Birgitta Böckeler, Global Lead for AI-assisted software delivery at Thoughtworks, discusses the latest advances in large language models and how they are revolutionizing software development. Topics include the applications of AI in software delivery, the role of generative AI and large language models in code generation, the value of an AI assistant in software development, and the potential applications and limitations of AI in software development tasks.
AI-assisted software delivery streamlines development, reduces errors, and saves time and costs.
Large language models are effective in generating code, translating natural language, and assisting developers.
Concerns about data confidentiality and the effectiveness of LLMs in infrastructure as code should be considered.
Deep dives
AI-assisted software delivery
AI-assisted software delivery refers to using artificial intelligence to enhance various phases of the software development lifecycle. It streamlines software delivery, reduces errors, and decreases time and costs. Advance in large language models is transforming software development.
Code generation and AI
Large language models are good at pattern recognition and can translate natural language into code. They are helpful for generating code from comments or requirements, as well as migrating code between languages or systems.
The role of LLMs in software delivery
LLMs are useful for coding assistance, providing suggestions as developers write code. They can also assist in writing tests by generating test code and data. However, their effectiveness may vary depending on the complexity of the code and the developer's experience.
Concerns about LLMs
There are concerns about data confidentiality when using LLMs. While some tools discard data immediately and do not reuse it for training, it's important to review the tool provider's terms and conditions to ensure trust. Issues such as code secrets and licensing should be considered.
Applying LLMs to deployment
LLMs can assist with infrastructure as code, but there are varying opinions on their effectiveness. Deterministic automation and repeatability are still important in deployment. LLMs may find more use in areas like exploratory testing and simulated agent environments.
AI-assisted software delivery refers to the utilization of artificial intelligence to assist, enhance, or automate various phases of the software development lifecycle. AI can be used in numerous aspects of software development, from requirements gathering to code generation to testing and monitoring. The overarching aim is to streamline software delivery, reduce errors and, ideally, reduce the time and costs associated with software development.
Birgitta Böckeler is the Global Lead for AI-assisted Software Delivery at Thoughtworks and she joins us in this episode. We discuss how the latest advances in large language models are revolutionizing software development.
Jordi Mon Companys is a product manager and marketer that specializes in software delivery, developer experience, cloud native and open source. He has developed his career at companies like GitLab, Weaveworks, Harness and other platform and devtool providers. His interests range from software supply chain security to open source innovation. You can reach out to him on Twitter at @jordimonpmm.