nikolas.sapa

Athens, Greece · 17

Nikolas Sapalidis

I build custom software — websites, apps, AI systems — from scratch.

I started where most teenagers start: deep in the self-improvement rabbit holeBooks, systems, 5am routines. Useful discipline, zero income.. That led to trading and crypto, then setting up a Google Ads agencyBuilt the offer and the site, never launched it. No clients, no ads ever run. that never launched, then trying to sell digital products — and getting nowhere. Didn't make a cent from any of it.

Then I learned to code. Got my first paying client in February 2026 and realized it was actually working. Since then I've built across the full stack — websites, web apps, iOS apps, AI automations, custom pipelines, admin dashboards, internal tools. No templates, no page builders. Everything custom.

Alongside client work I build products. First was Helpmarq — a feedback marketplace for structured, expert feedback on real projects. Since then: MarketMyAppMarketing plan generator for indie app builders — positioning, channels, copy., Creator RoastHonest teardown of a creator's page. No compliments, just what's costing you signups., Branch AI (900+ npm downloads), NeuroPulseOpen-source brain-response analyzer for marketing content. Drop in an ad, get scored across 8 brain regions., ns-ui (298 React components you install by URL), and more. I also work at AutomateSphere AI building custom AI automation for businesses.

"No existing brief. Needed something premium without feeling generic. Four days later: live, custom, exactly what I asked for."

— Sean Lee, client

Since April 2026 I've been on Claude Code MaxAnthropic's top tier. Custom skills, hooks, subagents — the whole harness tuned around how I actually work.. It changed how I work. I run a homelabSelf-hosted Supabase + n8n on my own hardware. No per-seat pricing, no vendor deciding my rate limits., ship multiple products in parallel, and build client work on the side. I write about the patterns that actually work — not the hype.

Lately I've been going deep on machine learningBackprop by hand, tensors from scratch, small models I can explain end to end. No framework hiding the maths. — from the fundamentals up, not the API-wrapper version. I've shipped a lot of AI on top of other people's models; now I want to understand what's actually happening underneath. Building small models by hand, doing the math, no shortcuts.

1984 contributions this year

Currently

  • SAC CapitalAgent that screens equities on fundamentals, momentum and disclosure signals, then argues its own picks down. Real money, published CLI. — live AI trading agent, CLI on PyPI
  • → Learning ML from the fundamentals
  • ns-ui298 React components, install by URL. Playwright gate fails anything whose hover looks identical to its resting state. — component registry, live at design.helpmarq.com
  • sigevalEvals as proportions with confidence intervals. PASS, FAIL, or INCONCLUSIVE — never a coin-flip. — statistical evals for LLMs
  • → AutomateSphere AI — client automations
  • → Client dev work — web, automations

How it works

  1. 1. Blueprint call — 30 min, you describe the problem
  2. 2. I send a scoped proposal within 24 hours
  3. 3. We build — Figma first, code after approval

Contact for more.

Taking 1–2 clients this month — slots fill fast.

Not ready yet? Get the build log — weekly notes on what I'm shipping, patterns that work, things that didn't.