Ask HN: What is your (AI) dev tech stack / workflow?
21–30 of 187 posts
Re: Ask HN: What is your (AI) dev tech stack / workflow?
#22My way is to just run a giant AI agent factory engine and make the agents full flow do everything. (plan long term, write prd, task, review).
Here's ~4000 commits in last month as an example, i have about ~10k ish including private/work stuff? https://github.com/portpowered/you-agent-factory/commits/mai...
The premise when you get to full automation generally is you go full industral engineering:
1. watch overall flow, improve process via continuous improvement
2. work via checklists and gates.
3. replace process with mechanisms as much as possible (code > agents)
4. optimal throughput is continual testing and iteration (CI, CD), coverage, full e2e tests, mock everything, general best practices really.
decent blog: https://openai.com/index/harness-engineering/
general points:
- build lots of linters
- document literally everything (arch, prd, best practices in repo)
- too many agents at the same time makes lots of code conflicts, so need to consider architecture of code how to maximize concurrency.
Re: Ask HN: What is your (AI) dev tech stack / workflow?
#23Re: Ask HN: What is your (AI) dev tech stack / workflow?
#24Re: Ask HN: What is your (AI) dev tech stack / workflow?
#25Discussion on hn: https://news.ycombinator.com/item?id=48231575
Repo: https://github.com/sermakarevich/sddw
Slides: https://docs.google.com/presentation/d/1SjKXF7hkoqyiN9-3tBGY...
Re: Ask HN: What is your (AI) dev tech stack / workflow?
#26There's lots of ways. You have to upskill through the stages IMO. Write code, write w/ agent, write w/ multi agents, write w/orchestrators. My way is to just run a giant AI agent factory engine and make the agents full flow do everything. (plan long term, write prd, task, review). Here's ~4000 commits in last month as an example, i have about ~10k ish including private/work stuff? https://github.com/portpowered/you-a…
But curious if you've found it to be a big unlock. I have been doing some of this industrial engineering myself.
Re: Ask HN: What is your (AI) dev tech stack / workflow?
#27There's lots of ways. You have to upskill through the stages IMO. Write code, write w/ agent, write w/ multi agents, write w/orchestrators. My way is to just run a giant AI agent factory engine and make the agents full flow do everything. (plan long term, write prd, task, review). Here's ~4000 commits in last month as an example, i have about ~10k ish including private/work stuff? https://github.com/portpowered/you-a…
In every project I've touched, business requirements are always the bottleneck - so I've never been able to wrap my head around what kind of requirements can be fed into a setup like this at high enough volume to justify it.
Re: Ask HN: What is your (AI) dev tech stack / workflow?
#28I am using Spec Driven Development approach implemented as a Claude Code plugin since Feb for all mid + size tasks. The idea is to write detailed specs first using agent help doing research and interviewing, decompose the task into smaller subtasks, write detailed spec for each task, implement each task separately. You can restart the session after every step in the workflow and after each subtask implementation sinc…
I'm definitely baby sitting the process more than vibe coding, and review each cycle's results. As for languages, mostly TS/JS and Rust with a bit of C# here and there depending on what I need. Claude Code's Opus does a pretty good job with Rust, so for anything personal, I've just gone with it.
Work has been limited to working out specific problems, or a small utility/library that I can pull in, but on my own system, separate from work resources.
Re: Ask HN: What is your (AI) dev tech stack / workflow?
#29I'm a bit of a fanboy, but exe.dev + their Shelley web agent is pretty great
Re: Ask HN: What is your (AI) dev tech stack / workflow?
#301) Claude Desktop which includes Claude Code for Anthropic: https://claude.com/product/claude-code (alternatively the terminal based version; either way get the subscription)
2) Codex for OpenAI: https://developers.openai.com/codex/app (same as above, subscription preferred instead of paying per token)
3) OpenCode for a variety of models: https://opencode.ai/ (they also have a subscription, but this in particular also makes it really easy to connect to OpenRouter)
4) KiloCode is essentially the above, but for VSC derived editors: https://kilo.ai/ (I personally liked RooCode more, but that got retired)
More niche tooling options:
1) Zed is pretty good, though I saw some issues with their LSP Edits and found that connecting them to OpenCode through ACP worked better, still a cool editor: https://zed.dev/
2) If you have to pay for tokens and can't get subscriptions, look at DeepSeek as a provider (V4 Pro with Max reasoning): https://api-docs.deepseek.com/quick_start/pricing
3) I'm also writing a launcher to make running Claude Code with 3rd party providers earlier, early days still: https://ccode.kronis.dev/
Note: for anyone on Windows, if you install the terminal versions of the tools (Claude Code, Codex, OpenCode, ...), you probably want them inside of WSL so there's less confusion with file paths etc. that some models have.
In regards to actually using the tech:
- version control and maybe worktrees
- sub-agents are pretty nice to have, Claude Code also introduced support for longer running workflows
- throw as much tooling as possible at the project, like Oxlint, Oxfmt etc., for Python it might be Ruff and ty or Pyright or whatever
- throw as much testing as possible at the project, maybe require certain coverage or just have CLAUDE.md that nudges the models to write and run tests
- throw as many additional scripts at the project as you want, e.g. how you want the architecture to be laid out, max file length limits etc., whatever common tools don't cover
- some tools also support LSP, use those when possible
- pretty much all models will still output slop, though making fresh instances (even of the same model) review its output, e.g. 3 parallel sub-agents looking for critical/serious issues works pretty well, I just have a review loop that I make the models run before commits
- ideally you'd also test local instances of whatever you build (e.g. real PostgreSQL instance etc.), just so the dev loops are tighter and faster