Johnathan K

We are in the golden era of "vibe-coding."

With AI tools, you can literally build and launch an MVP in a single weekend.

But here is the harsh truth no one talks about:

Building an app in a few hours is easy. Scaling it when it suddenly gets traction is brutally hard.

When an MVP built in a weekend suddenly gets a spike in users, you hit what I call the "Technical Cliff":

❌ Database queries bottleneck.

❌ API rate limits get crushed.

❌ The UI lags, and your early adopters churn.

Traction without technical stability is just a fast track to failure.

So, how do you improve your product and actually succeed when you catch lightning in a bottle?

Here is the playbook to go from a fragile MVP to a scalable business:

1️⃣ Audit Before You Add

Don't just keep piling new features on top of quick-fix code. Bring in a Senior Engineer to audit the architecture, optimize the database, and clear out the tech debt before you build anything else.

2️⃣ Architect for 10x Scale

Implement proper caching, optimize your backend logic, and ensure your infrastructure can handle 10x your current user load without breaking a sweat.

3️⃣ Play to Your Unfair Advantage

Founders, your job is to talk to users, market the product, and figure out monetization. Partner with a technical expert to handle the heavy lifting so you can focus on growth.

The biggest lesson in today’s tech world?

Success isn't just about who can build the fastest.

It's about who can build fast to validate, and then scale smart to dominate.

Founders: What’s the biggest technical bottleneck you’ve faced after getting unexpected traction? Let me know below!

I worked on the backend data layer for Cylinder Health - a specialized GI care platform that has now helped over 145,000 patients manage digestive conditions through clinician-backed, personalized care plans.

My piece of the stack: the clinical records layer and the EHR ingestion pipeline.

━━━ What "FHIR-compliant" actually means when you build it ━━━

FHIR (Fast Healthcare Interoperability Resources) is the standard that lets healthcare systems talk to each other. In theory it's clean. In practice, every EHR vendor - Epic, Athena, Cerner - sends you data in their own dialect of FHIR, with custom extensions, missing fields, and inconsistent date formats.

So the ingestion pipeline wasn't just "normalize JSON into Postgres." It was:

→ Model the core FHIR resources correctly: Patient, Observation, Condition, CarePlan - each with the right cardinality and relationships

→ Write normalization logic that could handle what real EHRs actually send, not what the spec says they should send

→ Output a PostgreSQL schema queryable by both the application layer (fast, indexed, relational) and the clinical team (human-readable, auditable, filterable by condition/patient/date)

━━━ Why this matters beyond healthcare ━━━

Any platform where multiple data sources feed a single operational layer - fintech aggregators, multi-ERP SaaS, IoT pipelines - hits the same problem: you don't control the upstream data quality, but downstream users expect consistency.

The FHIR normalization pattern translates directly.

Building something in healthtech, or dealing with messy multi-source data ingestion? Happy to talk through the architecture.

If you're a founder with an idea (or a half-built product), I can take it to production.

I'm a full-stack engineer. I help founders go from "we have a Figma" to "we have paying users."

No contractor handoff. No "the frontend dev can't wire Stripe." I own the whole thing - architecture, code, deployment, monitoring.

Here's what I've shipped recently:

→ AI SaaS MVP: zero to first paying customer in 4 weeks (Next.js + Supabase + OpenAI + Stripe)

→ Multi-tenant SaaS: 150+ customer accounts, per-tenant data isolation via Supabase RLS, zero cross-tenant incidents in prod

→ CRM automation: replaced 30 hrs/week of manual data entry with a Python + Twilio webhook pipeline. ROI in month one.

→ RAG internal assistant: cut support response time ~60% for a B2B SaaS team

My stack: Next.js · Supabase · Node.js(Express/Nest.JS) · Python (FastAPI/Django) · Stripe · OpenAI/Anthropic · Vercel · AWS

The founders I work best with usually have one of these problems:

◾ Need an AI SaaS MVP shipped in 4–6 weeks

◾ Want multi-tenant architecture done right from day one

◾ Have "vibe-coded" output from Cursor/Lovable that broke in production

◾ Are stuck on a stalled contractor handoff

If any of that sounds familiar - send me a message. I respond within a few hours and I'm happy to talk through what you're building before any commitment.

8+ years · AI · Fintech · Real estate · B2B SaaS · Healthcare

I built Timewell Books - a platform where customers create hardbound photo books, record voice stories for each photo, and then scan a QR code printed inside the book to hear those stories back. Years later.

The concept sounds simple. The engineering is not.

━━━ The hard part nobody thinks about ━━━

The QR code is printed once - permanently, in the physical book. That means the link has to work reliably 10, 20 years from now. No dead links. No "this service no longer exists." No app install wall when grandma scans it at Christmas.

So I built:

→ A QR generation and resolution system that maps each code to a specific page and specific user. Not just a URL - a durable identity layer for a physical object.

→ A cold-open mobile experience: when someone scans the code, the audio loads instantly with no app install required. First meaningful paint had to be fast - this is often a grandparent at a family gathering, not a developer on fibre.

→ A media upload pipeline for audio and images, built to handle the real messiness of consumer uploads (variable formats, slow connections, retry logic).

→ An admin dashboard for order and content management, so the team can track every book, every QR code, and every piece of attached media end-to-end.

━━━ The product ━━━

Timewell Books → timewellbooks.com

Curious if anyone else has built something similar this product or want it....

If you're a founder with an idea (or a half-built product), I can take it to production.

I'm a full-stack engineer. I help founders go from "we have a Figma" to "we have paying users."

No contractor handoff. No "the frontend dev can't wire Stripe." I own the whole thing - architecture, code, deployment, monitoring.

Here's what I've shipped recently:

→ AI SaaS MVP: zero to first paying customer in 4 weeks (Next.js + Supabase + OpenAI + Stripe)

→ Multi-tenant SaaS: 150+ customer accounts, per-tenant data isolation via Supabase RLS, zero cross-tenant incidents in prod

→ CRM automation: replaced 30 hrs/week of manual data entry with a Python + Twilio webhook pipeline. ROI in month one.

→ RAG internal assistant: cut support response time ~60% for a B2B SaaS team

My stack: Next.js · Supabase · Node.js(Express/Nest.JS) · Python (FastAPI/Django) · Stripe · OpenAI/Anthropic · Vercel · AWS

The founders I work best with usually have one of these problems:

◾ Need an AI SaaS MVP shipped in 4–6 weeks

◾ Want multi-tenant architecture done right from day one

◾ Have "vibe-coded" output from Cursor/Lovable that broke in production

◾ Are stuck on a stalled contractor handoff

If any of that sounds familiar - send me a message. I respond within a few hours and I'm happy to talk through what you're building before any commitment.

8+ years · AI · Fintech · Real estate · B2B SaaS · Healthcare