Coding with LLMs in the summer of 2025 – an update

Can anyone recommend a workflow / tools that accomplishes a slightly more augmented version of antirez’ workflow & suggestions minus the copy-pasting?

I am on board to agree that pure LLM + pure original full code as context is the best path at the moment, but I’d love to be able to use some shortcuts like quickly applying changes, checkpoints, etc.

My persistent (and not unfounded?) worry is that all the major tools & plugins (Cursor, Cline/Roo) all play games with their own sub-prompts and context “efficiency”.

What’s the purest solution?

Claude Code has worked well for me. It is easy to point it to the relevant parts of the codebase and see what it decides to read itself so you provide missing piece of code when necessary.

You can actually just put Cursor in manual mode and it's the same thing. You 100% manage the context and there's no agentic loop.

If your codebase fits in the context window, you can also just turn on "MAX" mode and it puts it all in the context for you.

This is almost the opposite of what OP is asking, and what the post from antirez describes.

I use Jetbrains AI assistant for its great integration with the editor and the codebase, and have been experimenting with Claude Code too. Jetbrains Assistant still has better editor integration for things like reviewing generated diffs and generating code based on currently selected code.

My augmented workflow is to “chat” with GPT because it’s free and powerful, to refine my ideas and surface things I hadn’t thought about. Then I start writing code to get in to the flow of things. I’ve found if I use the LLM straight away, I disengage, become lazy and lose context and understanding over the code. In these situations, I’ve had to redo the code more often than not. Lack of understanding is one part of why, but more importantly, disengaged prompting leads to vague and incorrect outcomes.

When I’m very clear in my head about my goal, I create a prompt either directly from my cursor, or if the changes are larger, I ask the LLM to not apply the changes but instead show them to me. I do both these things within the IDE in the chat window. I review the code and sometimes I’m happy applying it as is, other times I copy and paste it and tweak it manually.

I’ve got barebones rules set up; I haven’t felt the need to go overboard. Jetbrains Assistant does a good job of passing relevant context to the model.

I keep my prompts top-down (https://en.wikipedia.org/wiki/BLUF_(communication)) and explicit. Sometimes I’m much more detailed than others, and I’ve found that extra detail isn’t always necessary for a good result.

I'm actually building something for JetBrains, it's called https://sweep.dev. We're trying to bring next-edit prediction (like in Cursor) to JetBrains IDEs.

I use the agent panel in my editor of choice (Zed).

For each task I always start with a new (empty) context and manually tag relevant files to include (this is trivial since I know the codebase well).

First I use Claude 4 Sonnet in thinking mode (I could also use Gemini 2.5 Pro or Opus as per antirez' recommendations) to come up with a detailed plan on how to implement something (research/planning phase). I provide feedback and we iterate on the plan.

Then, in the same conversation I switch to Sonnet 4 non-thinking and tell it to implement what we just devised.

I manually review the changes and trst them. If something needs fixing or (more often) if I notice I missed some edge case/caveat, I tell it to do that (still same convo).

Commit, clear convo, next task.

For research that isn't directly tied to the code, I use ChatGPT or Claude (web apps) to brainstorm ideas, and sometimes copy/pasre these into the editor agent as starting point.

Github Copilot's Edit mode allows you to manually specify the context, and it runs only once each time to write code with diff checking, without entering a agent loop.