LLM Tool Use Patterns in 2026 — Schemas, Validation, and the Loop
Practical LLM tool use: schema design, parallel tool calls, error/retry on bad inputs, tool result formatting, and patterns that scale beyond 5 tools.
LLM
LLM Batch Processing in 2026 — Anthropic / OpenAI Batch API for 50% Off
Practical LLM batch processing: when 24-hour latency is fine, queueing patterns, retry logic, error handling, and integrating batches with online apps.
LLM Deployment Patterns in 2026 — Inference Servers, Routing, and Production Architectures
Practical LLM deployment: vLLM / TGI for self-hosted, hybrid (API + local), routing layers, autoscaling GPUs, fallbacks, and serving cost economics.
Prompt Engineering in 2026 — What Still Works, What Doesn't, and What Changed
Modern prompt engineering: instruction clarity, structured prompts, few-shot vs zero-shot, role tags, and the patterns that survive model upgrades.
LLM Context Windows in 2026 — Long Context, Cache, and the Limits of 'Just Add More'
Practical long-context: when more context helps vs hurts, the lost-in-the-middle problem, caching strategies, retrieval as the better default, and 1M-context economics.
Multimodal LLMs in 2026 — Vision, Audio, and What's Actually Useful
Practical multimodal: vision-aware document understanding, audio transcription + reasoning, image-from-text, video understanding, and where multimodal pays off.
LLM Observability in 2026 — Tracing, Evals, and the Things You Can't Skip
Practical LLM observability: tracing every call, eval harnesses, regression detection, prompt versioning, and how to debug the model in production.
LLM Cost Optimization in 2026 — From Bills That Hurt to Bills That Don't
Practical LLM cost cuts: prompt caching, model routing, batch APIs, structured output, fine-tunes for high-volume narrow tasks, and cache hierarchies.
LLM Guardrails in 2026 — Input Filtering, Output Validation, and Safety Nets
Production guardrail patterns: input filters, output validators, prompt injection defenses, PII redaction, and how to compose guardrails without killing latency.
Fine-Tuning LLMs in 2026 — LoRA, QLoRA, and the Cheap Path to Specialized Models
How to actually fine-tune LLMs in 2026 — LoRA / QLoRA mechanics, training data discipline, evaluation, and the patterns that make fine-tunes ship.