LLM FinOps in Practice
How to Cut Inference Costs by Up to 80% with Context Engineering, Caching & Smart Routing
- Date
- Tuesday, November 24, 2026
- Time
- 8:00 PM CET / 2:00 PM ET / 1:00 PM CT
- Where
- Online
Cost is an architectural defect, not a finance problem.
Vibe coding gives you momentum; unmonitored tokens give you a runaway invoice. When 85% of teams overshoot their AI budgets, cost isn't a finance problem: it's an architectural defect driven by bloated context, redundant tool calls, and infinite agent loops.
In this session, we break down how to treat LLM FinOps as an active engineering discipline.
What we will cover
Context Engineering over Token Bloat: decoupling knowledge into a deterministic Context Catalog to eliminate multi-hop overhead and slash query costs by up to 80%.
Semantic Caching & Smart Routing: stopping repeated prompt fees and dynamically offloading routine tasks from frontier models to SLMs.
Governance & Guardrails: using AI Gateways and local circuit breakers to catch non-deterministic loops before they drain credits.
Unit Economics & Observability: tracking cost-per-capability and token health directly in your engineering workflow.
Join us to learn how to sustain development velocity while keeping inference costs predictable and production-ready.
Save your seat: fill out the form and we'll send you the link to join.