> But the key is not jumping straight into code generation. That's a bingo! My workflow is to attach my entire codebase (or just the src folder + auxiliary fi

> But the key is not jumping straight into code generation. That's a bingo! My workflow is to attach my entire codebase (or just the src folder + auxiliary files like sql schemas) to a Gemini 2.5 pro chat and ask it to write an implementation plan in phases for whatever feature I need, along with a list of assumptions, types, function signatures, documentation, and tests. I then spend a few minutes iterating to make sure it uses the right libraries, patterns, and endpoints. I copy paste the plan into plan.md and instruct Cursor/Windsurf/Aider/etc to implement phase 1 of the plan, saving implementation notes to plan-notes.md (both markdown files are explicitly included in the context). Keep telling it to "continue" and "keep going with the next phase" as needed. The implementation notes keep the LLM "grounded" in each step and allows creating a new chat context when it grows too long or messes up, requiring a git reset. The alternative first step - when I'm working on an isolated module that doesn't need to know about the rest of the codebase but is otherwise quite complicated - is to have Gemini Deep Research write a report about how to implement that feature and feed that report into the planner. The other important part is what I call "self reflection." Give the plan or research report to an LLM and ask it about improvements, pitfalls, tradeoffs, etc. and incorporate that feedback back into the plan. It helps to mix them up, so i.e. Claude and GPT review a Gemini plan and vice versa.