The vibecoding journey, documented: project updates, the thinking behind each product, and lessons from shipping solo.
This blog is written by AI — on purpose, and I'm not hiding it.
Every post here is written by AI, in my voice and from my real project notes — the same AI I build everything with. The mind, the projects, and the journey are mine (Suhaib Elhadi); the writing is the machine's. I don't hide that. Owning it is the honest version, and honestly the more interesting one.
FCRA is about what your credit report says; FDCPA is about how a debt collector behaves. Knowing which law applies is why 'dispute everything' is the wrong move.
Reddit is the best place to find people with the exact problem your app solves — and the fastest place to get banned for saying so. How I think about marketing an app on Reddit.
Point your camera at a bottle and a model names the scent. What it actually takes to identify a fragrance from a photo — and the quiet ways it gets it wrong.
The same prompt, run twice, is the cheapest confidence check I have. When the two answers agree the ground is probably solid; when they diverge, that's the model telling you where it's guessing.
SQLite, self-run Postgres, or managed Postgres like Supabase — the real question isn't which is fastest, it's who gets paged when it breaks. How I actually choose, project by project.
Each app crops and covers your vertical video differently. How I stopped eyeballing it and encoded one safe layout into the render template so posting at volume can't drift.
A cold-email sending domain is a reputation asset that burns slowly and silently. The mechanics of SPF, DKIM, DMARC and a real warmup, and why none of it survives one bad week.
Vertical video safe zones decide whether your caption survives. Where TikTok and Reels put their UI, why published numbers disagree, and how to lay out a clip that works everywhere.
AI video drifts on brand color and exact product shape the same way it drifts on text. Why prompting can't fix it, and what grading and compositing actually solve.
Why AI video models mangle logos, labels and prices, and the compositing workflow that fixes it: generate clean plates, then apply the text in the edit.
How to storyboard a multi-shot AI video around continuity limits: plan cuts as features, pick the two or three shots that must match, and design the drift out.
Metro 2 is the format lenders' data has to follow. Understanding it is how you spot a reporting error worth disputing — and it's about funding, not credit repair.
No staging tier, no separate environment to babysit — just branch previews and a fast rollback. Here's why that's the right setup when it's just you.
The debtor's side of owing a friend money is its own kind of stuck. Here's the case for settling in the open instead of paying quietly and hoping it un-happens.
Four patches buy you continuity between AI-generated shots: reference frames, last-frame conditioning, video-to-video, and a character model. Here's what each one costs.
The generous move in lending money to friends is quietly walking away from it. Here's the case for making forgiveness an explicit button — and how you design it so it doesn't read as a flex.
The public reply to a one-star review isn't for the angry customer. It's for the next person reading, deciding whether to trust you.
If your database stores what someone bought, every pricing change is a migration. Store what they can do instead, and pricing becomes config.
"Multiple factors agreeing" sounds obvious until you have to turn it into a scoring function. The trap is quietly rebuilding a single indicator with extra steps.
The AI part of an AI product is a few lines. The code that decides whether there's enough input to run it at all is where the honesty lives. Here's how I actually build that check.
An AI website pipeline can generate the copy, the layout, the whole brand. It can't generate a photo of the actual room a customer is about to walk into. Here's how I try to get those anyway.
Five-star reviews tell you nothing and one-star reviews tell you someone was angry. The three-star review is where the real information lives.
Not everything in a Skool community is worth automating. Here's the order I'd actually do it in, ranked by what buys back the most time.
The Supabase free tier pauses a project after about a week of no traffic. Here's what that actually breaks, and how I decide which projects go Pro.
RevenueCat looks like a thin wrapper over StoreKit until you try to ship subscriptions yourself. Here's what it actually handles, from shipping a real iOS app.
How many Google reviews does a business need before a site can be written from them? Raw count is the wrong metric — here are the four tests I use instead.
The backtest says one thing, the paper shadow says another. Here's which one I believe, why the disagreement itself is the useful part, and what I fix.
A backtest is a description of the past, not evidence about the future. Here's every way mine lied to me, and the four things I need before risking real money.
A business is the worst describer of itself. Its Google reviews already contain the positioning — here's how I turn that pile of reviews into a whole website.
Next.js vs FastAPI isn't a performance question when you're building solo. It's about where the hard part of your app lives — here's the rule I use, and where it breaks.
A single-indicator alert isn't a signal, it's a coin flip with a notification sound. Here's why they fail and how scoring for confluence fixes each failure.