AI for Software Development Teams

Navigate AI adoption without breaking what works

Every engineering team is wrestling with the same questions: Which AI tools actually deliver? How do we adopt them without disrupting proven workflows? And if we're building products, how do we add AI features that users actually want?

The AI landscape moves fast, but thoughtful adoption beats rushed implementation every time. We help engineering teams and product companies navigate AI strategically—from developer tooling to user-facing features.

The Current State of Play

Developer tooling is fragmented

GitHub Copilot, Claude Code, Cursor, Windsurf—the options multiply faster than your bandwidth to evaluate them properly. Half your team swears by one tool, others are experimenting, and some are sticking with proven workflows.

Product pressure is mounting

"We need AI in our product" has become the weekly refrain. But most attempts land you with a chatbot shoved in the corner or features that feel bolted-on rather than genuinely useful.

Team dynamics are shifting

AI adoption raises legitimate questions about code quality, dependency on external services, and long-term skill development. Some developers are enthusiastic, others are sceptical, and most teams haven't figured out consistent practices.

Ethics and governance matter

Using AI tools for development raises questions about IP, security, and data protection. Building AI-powered features adds layers of complexity around bias, reliability, and user trust.

All valid concerns. The key isn't adopting everything—it's adopting the right things in the right way, with your team aligned on the approach.

Our Perspective

We've spent significant time with the major AI tools (and plenty of minor ones) across different codebases, development contexts, and product implementations. We know what works, what doesn't, and crucially, what the gotchas are that vendor demos don't mention.

More importantly, we understand that successful AI adoption isn't just about the technology—it's about people, processes, and culture. The best AI implementation in the world fails if your team isn't aligned on how and why to use it.

Our approach spans:

Developer productivity

Finding AI coding tools that genuinely accelerate your workflow

Product development

Building AI features that solve real user problems rather than following trends

Team alignment

Getting everyone on the same page about AI adoption and usage

Ethics and governance

Navigating AI responsibly whilst avoiding decision paralysis

Quality maintenance

Ensuring AI enhances rather than undermines your engineering standards

Common Areas We Work On

AI Developer Tooling

Which tools actually work with your stack? How do you configure them for your codebase patterns? What's the real productivity impact—we've seen 30% velocity gains for teams that get this right. How do you maintain code quality when AI is generating significant portions of code?

AI-Powered Product Features

Moving beyond basic chatbots to features that genuinely enhance user experience. Starting with user problems rather than cool technology. Building AI capabilities that feel native to your product rather than bolted-on.

Team Culture and Adoption

Getting your team aligned on AI usage—addressing concerns, building shared practices, and ensuring consistent approaches across different experience levels and preferences.

Ethics and Governance

Working through the legitimate concerns about AI adoption—from security and IP considerations to environmental impact and job displacement. Finding pragmatic approaches that align with your values without creating decision paralysis.

Change Management

Rolling out AI tools and practices in ways that enhance team cohesion rather than creating divisions. Training approaches that focus on consistent, effective usage rather than hype-driven experimentation. Building confidence in AI usage whilst maintaining the architectural thinking and code quality standards that matter.

How We Work

Every team's context is different—your stack, your users, your constraints, your culture. We start with understanding your specific situation rather than applying generic frameworks.

Depending on what you need, we might work together on:

  • AI Opportunity Assessment - Comprehensive evaluation of AI potential across your development workflow and product strategy
  • AI Ethics Workshop - Structured dialogue to work through AI concerns and build team alignment
  • AI Product Development - Guidance on building AI features that users actually value
  • Developer tooling evaluation - Hands-on testing of AI coding tools against your actual codebase
  • Team training and adoption - Getting your developers productive with AI tools quickly and consistently
  • Governance and policy development - Building practical guidelines for AI usage that align with your values

We're transparent about costs and scope before any engagement begins.

The Result

An engineering team that uses AI confidently and strategically—whether that's accelerating development with the right tools, building AI features that genuinely enhance your product, or navigating the cultural challenges of AI adoption.

You'll have practical experience with cutting-edge capabilities without the disruption that comes from unfocused experimentation. Most importantly, you'll transform AI from a source of uncertainty into a reliable part of your technical strategy.

Ready to Start?

Whether you're looking to adopt AI tools strategically or navigate the cultural challenges of AI implementation, let's have a conversation about what's possible for your engineering team.

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Flexible with timezones, based in Western Europe