6 min readDevelopment
Estimating LLM Costs Before You Build
Learn how to accurately forecast LLM expenses before development begins. This guide covers unit economics, token forecasting, and sensitivity analysis for engineering leaders.
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Ai Infrastructure
Read 9 articles on Ai Infrastructure by Ashish Srivastava — practical guides covering implementation patterns, security, and production lessons.
9 posts
8 min readBackendFeatured
Multi-Provider Failover with LiteLLM
Learn how to configure LiteLLM's router for automatic failover across multiple AI providers, ensuring high availability and resilience for your backend applications.
6 min readDevelopmentFeatured
Prompt Caching Across Providers: A Practical Comparison
Explore how different AI providers handle prompt caching, including cache TTL limits, cost implications, and prefix matching techniques to optimize API usage.
6 min readBackendFeatured
Vector DB Comparison: pgvector, Qdrant, Milvus, LanceDB
Analyze the strengths and trade-offs of pgvector, Qdrant, Milvus, and LanceDB to select the right vector database for your RAG architecture.
Part 4 · RAG from Zero to Production
6 min readDevelopmentFeatured
Choosing an Embedding Model in 2026
Navigate the 2026 landscape of embedding models. Learn how to evaluate MTEB scores, leverage Matryoshka dimensions, and handle multilingual data for production RAG.
Part 3 · RAG from Zero to Production
6 min readDevelopmentFeatured
Spot, Reserved, or Serverless GPUs: Picking a Capacity Strategy
A practical comparison of spot, reserved, and serverless GPU pricing models to help platform engineers optimize AI infrastructure costs.
Part 4 · GPU Economics for AI Teams
6 min readDevelopmentFeatured
Cost per Million Tokens: Building an Honest Model
Stop guessing your AI infrastructure spend. This guide breaks down the real math behind cost per million tokens, GPU efficiency, and total cost of ownership for self-hosted models.
Part 3 · GPU Economics for AI Teams
8 min readDevelopmentFeatured
Reading a GPU Spec Sheet: FLOPs, Bandwidth, and What Binds You
Stop guessing which GPU fits your workload. Learn to read spec sheets by understanding the relationship between compute power, memory bandwidth, and arithmetic intensity.
Part 1 · GPU Economics for AI Teams
6 min readDevelopmentFeatured
Tokens, Context Windows, and Why Your Bill Looks Like That
A technical breakdown of tokens, context windows, and tokenizer mechanics to explain LLM pricing structures.
Part 2 · LLM Inference from Scratch