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superze | 2 months ago
I repeatedly rewrite prompts, restate the same constraints, and write detailed acceptance criteria, yet still end up with broken or non-functional code.its very frustrating to say the least Yesterday alone I spent about $200 on generations that now require significant manual rewrites just to make them work.
At that point, the gains are questionable. My biggest success is having the model take over the first Design in my app and I take it from there, but those hundred lines if not thousand lines of code it generates are so Messi, it's insanely painful to refactor the mess afterwards
throwatdem12311|2 months ago
It's so frustrating, it regularly makes me want to just quit the profession. Which is why I still just write most code by hand.
data-ottawa|2 months ago
Instead of stuffing the context with DDL I suggest:
1. Reorganize your data warehouse. It needs to be easy to find the correct data. Make sure you use ELT clear layers, meaningful schemas, and have per-model documentation. This is a ton of work, but if done right the payoff is massive.
2. I built a tool for myself to pull our warehouse into a graph for fuzzy search+dependency chain analysis. In the spring I made an MCP server for it and Claude uses that tool incredibly well for almost all queries. I haven't actually used the GUI or scripts since I built the MCP.
Claude and Devstral are the best models I've used for SQL. I cannot get Gemini to write decent modern sql -- even the Gemini data science/engineer agents in Google Cloud. I occasionally try the paid models through the API and still haven't been impressed.
deadbabe|2 months ago
SkyPuncher|2 months ago
It’s _always_ easier to add more code than it is to fix broken code.
nowittyusername|2 months ago
mirsadm|2 months ago
krior|2 months ago
shepherdjerred|2 months ago
I use Claude Code and Cursor. What I do:
- use statically typed languages: TypeScript, Go, Rust, Python w/ types
- Setup linters. For TS I have a bunch of custom lint rules (authored by AI) for common feedback that I've given. (https://github.com/shepherdjerred/monorepo/tree/main/package...)
- For Cursor, lots of feedback on my desired style. https://github.com/shepherdjerred/scout-for-lol/tree/main/.c...
- Heavy usage of plan mode. Tell AI something like "make at least 20 searches to online documentation", support every claim with a reference, etc. Tell AI "make a task for every little thing you'll implement"
- Have the AI write tests, particularly the more expensive ones like integration and end-to-end, so you have an easy way to verify functionality.
- Setup Claude Code GHA to automatically review PRs. Give the review feedback to the agent that implemented it, either via copy-pasting or tell the agent "fetch review comments and fix them".
Some examples of what I've made:
- Many features for https://scout-for-lol.com/, a League of Legends bot for Discord
- A program to generate TypeScript types for Helm charts (https://github.com/shepherdjerred/homelab/tree/main/src/helm...)
- A program to summarize all of the dependency updates for my Homelab (https://github.com/shepherdjerred/homelab/tree/main/src/deps...)
- A program to manage multiple instances of CLI agents like Claude Code (https://github.com/shepherdjerred/monorepo/tree/main/package...)
- A Discord AI bot in the style of my friends (https://github.com/shepherdjerred/monorepo/tree/main/package...)
moffkalast|2 months ago
Lol sometimes I have to spend two turns convincing Claude to use its goddamn search and look up the damn doc instead of trying to shoot from the hip for the fifth time. ChatGPT at least has forced search mode.
throw2312321|2 months ago
BhavdeepSethi|2 months ago
miguel_martin|2 months ago
tmaly|2 months ago
falcor84|2 months ago
jefffoster|2 months ago
It’s very easy to spend $100s per dev per day.
christophilus|2 months ago
unknown|2 months ago
[deleted]
cloudflare728|2 months ago
Yeah the pain of cleaning up small mess is great too. I had some tests failing and type failing issues, I thought I will fix it later by only using AI prompt. As the size was growing, failing Typescript issues was growing too. At some point it was 5000+ type issues and countless number of failing unit tests. Then more and more. I tried to fix with AI, since it was not possible fixing old way. Then I discarded the whole project when it was around 500k lines of code.
pca006132|2 months ago