Beyond the Chatbot: Unlocking the Next Phase of AI Developer Tools

Developers are turning to AI coding tools as a lifeline, as a result of their ever-increasing workloads. In fact, 41% of developers believe AI coding tools can help prevent burnout, highlighting their value in easing the daily pressures developers face. Yet, while there are many AI-powered tools available, chatbots remain the most popular, providing near-instant support for tasks like writing scripts or finding bugs.

However, the reliance on a single AI use case is limiting developers' ability to leverage the technology to its full potential. Opportunities for greater efficiency, automation, and creativity are not yet fully realised within the developer community.

In some cases, developers are holding themselves back. Despite being creative problem-solvers and always looking for new ways to work, many developers remain cautious about AI – from how it works, to the reliability of its output. In fact, 66% of developers don’t trust the output or answers provided by AI tools. Until they see clear, productive, and safe examples of AI in action, many professionals are waiting to commit. Once these barriers are addressed, developers are likely to lead a wave of productivity.

To move the needle on AI adoption, organisations must take an active role in enabling developers. IT and business leaders should first define what the ideal AI developer tool looks like by focussing on the key features and functionalities that truly empower developers. AI tools have the potential to improve productivity, automate tasks, and unlock greater creativity. So where do business leaders start with this journey to maximising their developer talent with AI?

Meeting developer expectations

Organisations clearly recognise the benefits AI offers in boosting developer productivity. Almost three-quarters of CIOs say their organisations are increasing their investment in AI tools to help developers work more effectively and accelerate the creation of GenAI applications.

Still, developers are wary of AI tools, and for good reason. While large language models (LLMs) can be transformational for some AI services, they can also lack detailed or domain-specific knowledge. This means there’s a risk AI can give inaccurate, misleading results or hallucinate. For developers, this could result in unreliable code embedded into applications. Such problems can severely impact the quality of the applications that developers build for end users, creating user experience issues as well as reputational and financial damage to the organisation.

One way organisations can address these issues is by drawing on small language models (SLMs). Unlike LLMs, SLMs are purpose-built for specific tasks, meaning the output can be more accurate and reliable. With a reduced risk of hallucinations or false outputs, SLM powered AI services can help to alleviate developer concerns, allowing them to benefit from the productivity benefits that AI tools can deliver. SLMs are also easier to run on a local machine, and as such would address CIO concerns around data leaks.

The trend is already underway. YouTube is full of videos explaining to developers how to get the most out of a SelfHosted DeepSeek mode with their favorite AI enabled IDE. We’re still in the early stages of AI adoption in software development; there will be more transformation, more efficiency gains, and more new hardware to support that.

Balancing AI reliance and developer growth

While AI offers endless opportunities for software development and engineering functions, there’s a risk developers may become overly reliant on these tools. This is particularly the case for junior developers, who are learning the ropes in an age where AI is becoming deeply integrated into software development. An over-dependence on using AI copilot tools, like heavily leaning on them to check or complete work, could create a significant skills gap between junior developers and their more experienced colleagues.

Senior developers, having worked in the industry prior to the AI boom, are able to assess the accuracy of AI-generated suggestions, identify hallucinations, and effectively re-prompt AI to achieve better results. Their knowledge and experience equips them with the necessary skills to know when AI responses need to be corrected. However, junior developers may find it difficult to understand the reasoning behind an AI-generated solution or to recognise hallucinations, due to their limited experience, which can result in unnoticed errors slipping through.

To address this challenge before it becomes a major problem, organisations must give junior developers the room to build their skills without becoming overly dependent on AI tools. A proactive approach, such as investing in education and training, will be essential to bridging the gap. AI itself can play a pivotal role in this process by offering immersive, real-time learning experiences that guide developers through coding processes and enhance their skills on the job. In this way, the true value of AI does not exclusively lie in generating new content, but in helping developers build a solid foundation of knowledge and expertise by providing support and learning opportunities.

Empowering developers for the future

AI offers a huge opportunity to enhance the productivity and creativity of developers, but its effectiveness hinges on organisations addressing key challenges. To unlock AI’s full potential, organisations must design or deploy tools that align with developers' expectations, prioritising ease of use, familiarity, integration, and trustworthiness.

At the same time, it's important to strike a balance between leveraging AI’s capabilities and nurturing developer growth, particularly among junior developers. Rather than becoming overly dependent on AI, developers should be supported with continuous learning opportunities that help them develop the critical skills to assess and leverage AI effectively. By keeping developer’s preferences and growth in mind, AI can empower them without undermining their expertise and drive innovation.