// Topics / Performance

Performance

    AI Inference Cost Trends 2026: Model Pricing and Token Costs AI inference costs are falling, but durable savings come from routing, caching, context control, and cost per outcome. cost ai performance AI Cost Benchmarking: What Your Bill Actually Tells You Price-per-token is the least useful number on your AI bill. Real cost benchmarking starts with your workload, not a provider's pricing page. ai cost llm The Best Model Is the Smallest One That Works Everyone reaches for GPT-4 by default. Most production tasks don't need it. Small models are faster, cheaper, and often better when the task is well-defined. llm ai performance LLM Prompt Caching in Go: Cut Costs Without Breaking Things Caching LLM responses is the highest-leverage optimization most teams skip. How I implement it in Go -- keys, invalidation, and safety patterns. llm performance go Your Cloud Bill Is Not a Mystery Most cloud cost problems are visibility problems. Fix tagging, kill idle resources, right-size what remains, and make cost a regular engineering conversation. cost cloud infrastructure Caching: The Easy Part Is Adding It, the Hard Part Is Everything Else Cache-aside, write-through, invalidation strategies, and the failure modes that will wake you up at night. With Go examples. performance databases go PostgreSQL Performance: Measure First, Tune Second Most Postgres performance problems are indexing problems. The rest are vacuum problems. Here's how to find and fix both. databases performance backend Rust for Cloud Services: A Go Developer's Honest Take I write Go for a living. Rust is not replacing it. But I have to be honest about where Rust wins. engineering go cloud eBPF Is Interesting. I Am Not Sold Yet. eBPF promises kernel-level observability without the pain of kernel modules. The tech is real. The hype-to-adoption ratio concerns me. observability engineering performance Your Load Tests Are Lying to You Most load tests produce comforting numbers instead of useful answers. Here's what I learned the hard way about getting honest results. testing performance reliability The PostgreSQL Tuning Playbook I Actually Use Battle-tested PostgreSQL tuning: connection pooling, memory sizing, index discipline, vacuum management, and the queries that tell you what's broken. databases performance backend Making Go Services Fast: What Actually Matters Practical patterns for squeezing performance out of Go services — profiling, allocation control, bounded concurrency, and HTTP/DB tuning from real production work. go performance backend A Go Developer Looks at Rust for Backend Work I write Go every day at the fintech startup. Here's why I've been spending evenings with Rust, what impressed me, and where it still hurts. engineering go backend Stop Guessing: How I Fix Slow Databases The repeatable process I use at the fintech startup to diagnose and fix database performance problems instead of throwing random indexes at the wall. databases performance