Bring FinOps discipline to production LLM systems by measuring AI spend, optimizing token usage, and building cost controls that scale with your applications
LLM applications introduce a new kind of cloud economics. Costs are usage-based, model-dependent, and influenced by everything from prompt length and caching to RAG pipelines and autonomous agent loops. As grows, engineering teams need more than isolated cost-cutting tricks; they need FinOps for LLM systems.
The AI Cost Playbook shows you how to apply financial accountability and engineering discipline to production AI. You’ll build tokenwatch, a Python-based cost observability and optimization toolkit, while learning to meter tokens, attribute spend, and calculate costs per request, user, and feature.
You’ll then reduce unnecessary spend through prompt optimization, caching, batch processing, model routing and cascades, RAG optimization, and agent cost controls. You’ll also evaluate the break-even economics of self-hosting and learn how to forecast future AI expenditure.
Finally, you’ll turn optimization into an operating discipline by establishing budgets, quotas, forecasting, and cost accountability. With configurable pricing rather than hardcoded model costs, the techniques remain useful as providers, models, and pricing evolve.
This book is for AI engineers, ML engineers, software engineers, platform engineers, technical leads, engineering managers, architects, and FinOps professionals responsible for building or operating LLM applications. It will also benefit technology leaders responsible for AI infrastructure and API spending who want to understand the economics behind production AI systems and establish better cost controls. Familiarity with LLM applications and basic Python will help readers get the most from the implementation-focused sections.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Caio Incau is an Engineering Manager with experience leading software engineering teams at scale. In his day-to-day work, he combines people leadership with deep technical expertise to deliver products that impact millions of users. He started using Claude Code out of curiosity, became an advocate after seeing the productivity gains firsthand, and wrote this book so other developers wouldn't have to figure everything out on their own.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. N° de réf. du vendeur I-9781808822155
Quantité disponible : Plus de 20 disponibles
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. Neuware - As LLM applications scale, controlling their unpredictable usage-based costs becomes critical. N° de réf. du vendeur 9781808822155
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