AI-augmented development that accelerates delivery without sacrificing quality
Learn how to leverage AI effectively in your development process. Get proven AI-augmented practices for LLM integration and developer tooling, realistic guidance on when AI helps vs. hinders, and hands-on implementation support that fits your team's capability.
Every technology leader is facing the same question: how do we use AI to accelerate delivery without introducing risk, reducing quality, or creating technical debt?
The narrative around AI in software development is polarised. Either AI will replace developers entirely or it's useless hype. The reality is more nuanced. AI can genuinely accelerate certain tasks (documentation generation, risk assessment, code analysis, research and investigation) while slowing others (complex architectural decisions, novel problem-solving).
I help organisations adopt AI-augmented development practices based on real-world experience, not vendor promises. You learn where AI accelerates your delivery, where it introduces risk, and how to implement practices that fit your team's capability and context.
Evaluate your team's capability and codebase to identify high-impact opportunities for AI adoption. I assess which development tasks can be accelerated with AI, which introduce unacceptable risk, and what quality oversight practices you need to maintain standards.
Hands-on workshop demonstrating proven AI patterns in your actual codebase, primarily using Claude. Your team learns practical techniques for documentation generation, code analysis, test generation, research acceleration, and risk assessment, with realistic guidance on limitations and quality oversight.
Ongoing support as your team adopts AI-augmented practices. I provide architectural review of AI-generated code, help establish quality standards, and coach your team to develop judgment about when AI accelerates delivery vs. when it introduces risk.
Implement AI-powered documentation generation for legacy codebases or complex systems. I demonstrate tools and patterns for automated code documentation, architecture diagram generation, and policy extraction, reducing documentation burden while maintaining accuracy.
Establish practices to ensure AI-generated work meets your quality standards. I help you implement review processes, automated testing strategies, and architectural validation that catch AI mistakes before they reach production.
I help you integrate AI into your software and workflows where it genuinely adds value—LLM features, developer tooling, and productivity gains—not generic AI strategy or ML engineering.
What I focus on:
What I don't do:
I've built production systems using AI-augmented development and seen the results firsthand. A 3-month discovery process reduced to 1 week using AI-powered repository analysis. A production-ready risk assessment engine built in 3 days. Authorisation services scaffolded and refined with AI assistance, then validated through architectural review. Research tasks that would take days compressed into hours.
But I've also seen where AI fails. Research from METR shows AI makes developers 19% slower on complex, novel tasks. I know when to use AI for acceleration and when to step back and think architecturally.
My approach to AI adoption is pragmatic and evidence-based. I demonstrate proven AI-augmented patterns in your actual codebase, not toy examples. I help your team develop the judgment to know when AI helps and when it hinders. And I implement quality oversight practices that ensure AI-generated work meets your standards.
You don't need to become an AI expert to benefit from AI-augmented development. You need practical patterns, realistic expectations, and guidance from someone who's actually built production systems this way.
AI adoption consulting is right for you when:
AI adoption consulting helps you integrate AI-augmented development practices into your team's workflow safely and effectively. This includes workshop-based introduction to AI tools, guidance on where AI genuinely accelerates work (and where it doesn't), quality assurance frameworks to prevent AI-generated technical debt, and hands-on coaching for your team. My approach is practical and evidence-based, focused on real production outcomes rather than hype.
I implement structured quality controls based on research and production experience. This includes human review gates for AI-generated code, architectural oversight to catch scaling issues, test coverage requirements, and clear documentation of AI-assisted decisions. I cite METR research showing AI can be 19% slower on complex tasks when used incorrectly, so I help teams identify where AI helps (boilerplate, documentation, research compression) versus where deep human expertise is essential (architectural decisions, complex domain logic).
Real client outcomes include compressing a 3-month discovery phase to 1 week (BPP/BuildCircle), building a risk assessment engine in 3 days (Evently), and reducing research and documentation work from months to hours. I've used AI/MCP tools to analyse 390+ repositories for technical due diligence and automate legacy system documentation. These aren't theoretical benefits but proven results from production systems where quality and reliability were non-negotiable.
Not necessarily. I take an incremental, low-risk approach that integrates with your current practices. Initial adoption typically starts with documentation and research tasks, then expands to appropriate development activities once your team builds confidence. I work with your existing tools and processes, adding AI capabilities where they provide clear value. Most teams find AI adoption improves productivity without disrupting established workflows, especially when guided by someone with production experience.
Yes, with appropriate controls. AI-augmented development can work in regulated contexts when paired with proper governance, human oversight, and quality assurance. I help establish compliance-aware practices that leverage AI for efficiency while maintaining audit trails, security standards, and regulatory requirements. My experience includes financial services and education sectors where compliance and data protection are critical. The key is knowing where AI can safely assist and where human expertise is mandatory.
I work on a day rate of £800-1,000 per day for AI-augmented development services, structured as scoped project engagements or ongoing retainer arrangements. Contact me to discuss your specific AI adoption goals and receive a tailored proposal.
Working with Michael was an absolute pleasure. He was the border between the developers and the business and always managed to handle both sides' expectations and took the stress of the business on to himself to give the developers enough room to do amazing work. A great developer as well. Always a laugh, great personality, light hearted and I would definitely work with him again at a moment's notice.
Michael doesn't just tackle challenges; he approaches them with a no-nonsense attitude, cutting through complexities with a level of precision that's truly impressive. His ability to break down intricate problems and come up with elegant solutions is not only commendable but also a testament to his exceptional problem-solving skills.
Let's discuss how we can help your business.