The other day I needed to implement a feature that already had very detailed instructions and planning yet the agent gave me very low quality code riddled with naive mistakes. As I knew what should be done I discarded all the changes proposed by the agent and wrote the entire thing with the help of autocomplete in VSCode which was incredible as long as write a meaningful function names and comments it and managed to finish the entire feature in one day thanks to that and I believe that was much cheaper than all my failed attempts at agentic coding.
How do you guys yield good results from Claude Code and the likes of it?
I use the pi-mono coding agent with several different new open models running locally.
The simpler and more precise the prompt the better it works. Some examples:
"Review all golang code files in this folder. Look for refactor opportunities that make the code simpler, shorter, easier to understand and easier to maintain, while not changing the logic, correctness or functionality of the code. Do not modify any code; only describe potential refactor changes."
After it lists a bunch of potential changes, it's then enough to write "Implement finding 4. XYZ" and sometimes add "Do not make any other changes" to keep the resulting agent actions focused.
So maybe describe the problem and work first on a means to detect errors, second - then let it rip.