Technical decisions, explained clearly.
Practical references for using developer utilities safely and planning AI systems with realistic assumptions.
How Much VRAM Does an LLM Need?
A practical breakdown of model weights, KV cache, context length, batching, and runtime overhead.
AI infrastructureLLM Quantization: FP16, INT8, and INT4 Explained
Understand what lower precision changes, what it saves, and why file size is not the whole deployment story.
AI budgetingHow to Calculate AI API Costs
Forecast spend using input tokens, output tokens, cache rates, request volume, and realistic usage distributions.
Developer workflowJSON Formatting and Validation Without Exposing Data
Diagnose malformed JSON safely and understand the errors formatters are helping you find.
SecurityHow to Decode a JWT Safely
Read JWT claims without confusing decoding with signature verification or trust.
Developer workflowA Practical Guide to Cron Expressions
Read five-field schedules, avoid timezone surprises, and test jobs before they reach production.
AI infrastructureHow to Calculate KV Cache Memory
Understand the variables behind one of the largest memory costs in long-context LLM inference.
AI infrastructureChoosing a GPU for Local LLMs
Balance memory capacity, bandwidth, runtime compatibility, power, and workload requirements.
AI infrastructureINT4 vs INT8 for LLM Inference
Compare memory savings, output quality, performance, and operational compatibility.
AI budgetingHow Token Caching Reduces API Costs
Estimate cache-eligible input, hit rates, invalidation, and the real effect on model spending.
Developer workflowUnix Seconds vs Milliseconds
Recognize timestamp units, prevent 1970 dates, and exchange time safely between systems.
Developer workflowCommon JSON Validation Errors
Find trailing commas, invalid quotes, escaping problems, and structural mistakes faster.