16 May 2025
by Kai Widdeson

Building a future-ready development team for the AI Age

Guest blog from Kai Widdeson, Technical Consultant at Blue Hat Associates, as part of our #SeizingTheAIOpportunity campaign week 2025.

Artificial intelligence is rapidly changing how software is built. From writing simple functions to automating tests and debugging, AI is increasing the pace and precision of development work. AI is becoming a powerful assistant that can help teams build smarter and faster - augmenting developers rather than replacing them. 

Modular functions: speed through composition 

One of the most promising uses of AI in coding is the generation of small, modular  functions. These bite-sized blocks of logic can be reviewed, tested, and assembled into larger systems. Rather than building the entire solution, AI provides developers with high quality building blocks, like well-shaped bricks, that speed up construction but still require human hands to create the full structure. 

This modular approach accelerates development without sacrificing control. It gives developers a flexible toolkit that reduces the overhead of writing boilerplate code while preserving architectural oversight. 

When AI is used in this way - as a builder of well-defined, discrete components - it becomes easier to manage code quality and reduce the risk of introducing hard-to-trace bugs. The developer remains the architect, ensuring the final product meets performance, security and design requirements. 

Debugging, testing and documentation 

AI’s pattern recognition abilities make it a handy tool for debugging. It can identify syntax issues, propose optimisations and even highlight logic flaws that might be overlooked. It helps trace runtime problems and can offer context-specific fixes that speed up resolution. 

AI can also automate test generation. By analysing code paths and predicting inputs, it  improves test coverage and helps catch issues earlier in development. This improves reliability and reduces the burden of manual testing.

Documentation is another area AI can assist. It can explain code behaviour, summarise changes, and improve project visibility. This supports maintainability, collaboration and onboarding. These forms of automation allow developers to focus on design and architecture while helping teams move faster without compromising quality. 

Challenges: control, clarity and accountability 

Despite its strengths, integrating AI into coding workflows brings important challenges. One of the biggest is explainability. Developers must still understand the code, how it  works, why it was written that way and how to adapt it in the future. Relying on AI for  complex logic can lead to code that is harder to maintain or audit. 

AI may also miss edge cases. While it handles standard code well, it may not anticipate unusual inputs or subtle conditions that a human would catch. Without careful review, these gaps can result in hard-to-detect bugs or security vulnerabilities. Another concern is design ownership. Letting AI make decisions about how features are implemented can lead to inconsistency and architectural drift. Developers need to stay in control of design direction and uphold coding standards to ensure long-term quality and cohesion. 

How can developers prepare for the AI Age? 

To make the most of AI, developers must go beyond simply knowing how to use tools. They need to assess AI-generated code critically, understand its implications, and know when human input is essential. Recognising the limits of AI is just as important as knowing how to apply it effectively.  

Understanding the reasoning behind the code remains a core responsibility. Without that insight, developers risk inheriting systems they can’t explain, maintain, or evolve. Skills like refining AI-generated documentation, spotting missed edge cases and guiding design choices will continue to be essential. 

The developers who succeed in an AI-assisted future won’t step away from the craft. They’ll stay close to the work - reviewing, shaping and maintaining code - to make sure software is not just delivered quickly, but is built to last. 


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Authors

Kai Widdeson

Kai Widdeson

Technical Consultant, Blue Hat Associates

Kai is a full stack developer. Formerly with Barclays Bank, Kai works across many of the Blue Hat projects implementing data driven solutions, AI proof of concepts, and embedded analytics with UK clients