Deep breakdowns of AI infrastructure cost, SaaS pricing, and engineering decisions. Real numbers, stage-specific guidance, and opinions shaped by production experience.
Read by engineering leaders shipping production AI systems.
Vibe coding technical debt is the silent infrastructure tax paid when teams rely on AI code generation without architectural oversight. While AI tools accelerate early velocity, they produce unoptimized schemas that inflate cloud costs at scale.
Every scenario uses verifiable vendor pricing and concrete production data. No vague "it depends" conclusions.
Clear recommendations based on production experience. Not market surveys, not vendor-funded reports.
Early, growth, and scale stages produce different cost dynamics. Every analysis covers all three explicitly.
LLM token cost optimization requires stopping the practice of sending raw HTML to frontier models. Learn why shifting data cleaning to local...
Framesta Fernando 
Scaling Puppeteer or Playwright is an incredibly expensive architectural mistake. You are paying cloud providers to render CSS and parse DOM...
Framesta Fernando 
Most engineering teams assume residential proxy cost scaling is a linear math problem. This false mental model ignores the exponential compu...
Framesta Fernando 
The exclusive Microsoft and OpenAI deal is dead. With OpenAI models natively available on AWS Bedrock, engineering leaders must completely r...
Framesta Fernando 
Consolidating RAG infrastructure into Postgres seems pragmatic. However, at scale, critical pgvector scaling issues emerge. HNSW index trave...
Framesta Fernando 
Replacing RAG with a 1M token context window feels like a productivity hack. In reality, massive context window cost acts as a silent margin...
Framesta Fernando Engineering Manager & Technical Architect
5 years of experience leading dozens of engineers and architecting robust backend ecosystems to handle massive data volumes powering 100+ microservices, consistently sustaining hundreds of RPS, and optimizing databases to query millions of records in milliseconds.