. Structure requirements so AI can execute predictably, reducing rework from 60% to near zero.
Test-Driven AI Development
Define test cases upfront, let AI write the implementation, verify automatically. Confidence without manual review of every line.
Voice-Driven Development
Dictate requirements, architecture decisions, and code reviews. 3x faster than typing, especially for senior developers.
Knowledge Sharing Systems
CLAUDE.md files, project rules, and internal docs that make AI context portable across your entire team.
Sub-Agent Orchestration
Run 10–40+ parallel AI agents on different tasks. Plan the work, divide it, execute simultaneously, merge results.
Debug & Recovery Workflows
When AI gets stuck in loops or produces broken code: checkpoint strategies, context resets, and structured recovery.
Automation & Handover
CI/CD integration, automated testing pipelines, and the documentation practices that let your team run independently.
Plan or Execute. Never Both.
The core principle that separates productive AI development from expensive prompt-and-pray.
Define Requirements
Write a clear spec with acceptance criteria before touching any code. AI needs unambiguous instructions.
Design Architecture
Map files, interfaces, and data flow. Decide what to parallelise. This is the human thinking step.
Execute in Parallel
Launch multiple AI agents on independent tasks. Each works from the spec — no coordination overhead.
Test and Refine
Automated tests catch issues immediately. Fix with targeted prompts, not full rewrites. Ship with confidence.
Real Results, Not Hypotheticals
3–4x
Development velocity increase
Week 1
First measurable results
40+
Parallel AI agents in use
0
Ongoing dependency after 90 days
How Label-source Transformed Their Business Through Development
“We had planned a major business expansion for two years. With AI Code Coach, we implemented the right AI tools and processes to launch in just 8 weeks, completely transforming our market position.”
From 2-year roadmap to 8-week delivery. Full e-commerce platform rebuild with AI-assisted development.
A Sample 90-Day Program
Every engagement is tailored to your team's size, skill level, and goals. Here's what a typical program looks like.
Full-Day On-Site
Environment setup, team assessment, and first AI-assisted feature shipped before end of day.
12 Coaching Sessions
90-minute remote sessions covering methodology, live pairing, and code review with your actual codebase.
6 On-Site Sessions
In-person deep dives, pair programming, and hands-on workshops with the full team.
What's Included
- ✓Custom MCP server built for your codebase
- ✓Cursor workspace & project rules configuration
- ✓Internal knowledge base setup
- ✓Async Slack/Teams support between sessions
- ✓Full handover — zero ongoing dependency
What's Not Included
- ✗AI tool licence fees (Claude, Cursor, etc.)
- ✗Writing production code for you
- ✗Travel expenses for on-site visits
Every Program Is Bespoke
The structure above is a starting point. We tailor the depth, pace, and focus areas based on your team size, current skill level, and the level of involvement you need. Some teams need more on-site time; others move faster with remote-only sessions.
Book a Discovery Call to Discuss Your TeamFrequently Asked Questions
What team size does this work for?
The program is designed for teams of 2–10 developers. Larger teams can be accommodated with a tailored structure — we'll discuss this on the discovery call.
Do we need AI experience before starting?
No. The program starts from first principles. If your team can write code, they can learn this methodology. Prior AI tool usage is helpful but not required.
What if some team members are sceptical about AI?
Good — that means they have standards. Scepticism usually dissolves in the first session when developers see AI produce working, tested code on their own codebase. We've never had a holdout past week two.
Where do the on-site sessions happen?
At your office. We currently work with teams across the UK. Travel costs outside London are quoted separately if applicable.
What happens after the 90 days?
Your team runs independently. That's the entire point of month three — building internal capability so you don't need us. Optional follow-up check-ins are available but rarely needed.
Can we do a shorter engagement?
Yes. We offer 1-day intensive workshops for teams that want a taster before committing to a full program. Every engagement is scoped to fit — we'll discuss the right format on the discovery call.
How do you measure ROI?
Sprint velocity, cycle time, and deployment frequency — measured against your existing baseline from the first two weeks. Most teams see a 3–4x throughput increase on AI-assisted tasks within the first month.
Ready to Transform How Your Team Builds Software?
Fill in your details and we'll be in touch within 24 hours to schedule a discovery call.