Walid Boulanouar recently shared something that caught my attention: "you can actually build everything you need using this tech stack.

0$ to build agents, apps....

a guy on r/vibecoding went from $300/mo to $0."

That line hits because it reframes the real bottleneck for most builders. It is rarely a lack of ideas. It is rarely even a lack of skill. It is the slow leak of monthly subscriptions that quietly turns experimentation into a budget meeting. Walid is arguing for something simpler: a $0 stack buys you time. Time to ship, learn, and only pay when you have signal.

In this post, I want to expand on Walid's idea and turn his list into a practical blueprint you can actually use this weekend, including what each tool does, how the pieces connect, and the tradeoffs to watch for.

"a $0 stack buys you time.
time to iterate, find signal, and charge later."

The core thesis: stop paying to learn

If you are early in a product or experimenting with AI agents, your biggest risks are uncertainty and churn, not scale. A free-tier stack is not about being cheap. It is about maximizing iterations per week.

Paid tools can be worth it, but they make the wrong thing feel urgent. You start optimizing dashboards before you have users. You buy a hosted database with more capacity than your first 12 months. You pay for auth features you will not configure correctly yet. Walid's stack flips the order: ship first, observe second, pay third.

Walid's $0 stack, organized by job-to-be-done

Walid broke the stack down cleanly by utility. Here is the same structure with a bit more context so you can map it to your own app.

Hosting: Vercel

Vercel is the default choice for quickly deploying a Next.js or frontend app with minimal friction. The free tier is often enough for prototypes, internal tools, and early-stage SaaS.

What it buys you:

Instant deployments from GitHub
Preview URLs for every branch or PR
Edge and serverless options for quick API routes

What to watch:

Usage-based limits can surprise you if you suddenly get traffic
Long-running background jobs do not fit serverless well without additional patterns (queues, cron, workers)

Backend + database: Supabase

Supabase gives you Postgres, a REST and realtime layer, storage, and an auth option. Walid highlights it as the backend + DB anchor, and that is exactly where it shines: a real relational database with modern developer ergonomics.

Why it works for $0 builds:

Postgres is a durable foundation, even when you outgrow the free tier
You can start with basic tables and row-level security without inventing your own permissions system
It pairs nicely with Vercel for a classic web app pattern

Tradeoffs:

You still need to think about schema design and data access patterns
Realtime and storage are great, but easy to overuse without guardrails

Auth: Stack Auth (StackAuth)

Walid lists "stackauth" as a dedicated auth layer. The reason builders pick a separate auth provider, even when Supabase Auth exists, is usually one of these:

They want a different UX for login flows
They want provider-agnostic auth if they might switch databases
They want specific enterprise features later

My take: if you are truly at prototype stage, you can often start with Supabase Auth to reduce moving parts. If you already know you want a dedicated auth layer (or you are building multiple apps), a standalone auth service can simplify governance across projects.

AI layer: OpenRouter + Gemini (and Grok)

This is the heart of Walid's post: you can build agentic features without locking into a single model vendor.

OpenRouter acts like a routing layer: one API, multiple models. Walid calls out Gemini and sometimes Grok, and also mentions that new models can drop with free access for limited windows. That matters because experimentation is the whole point.

Practical benefits:

Swap models without rewriting your app
Compare outputs and costs side by side
Fail over if one model is rate limited

What to watch:

Free access windows end, and pricing changes
Prompting and tool-use can vary by model, so you need light abstraction
Data handling and privacy requirements may push you to specific providers

Analytics: PostHog + Clarity + GA

Walid's combo here is interesting because it is not "pick one." It is "use each for what it does best."

A simple way to think about it:

PostHog: product analytics, events, funnels, feature flags
Microsoft Clarity: session replays and heatmaps for UX debugging
Google Analytics: broad traffic attribution and baseline web analytics

If you are starting from zero, you can implement only PostHog first, then add Clarity when you need to see why users are stuck. GA can come later if marketing channels start to matter. The goal is not to instrument everything. It is to answer a small set of questions weekly.

If your analytics do not change what you build next, they are just noise.

ML fine-tune path: Unsloth (prod)

Walid mentions "unsloth prod" as a fine-tuning path. The key idea: you do not need fine-tuning to start, but it is useful to have an upgrade path once you have real data.

A sensible progression looks like this:

Start with prompting and retrieval (RAG)
Add evaluation and logging
Fine-tune only when you can clearly measure improvement

Fine-tuning too early is a classic way to burn time. Walid's stack keeps it optional until you have evidence.

Code home: GitHub

This one seems obvious, but it is part of the $0 story: your workflow matters as much as your infra. GitHub gives you version control, PR reviews, issues, and CI options that scale from solo builder to team. Paired with Vercel previews, it becomes a tight loop.

Why r/vibecoding matters more than the tools

Walid also points to a non-tool component: "communities like r/vibecoding (250k builders) are basically a living playbook for this."

That is not fluff. When people swap stacks in public and share receipts, you get three advantages you cannot buy:

Real benchmarks (what actually costs $0 at your scale)
Migration stories (what breaks at 10 users vs 10,000)
Patterns for shipping fast (templates, prompts, workflows, automations)

In other words, the community acts like distributed R and D. The stack is the baseline, but the playbook is the compounding asset.

A weekend plan: turn subscriptions into a shipping loop

Walid's call to action is simple: "block 30 minutes this weekend, list every paid dev tool, and find a free-tier /opensource swap." I would extend that into a practical checklist.

Step 1: List what you pay for, by category

Write down every recurring dev-related cost, including "small" ones. Group them into:

Hosting
Database
Auth
AI APIs
Logging and analytics
Email, files, and background jobs

Step 2: Define the minimum acceptable replacement

For each category, decide what you truly need for the next 30 days. Example: "auth" might mean "email magic link + Google login," not "enterprise SSO."

Step 3: Swap one category at a time

Do not migrate everything at once. Pick the highest-cost, lowest-risk item. Deploy a small slice, verify, then move on.

Step 4: Add guardrails so $0 stays $0

Free tiers often fail because of accidental overuse. Add simple guardrails early:

Rate limits on endpoints that call LLMs
Budgets and alerts for AI spend
Sampling for analytics events if you get noisy
Caching for repeated prompts or retrieval results

The bigger point I took from Walid

Walid is not saying paid tools are bad. He is saying excuses are expensive. If someone can drop from $300 per month to $0 and still ship agents and apps, then the default for early builders should be: prove demand first.

A $0 stack is not a permanent identity. It is a strategy for getting to the only moment that matters: when users pull the product out of your hands and you have permission to charge.

This blog post expands on a viral LinkedIn post by Walid Boulanouar, building more agents than you can count | aiCTO ay automate & humanoidz | building with n8n, a2a, cursor & ☕ | advisor | first ai agents talent recruiter. View the original LinkedIn post →