Architecture.
AI Systems.
Growth Engineering.
Deep technical content on building sovereign infrastructure, private AI agents, PostgreSQL at scale, and full-stack systems design.
< EXPLORE_KNOWLEDGE />What I Write About
< INFRASTRUCTURE />
Self-hosted alternatives to SaaS, Coolify deployment guides, n8n automation patterns, PostgreSQL schema design, and Docker production setups.
< AI_SYSTEMS />
Private LLM deployment, RAG pipelines with pgvector, LangChain vs bare API patterns, and AI agents that run on your own hardware.
< GROWTH_ENGINEERING />
Server-side conversion tracking, CAPI setup, attribution modeling, CAC/LTV calculators, and funnel analytics that survive iOS14.
Topic Index
Sovereign Infrastructure
Why self-hosted beats SaaS past $1M revenue. Coolify, n8n, Supabase, and the stack for infrastructure independence.
Private AI Agents
Running Llama, Mistral, and custom fine-tunes on your own VPS. No OpenAI data risk. Full control.
PostgreSQL Deep Dives
JSONB vs relational, pgvector for semantic search, Row-Level Security for multi-tenancy, and asyncpg patterns.
Server-Side Tracking
Facebook CAPI, Google Enhanced Conversions, and TikTok Events API. Attribution without cookies or pixels.
FastAPI Patterns
Async architecture, dependency injection, Pydantic v2, background tasks, and deployment on Coolify.
Astro & Frontend
SSR with Astro, React islands, Tailwind design systems, and building Lighthouse 100 marketing sites.
Calculator Architecture
ROAS, CAC, LTV, cohort analysis. How I build interactive financial tools that capture leads and educate buyers.
Security & DevOps
SSH hardening, Docker secrets, PostgreSQL RLS, and zero-trust architecture for agencies handling client data.
Featured: The Sovereign Stack Guide
The most common question I get after a strategy call: "What would you actually build for us?" The answer is almost always the same stack, adapted to the problem.
The Core Stack
Backend: Python 3.12 + FastAPI + asyncpg + PostgreSQL 16. This handles everything from lead capture to AI agent orchestration to billing webhooks. One language, one database, full async.
Automation: Self-hosted n8n on a $10/mo VPS (or shared with the main server). Replaces Zapier entirely. Handles CRM syncs, email sequences, Slack notifications, and webhook relay without per-task fees.
Frontend: Astro SSR for marketing pages, React for dashboards and interactive tools. Tailwind for design system. Zero client-side JavaScript unless needed.
Infra: Coolify on a Hetzner or Digital Ocean VPS. Git-push deploys. Auto SSL. Docker Compose per service. Total cost: $50–$200/mo depending on scale, vs. $3,000–$5,000/mo in SaaS subscriptions.
AI: Ollama + pgvector for private LLM operations. OpenAI API only for non-sensitive tasks. Fine-tuned Llama for client-specific workflows.
Built From Real Projects, Not Tutorials
Every post on this blog comes from a system I have actually deployed in production. No tutorial repos. No "example" codebases. If I write about a PostgreSQL optimization, it is because I ran EXPLAIN ANALYZE on a 50M-row table and found the winning index.
I have built systems for media agencies, solar installation companies, law firms, e-commerce brands, and SaaS startups. The patterns repeat. The mistakes repeat. The solutions I write about are the ones that closed the gap between "it works in dev" and "it works at scale."
Want This Applied to Your Stack?
Reading about architecture is useful. Having it built for you is better.
Book a Strategy Session// LATEST_POSTS
RSSVector Search in Postgres: Preparing Your Data for AI
You don't need a dedicated vector database to build AI features. I use pgvector inside PostgreSQL to store embeddings right next to relational data. It simplifies architecture, speeds up development, and keeps all your data in one source of truth.
PostgreSQL: The Only Database You Actually Need
You don't need MongoDB for documents, Redis for caching, and Pinecone for AI. PostgreSQL does it all. With JSONB columns, pgvector for AI search, and RLS for multi-tenancy, Postgres provides document flexibility without sacrificing relational integrity.
Real URLs, Real Data: Mastering the Fast Cycle
Day 4–14 of my methodology is implementation in fast cycles. The rule? Each cycle ends in a production deployment. Not a staging link. Not a local demo. Real URLs, real data, real results. Continuous deployment is the only way to validate code.
Asyncpg: Building High-Throughput APIs in Python
If you are building APIs in Python, standard SQLAlchemy is holding you back. For high-throughput, read-heavy workloads, async Python combined with asyncpg is up to 3x faster. Here is how to architect for pure speed.
The 14-Day Blueprint: Escaping the Endless Sprint Cycle
You don't need another sprint; you need a system. Moving from discovery to production in 14 days isn't about typing faster—it's about a repeatable architecture methodology. No sprints that slip. No handoff chaos. Just a strict transition from Discovery → Design → Deploy.
The Architecture-First Principle: Why Writing Code is Your Last Step
The single biggest mistake development teams make is writing code before the architecture is locked in. Technical debt compounds with every sprint. Refactoring a live system costs 5–10x more than designing it correctly from the start. Here is how to run a 48-hour architecture sprint.
Python FastAPI vs. Node Express: Building Data-Heavy Backends
Stop defaulting to Node Express for your backends. Python FastAPI is async by default, provides built-in Pydantic validation, and auto-generates OpenAPI docs. If you are building data-heavy, high-throughput systems, the architecture choice is clear.
Astro vs. Next.js: Scoring 100 on Lighthouse
Next.js is shipping too much JavaScript to your users. For marketing sites, I use Astro. Zero JavaScript by default. HTML ships directly to the browser, with React islands only where needed. The result? Lighthouse scores in the 95–100 range, every time.
Multi-Tenancy Made Simple with Postgres RLS
Building a SaaS? Stop writing complex application logic to separate client data. Postgres Row-Level Security (RLS) handles multi-tenancy at the database layer. Secure, scalable, and impossible to bypass via a buggy API endpoint.
Anti-Pattern: Writing Code Before the Schema is Locked
Failure pattern #1: No schema before code. When database changes break the API weekly, your project is bleeding out. Lock the database schema first, define the API contracts second, and only then start the frontend.
Anti-Pattern: Using Zapier for Core Business Logic
Failure pattern #2: Zapier as business logic. Webhook reliability on commercial iPaaS platforms sits around 97%. That 3% failure rate means lost leads, broken onboarding, and angry clients. Business logic belongs in your backend.
Anti-Pattern: "Works on My Machine"
Failure pattern #4: No local dev parity. "Works on my machine" delays every sprint. If your local environment doesn't mirror production exactly, you are guessing, not engineering. Docker is non-negotiable.
The Art of the 48-Hour Architecture Document
Every engagement I take begins with a 48-hour architecture sprint: no code, just design. I produce a written document covering the database schema, API contract, infrastructure diagram, and deployment strategy. Here is how to write one.
The 14-Day Blueprint: Escaping the Endless Sprint Cycle for New York County SaaS Startups
You don't need another sprint; you need a system. Moving from discovery to production in 14 days isn't about typing faster—it's about a repeatable architecture methodology that scales users fast for New York County SaaS founders pushing growth with the Empire State Building in view.
The 14-Day Blueprint: Escaping the Endless Sprint Cycle for Miami-Dade Real Estate Brokerages
You don't need another sprint; you need a system. Moving from discovery to production in 14 days isn't about typing faster—it's about a repeatable architecture methodology that gets listings live fast for Miami-Dade brokers closing deals around South Beach and the Brickell skyline.
The 14-Day Blueprint: Escaping the Endless Sprint Cycle for Los Angeles County Marketing Agencies
You don't need another sprint; you need a system. Moving from discovery to production in 14 days isn't about typing faster—it's about a repeatable architecture methodology that gets campaigns live fast for LA agency owners chasing clients from the Hollywood Sign to Santa Monica Pier.