Why we chose LangGraph to build our coding agent

We’ve been building AI coding assistants at Qodo since the GPT-3 days. Our initial approach was highly structured with predefined flows for different coding tasks like test generation, code reviews, and improvements. This approach worked well with earlier generations of LLMs and with structured flows we were able to get real-world value from older models, despite all of their limitations. Since Claude Sonnet 3.5 was released 9 months ago, LLMs have become significantly more capable at general-purpose coding tasks. The new models opened up the possibility to build something more dynamic and flexible while still maintaining our standards for code quality. We wanted to move away from rigid workflows to an agent that could adapt to any kind of user request, while still reflecting our opinionated views on how AI can be best used for coding. Initially, we needed a framework that would let us quickly validate our ideas and from the few options that were available about 4 months ago, we sett ... Read full article.