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Google Ads vs SEO: How to Split a $10k/Month Budget When You Can't Do Both Properly
The $10,000 per month marketing budget question is the one I hear most often from founders and early-stage marketing leads. It sounds like a tactical question. It is actually a business strategy question in disguise, because the right answer depends entirely o
Meta Ads in 2026: What Still Works After Advantage+ Ate the Manual Playbook
I spent the better part of 2024 fighting Advantage+ on behalf of clients who had carefully built manual campaign structures. I lost. Not because the clients were wrong to want control, but because Meta had redesigned the entire ad platform around their learnin
Document Extraction Pipelines: Combining Vision Models, OCR, and Validation
Three clients, three different industries, nearly identical problems. A London law firm could not extract clause information from contracts arriving in mixed formats (PDF, DOCX, scanned images). A Manchester manufacturer needed structured data from supplier in
OCR Pipelines That Actually Work in Production: Lessons From 2M Documents
Over the last two years I have processed roughly two million documents across five client projects: medical records for a Karachi cardiology clinic, customs forms for a Berlin logistics company, insurance claims for a Bahrain broker, property contracts for a D
Self-Hosted vs. API LLMs for Internal Tools: A Real Cost Breakdown
This is the question I get most often from clients who have been running LLM-powered internal tools for six months: should we keep paying OpenAI or move to a self-hosted model? The honest answer is that it depends on four specific variables, and I can give you
LLM Tier Economics: Flash Lite vs Pro vs Frontier - A Decision Framework
Every major LLM provider now offers three tiers: a small/lite model (Gemini 3.1 Flash Lite, Claude Haiku, GPT mini variants), a mid-tier workhorse (Gemini 3.1 Pro, Claude Sonnet 4.6, GPT 5.4/5.5), and a frontier flagship (Claude Opus 4.7, reasoning-tier models
Streaming LLM Responses in FastAPI: SSE, WebSockets, and Real-Time AI
LLM responses are fundamentally different from traditional API responses. A typical database query returns in under 100ms. A GPT-4 completion for a long prompt can take 15-30 seconds to fully generate. Users will abandon a blank screen after 2-3 seconds. The s
Next.js Caching: A Production Deep Dive (Fetch, Router, ISR, Edge)
Next.js has four caches. They interact. They don't always invalidate the way you'd guess. Most production incidents I've debugged in the last year on Next.js apps trace back to a misunderstanding of one of the four. usually the Data Cache or the Full Route Cac
Next.js Edge Runtime - A Production Reality Check
The pitch for the Edge Runtime sounds irresistible: your code runs in 300+ cities, the cold start is under 50ms, and your users always hit a server within a few hundred miles of them. Latency disappears. The reality, after building several apps that targeted E
Next.js App Router in Production: Patterns That Actually Scale
The Next.js App Router has been generally available for over two years now. The early "should we migrate?" debates have settled. the answer for new projects is yes, and the migration patterns for existing apps are mature. But the App Router rewards a different
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