Structured tutorials and reference knowledge—organized for learning and lookup
Current Situation Analysis We migrated our LLM serving layer from a naive round-robin load balancer to a specialized infrastructure in Q3 2024. The results were not incremental; they were structural. We reduced cost per million output tokens from $3.80 to $1.36, cut p99 latency from 1.4s to 0.
Current Situation Analysis Most engineering teams treat Ollama as a drop-in replacement for OpenAI in development and hit a wall immediately in production. The standard tutorial pattern is docker run ollama/ollama followed by setting OLLAMA_KEEP_ALIVE=-1.
Current Situation Analysis When we audited our internal RAG pipelines across three product lines, the results were embarrassing. We were burning $14,000/month in LLM inference costs for a system with 42% cacheable query overlap.
## Current Situation Analysis Customer development interviews are the primary feedback mechanism between engineering output and market reality. Despite their critical role, they remain one of the most
Current Situation Analysis We migrated our customer support agent to an LLM-driven architecture six months ago. Within three weeks, the API bill hit $18,000/month, and our P99 latency jittered between 800ms and 2.4s. The root cause wasn't the model choice; it was how we treated the API.
Current Situation Analysis Most engineering teams treat Product-Market Fit (PMF) as a retrospective business analysis. You build a feature, deploy it to 100% of users, wait three weeks for analytics to aggregate, and then decide if it "worked." This latency is catastrophic.
Current Situation Analysis Most engineering teams treat Clean Architecture as a folder structure. This is a category error that leads to what I call "Clean Architecture Theater.
## Current Situation Analysis Infrastructure drift occurs when the actual state of deployed resources diverges from the desired state defined in Infrastructure as Code (IaC). Despite the widespread ad
