At the recent QCon London conference, Mathew Lodge, CEO of DiffBlue, gave a presentation on the advancements in artificial intelligence (AI) for writing code. Lodge highlighted the differences between Large Language Models and Reinforcement Learning approaches, emphasizing what both approaches can and can't do. The session gave an overview of the state of the current state of AI-powered code generation and its future trajectory. In his presentation, Lodge delved into the differences between AI-powered code generation tools and unit test writing tools. Code generation tools like GitHub Copilot, TabNine, and ChatGPT primarily focus on completing code snippets or suggesting code based on the context provided.

Developers are critically important to every business, and they're not cheap. According to the Bureau of Labor Statistics, the median annual salary for a software developer in the US is close to $110,000. In San Francisco, it's closer to $145,000, where entry-level developers can command $100,000. Meanwhile, developer tools are typically priced using the size of development team (seats) as a proxy. Production platforms, on the other hand, are typically charged by the size of the environment.