71–80 of 123 posts
It's like people are rediscovering the most basic principles: E.g. that documentation ("prompt library") is usecho, or that well-organized code leads to higher velocity in development.
I'm interested to see where we'll land re: organizing larger codebases to accommodate agents. I've been having a lot of fun taking my larger projects and decomposing them into directed graphs where the nodes are nix flakes. If I launch claude code in a flake devshell it has access to only those tools, and it sees the flake.nix and assumes that the project is bounded by the CWD even though it's actually much larger, s…
I'm interested to see where we'll land re: organizing larger codebases to accommodate agents. I've been having a lot of fun taking my larger projects and decomposing them into directed graphs where the nodes are nix flakes. If I launch claude code in a flake devshell it has access to only those tools, and it sees the flake.nix and assumes that the project is bounded by the CWD even though it's actually much larger, s…
The focus mainly seems to be on enhancing existing workflows to produce code we currently expect - often you hear its like a junior dev.
The type of rethinking you outlined could have code organised in such a way a junior dev would never be able to extend but our 'junior dev' LLM can iterate through changes easily.
I care more about the properties of software e.g. testable, extendable, secure than how it organised.
Gets me to think of questions like
- what is the correlation between how code is organised vs its properties? - what is the optimal organisation of code to facilitate llms to modify and extend software?
Earlier quoted context omitted.
I don't do any of that. I find with GitHub copilot and Claude sonnet 4.5 if I'm clear enough about the what and where it'll sort things out pretty well, and then there's only reiteration of code styling or reuse of functionality. At that point it has enough context to keep going. The only time I might clear that whole thing is if I'm working on an entirely new feature where the context is too large and it gets stuck…
Same. I find that if I can piecemeal explain the desired functionality and work as I would pairing with another engineer that it’s totally possible to go from “make me a simple wheel with spokes” to “okay now let’s add a better frame and brakes” with relatively little planning, other than what I’d already do when researching the codebase to implement a new feature
As the models have progressively improved (able to handle more complex code bases, longer files, etc) I’ve started using this simple framework on repeat which seems to work pretty well at one shorting complex fixes or new features. [Research] ask the agent to explain current functionality as a way to load the right files into context. [Plan] ask the agent to brainstorm the best practices way to implement a new featur…
As of Dec 2025, Sonnet/Opus and GPTCodex are both trained and most good agent tools (ie. opencode, claude-code, codex) have prompts to fire off subagents during an exploration (use the word explore) and you should be able to Research without needing the extra steps of writing plans and resetting context. I'd save that expense unless you need some huge multi-step verifiable plan implemented. The biggest gotcha I found…
Sounds very functional, testable, and clean. Sign me up.
Earlier quoted context omitted.
> it seems pretty random as to when it decides to drop that out of context Overcoming this kind of nondeterministic behavior around creating/following/modifying instructions is the biggest thing I wish I could solve with my LLM workflows. It seems like you might be able to do this through a system of Claude Code hooks, but I've struggled with finding a good UX for maintaining a growing and ever-changing collection of…
Wouldn't it be great if we had some kind of deterministic language to precisely and concisely tell a computer what to do
I'm interested to see where we'll land re: organizing larger codebases to accommodate agents. I've been having a lot of fun taking my larger projects and decomposing them into directed graphs where the nodes are nix flakes. If I launch claude code in a flake devshell it has access to only those tools, and it sees the flake.nix and assumes that the project is bounded by the CWD even though it's actually much larger, s…
Earlier quoted context omitted.
As of Dec 2025, Sonnet/Opus and GPTCodex are both trained and most good agent tools (ie. opencode, claude-code, codex) have prompts to fire off subagents during an exploration (use the word explore) and you should be able to Research without needing the extra steps of writing plans and resetting context. I'd save that expense unless you need some huge multi-step verifiable plan implemented. The biggest gotcha I found…
> Instead of considering that something should be written encapsulated into an object to maintain state, it will instead write 5 functions, passing the state as parameters between each function. Sounds very functional, testable, and clean. Sign me up.
I have a user prompt saved called clean code to make a pass through the changes and remove unused, DRY and refactor - literally the high points of uncle bob's Clean Code. It works shockingly well at taking AI code and making it somewhat maintainable.
LLMs are so good at telling me about things I know little to nothing about, but when when I ask about things I have expert knowledge on they consistently fail, hallucinate, and confidently lie...