▸ Blog · Page 4
More from the trenches.
Older posts. Same hot takes.
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AIRAG vs fine-tuning: choosing your AI architecture
RAG vs fine-tuning for production LLMs — knowledge vs behavior, latency, cost, privacy, and the hybrid approach. How to pick the right AI architecture.
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DevOpsRate limiting vs throttling
The engineering difference between rate limiting and throttling, and how each secures your APIs and keeps infrastructure stable under heavy load.
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AIRAG architectures: traditional, agentic, corrective
Compare traditional, agentic, and corrective RAG architectures, with the latency, cost, and accuracy trade-offs that decide which fits your AI app.
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ArchitectureMonolith vs microservices: how to choose
Monolith vs microservices: the real technical trade-offs for Laravel and Shopify teams, when each pays off, and why a modular monolith often wins.
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AIPrompt engineering vs context engineering
The shift from instruction design to data infrastructure — how context engineering uses RAG and MCP to build robust, accurate AI systems.
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AIML engineer vs AI engineer
ML engineer vs AI engineer: who trains the model, who orchestrates the system, their diverging toolsets, and which role your AI roadmap actually needs.
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ArchitectureLoad balancer vs reverse proxy: scale vs security
Reverse proxies handle SSL, caching, and security; load balancers handle scale and availability. The differences — and how to layer both in a Laravel stack.
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DevOpsLogging vs monitoring: a guide for scaling
Monitoring tells you a system is unhealthy; logging tells you why. How to combine metrics, structured logs, and correlation IDs for fast debugging.
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ArchitectureLoad balancer vs API gateway
Load balancers distribute traffic; API gateways enforce policy. The real differences, when to use each, and how to layer both in a production stack.
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