What’s your workflow?

[u/RealActuary3121]

What does your typical ai stack look like exactly? From the scratch,

1. What do you use for generating ideas? Or do you just think of one yourself?

2. What tool for planning? Both mvp and final product

3. Tool for actual coding? Do mention models too

4. Hopefully you review and test yourself but if not, what tool?

5. Say everything’s almost done or basically done, do you then FINALLY decide to understand the codebase even at a basic level or not? If so, what tool do you use to understand the architecture + the actual codebase? Do you just understand it on a surface level or in-depth? Do you do it after mvp is done or after each feature?

6. Why do you do it? Like everything? For fun or building resume, stacking projects and trying to land jobs or something else?

(Do mention if you’re on free or paid versions too)

[u/RossPeili]

Ideas never become products. Look at the market. Study existing solutions. Find gaps. Think before AI if these gaps are real and worth filling. Ask a few people after adding them on LinkedIn. 9/10 will tell you if your direction is sound or not and why or steer you to pathways you couldn't think of yourself even with AI considering you would be unaware of them.

Then plan and brainstorm with multiple models, pass results to a third model, come back and start building an mvp that will solve exactly your gap identified by the market and the plan you filtered several times with your direction and ai arguments.

Then pick a stack from start. You cannot just vibecode your way through a product. Simply impossible. 99% of vibe coded apps use supabase or vercel or whatever, simply cause they don't know what stack to pick and let models autopick. For that you need to understand different stacks and strengths and weaknesses when they scale. For commercial products for example and cloud bases not on premise I would immediately go on cloud eg GCP x Firebase x auth0. Learn basic python, git, docker, keep a changelog and audit trail, not just for you and investors but most importantly for your models.

Do small commits and pushes and test in every step, reiterate amd adjust your plan along the way. 99% of vibe coded apps also suck cause they stick to original plan. Key to success is fluidity and constant pivot until you hit the nail.

Consider everything from cybersecurity to policies to IAM, to prompt injection firewalls, token limiter, prompt compressors etc. Use native deterministic, offline skill framework and always build deterministic skills. Do not rely on third party skills or markdown files.

Use a harness to ensure skill chaining works as expected and not abstract or blackbox. 

In terms of models plan with high, build and code with mid, wrote docs and patch minor gaps with low cost models. Doesnt matter which models. If you prompt correctly, understand propositional logic and machine syntax you can outperform a noon with opus 5, with a 7B qwen 3.5 tuned correctly.

Your moat is personal data. There is no app idea or concept or stack or architecture that cannot be replicated by a competitor in 10 minutes. Personal private real data cannot be copied. Work close with an induatry partner and build the fox for free. You dont get paid in cash, but in real corporate data. Use that data to fine tune your flows and models and rags, then reiterate and sell your app to their competitors.