13 articles
Slash your AWS bill in 2026: Reserved Instances vs Savings Plans, Spot Instances for 90% savings, right-sizing EC2, S3 intelligent tiering, Lambda cost analysis, RDS optimization, and FinOps dashboards with AWS Cost Explorer.
Reduce AI costs by 50% with OpenAI Batch API. Process embeddings, classifications, and reports offline with intelligent pipeline design.
Deploy LiteLLM as your AI gateway. Route requests across OpenAI, Anthropic, Cohere, self-hosted models. Implement fallback, rate limiting, and budget controls.
Cost visibility as a first-class concern: per-request metering, cost circuit breakers, ROI calculations, spot instances, and anomaly detection for sustainable AI systems.
Master token counting, semantic caching, prompt compression, and model routing to dramatically reduce LLM costs while maintaining output quality.
Route queries intelligently to cheaper or more capable models based on complexity, intent, and latency SLAs, saving 50%+ on LLM costs while maintaining quality.
Implement exact-match and semantic caching with Redis to dramatically reduce LLM API calls, improving latency and cutting costs by 60% through intelligent cache invalidation.
Master LLM token economics by implementing token counting, setting budgets, and optimizing costs across your AI infrastructure with tiktoken and practical middleware patterns.
Deploy Pinecone at scale with namespaces for multi-tenancy, metadata filtering strategies, batch operations, hybrid search, and cost optimization tactics.
Learn the Plan-and-Execute pattern for slashing AI inference costs. Use frontier models for planning, cheap models for execution, and optimally route tasks by type.
Choose between long-context LLMs and RAG by understanding the lost-in-the-middle problem, cost dynamics, and latency tradeoffs.
Implement semantic caching to reduce LLM API costs by 40-60%, handle similarity thresholds, TTLs, and cache invalidation in production.
Optimize Lambda cold starts, implement idempotent handlers, integrate with SQS, and understand when serverless costs more than traditional compute.