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Ask HN: What is your (AI) dev tech stack / workflow?

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Re: Ask HN: What is your (AI) dev tech stack / workflow?

#91

I'm using VSCode with Github Copilot (Business) in Agent, and Ask mode with varying LLMs, depending on the complexity of the task. For a specific task, i create a markdown file with the requirements in tandem with the Agent, manually edit it where convenient. And then i let the Agent implement one feature or work unit after another, while micro managing it and making sure that i understand what it has written (not fo…

You aren't the only one. There are many people using Github Copilot. Github Copilot CLI is for automation. For example, in a Rust project, I use it to audit for security, documentation gaps, and test issues crate by crate. This can take an hour and I look at the suggested stories it writes afterwards to triage for implementation.

And does Copilot CLI make that more convenient than letting the Copilot Plugin in Agent mode do it? Maybe because of swarms of agents?

Re: Ask HN: What is your (AI) dev tech stack / workflow?

#92

Don't want to jeopardize this awesome chat about tools but for AI workshops I think these visual cards I came across could be an amazing way to handout. They cover all LLM concepts and explained visually. Found very useful to revise LLM concepts before AI research scientist/AI engineer interviews. https://github.com/llmsresearch/llm-flashcards

"these visual cards I came across" You came across them in your own repo and company that sells them?

Thanks for spotting it but if I tried other way would have kicked out, it was a genuine try to help but thanks @mellosouls I can understand.

Re: Ask HN: What is your (AI) dev tech stack / workflow?

#93
Assuming you have a SOTA model - the thing I'd teach them is minimalism.

- Minimal tooling - Minimal system prompt - Folders + files + text

AI driven development has turned the whole development job into knowing what questions to ask + complexity reduction.

First ask the model how to do something / what options there are to do something - not just to do something. Creating moments to teach that is a challenge in itself.

After its answered go tell it to do the thing.

If they're serious though, the next step is to teach them to always ask if there is a simpler alternative with fewer dependencies.

Anything with a too magical UI is going to give them the wrong 'model' in their mind on how to think about the tool.

A bit of a hidden aspect many people seem to miss, the tone you take with the model is absolutely critical. Ask a bunch of psychology questions before having it write javascript or propose a tech stack is going to get you different results.

Finally, the semi obvious hack (and which something like claude will do automatically when in team mode) - have the model talk to another instance of itself. The model can translate your ramblings into coherent specs in the right tone and feeding that back into itself in a new session gets you the good results. Its also part of why the "first write a plan" works because it fills the context with the right tone and clear instructions.

Re: Ask HN: What is your (AI) dev tech stack / workflow?

#94
Tldr; just teach them to talk to Codex and show Pi to ambitious ones.

Raw Codex, both app and cli. On windows 11 which is horrible (sometimes in WSL, which sometimes crashes for no reason when I copy a lot of data around and somehow reverts contents of a mounted vhd virtual drive to previous state from long ago, after a crash). I'd love to switch to linux but I'm an avid gamer. I installed a linux on my old box though and some of my AI jobs run there. GPU there is two generations back but it still has 24GB of VRAM.

Bare Pi if I have a cool idea on how to extend the harness. I don't use any skill in Codex but I ask to create some for Pi to go with the extension for Pi I am building at any given moment.

I used to have a kanban skill for Codex (and others) to build large amount of features afk in a spec driven development manner, but recently Codex is doing fine without it. And the last time I used kanban it built diligently a completely wrong thing that I, it turned out, underspecified.

Zed if I'm really inclined to view any files. But basically it's my text file viewer because it's marginally faster than the modern Notepad.

About 5 different web browsers, because they all suck. All crammed with tabs going back months.

Language, whatever. I bounce around between Python, Rust, C#, TypeScript. Maybe I should try something exotic.

Gpt-5.5 xtra high, Glm-5.1 (not recently because it's not as good, I used to like Kilocode with it, in previous major version 5(?), most recent Kilocode is streamlined into mediocrity, although you can still intall old version). Gemma4 on local ollama for specific non-coding tasks. Openai api proxy connected to my Codex sub, for cases where Gemma4 doesn't do that well.

I'm having immense fun by making programs for ad hoc tasks like transcribing a conversation I had this morning in a language I barely know. Or extending my old program that searches proofs in domain of axiomtic logic. Or adding feature to a charting "app" I built few years ago I was too lazy to add back then. Those 3 I did just today.

I can conclude that Gpt-5.5 is a better developer than I ever was or even could ever be (in all aspects) after being a programmer for two decades and being considered pretty good by my peers.

When I need a prompt for something, I ask codex to write it. If results are unsatisfactory I ask it to tweak it. It works very well.

I do image generation with chatgpt-image-2 although I think I'll need to build some tooling around it at some point, like a basic photoshop, mostly LLM controlled. The model itself is not good in basic composing and keeping track of different versions of the same sub-image

Sometimes I go to chat.com and ask for deep research on some subject an put the result in my project dir for Codex to find and learn from.

I don't use skills or MCPs. I always --yolo.

I release nothing. Even if I build something that might have wider appeal, I firmly believe that anyone could build it as well. And effort needed to find what I built and check if it fits somebody's need exceeds the effort they would need to extend to build it themselves exaclty as they want it. That's my experience. Human accessible internet, including Google is 50% dead for me already. I delegate the drudgery of browsing it to Codex or chat.

All I do is mostly for my own amusement. I have as much fun with it as with playing games. Possibly even more.

Re: Ask HN: What is your (AI) dev tech stack / workflow?

#96

Ghostty with Claude Code. That's pretty much it. For each new feature, I open a worktree, spar with Claude to work up a gherkin spec with @todo on each story. Each agent pushes commits to a WIP PR in GitHub where I review and leave comments or questions. Once the spec is done we mainly interact on the PR. @todo becomes @wip and @done as the agent progresses. I really like gherkin for agentic engineering, it's very cl…

same

Re: Ask HN: What is your (AI) dev tech stack / workflow?

#97
I've dabbled a bit in GitHub Copilot using Claude Opus and Sonnet models via work, but I couldn't shake the thought that we weren't allowed to use this on any of our clients' codebases. Having been a fan of Ollama, I wanted to try something truly local.

First I tried OpenCode but they unexpectedly make external requests (!) even when using Ollama (I noticed when Ollama wasn't properly connected and I still got a title generated).

So I settled for Pi, but I strongly disliked the idea that the agent could, at any point, decide to delete files or exfiltrate .env secrets. So I created Picosa (https://github.com/GreenpantsDeveloper/Picosa), containerizing and sandboxing Pi, with firewall rules such that it could only ever reach the local network (for Ollama), scoped by just the current working directory, and nothing else. Combined with Qwen3.6:35b, it works surprisingly well, and I could ask it to improve itself when run on its own repository.

Re: Ask HN: What is your (AI) dev tech stack / workflow?

#98

I 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…

Genuine question, I'm trying to adopt specs and AI DLC in my team so we can use it as an enhancement and improve our development and the biggest pain right now for us is managing all those md artifacts.

I'm curious how do you manage them? Do you preserve them for the future or delete as soon as task was accomplished? If you're deleting those artifacts after job being done - do you summarize those specs into the Jira ticket or whatever system you use.

Re: Ask HN: What is your (AI) dev tech stack / workflow?

#99
My workflow for production code:

1. Pick the most complete project boilerplate (fullstack JS can easily introduce security bugs, SPA + API is best as cheap linting solves most problems)

2. Project skills (how to CRUD without mess)

3. Use worktrees for concurrent features, local session for conflicts

4. Local session for QA and refinement

I use Copilot and GPT 5.4

Managed to shorten pre-AI priced ongoing projects to 2 weeks or a month

Re: Ask HN: What is your (AI) dev tech stack / workflow?

#100
I use PI ( https://pi.dev ) and ( https://hermes-agent.nousresearch.com/ ) as the main drivers together with deepseek-v4-pro as the main model (~10M/day tokens overall there).

Hermes basically rules my personal life at this point - it is a _very_ useful personal assistant.

I also use it at work (integrated at Slack) and at this point it answers most of both my emails and slack messages (I calibrated https://github.com/blader/humanizer with a large corpus of my own voice to make it less annoying for the others). My routine now involving walking in circles while exchanging messages with hermes directing it how to answer this or that... Hermes uses an llm-wiki ( https://gist.github.com/karpathy/442a6bf555914893e9891c11519... ) as a source of information when drafting suggested replies - I have a cronjob that feeds it all emails, slack messages, meeting minutes every single day.

Claude Code with Opus 4.6 for multimodal/vision, design and writing tasks ("Create a crisp memo from this meeting transcription" is a prompt that will bring great results with either Opus 4.6 or GLM-5.1) - very recently I started to use https://github.com/anomalyco/opencode occasionally with opus models too (I am forcing myself a little bit because it is hard to help people with a tool you are unfamiliar with).

For building software automatically I currently use one of the harness above for for launching https://tamandua-tetradactyla.nfshost.com/ feature-dev-merge-worktree runs (it provides workflows on top of PI+deepseek).

Where it comes from: until recently I used https://steve-yegge.medium.com/welcome-to-gas-town-4f25ee16d... for automatic software building but while planning an AI bootcamp I concluded that teaching Gas Town along with everything else would be impossible (too hard/complex), and decided to teach https://github.com/snarktank/antfarm instead but did not want to add OpenClaw as one more dependency - so I built Tamandua ( https://github.com/igorhvr/tamandua ) and I ended up using it all the time! I now every single day before going to sleep launch a couple of runs and it is very cool waking up to see them done.

For autoresearch-like, optimization, and other tasks with a very clear measurable goal (such as increasing test coverage, changing things from one programming language to another, etc) I use https://github.com/davebcn87/pi-autoresearch (100% of the time on top of deepseek-v4-pro).

For debugging or very hard problems I use codex w/ GPT5.5. I don´t like its personality (lazy) but I do think it is smartest model available. As evidence, here is a commit of a problem where I tried Opus 4.8, Deepseek-v4-pro and a couple of other models and they all failed to understand what the bug was: https://github.com/NousResearch/hermes-agent/pull/38198/chan... - once the bug was found within codex I launched from it a tamandua bug-fix-merge-worktree run on top of deepseek-v4-pro that created the commit itself...

As a web application I use OpenWebUI and I am specially fond of the notes feature ( https://docs.openwebui.com/features/notes/ ) which I did not find anywhere else.

Last but not least, I love playing with local models. https://huggingface.co/Qwen/Qwen3-Coder-480B-A35B-Instruct is my current favorite for coding and deepseek-r1 for general tasks. I also started yesterday testing https://github.com/antirez/ds4 - it works _very_ well from what I could see so far.

What comes next? Trying to figure out what is the "deepseek-v4-pro of multimodal" model (frontier performance, efficient/comparatively cheap to run, support for image/audio/video/etc). Currently using kimi-k2.6, will test Minimax M3 soon.

Ah, almost forgot: https://huggingface.co/microsoft/VibeVoice-ASR will give you AMAZINGLY good meeting transcriptions (my hermes vibecoded a program to use it). Seriously, night and day difference from what the big players provide natively in their platforms. Have 8 people talking in 3 different languages? No problem - you will need a bit of patience and beefy hardware, only..

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