Free training and education
AI Cost Academy
A practical learning path for teams that need better control over AI and cloud spend without becoming a finance department.
Use this when
You need a faster path than searching random posts
The Academy is organized around the real jobs teams work through: building a budget, forecasting growth, reducing AI cost, choosing better architectures, and running a repeatable weekly review.
Build a budget this week
Start with the budget and forecast track if you need a practical model for the next month.
Start hereDiagnose a spike quickly
Use the checklist path when you need an immediate answer instead of a long read.
Start hereReduce inference cost
Use the engineering tactics track to pick the next two cost changes worth shipping.
Start hereBuild an LLM workflow
Start with production patterns if you are designing retrieval, agents, chat, or multimodal features.
Start hereShip with evals and guardrails
Use the reliability path if you need release gates, review queues, and safer automation.
Start hereChoose your role
CTO or founder
Start with budget, forecast, and weekly review so you can explain spend with confidence.
Founding or staff engineer
Start with cost drivers, optimization, and architecture tradeoffs to improve margin without slowing shipping.
Platform or DevOps
Start with monitoring, thresholds, and weekly operating rhythm so the team sees spend early.
Application or ML engineer
Start with structured outputs, retrieval, agents, and evaluation if you are building LLM features directly.
Course paths
Pick the path that matches the job you need done
Each course is built around a specific operating problem and ends with a concrete next step, not a dead end.
Track and understand costs
Learn how AI and cloud costs actually work, what changes spend fastest, and which signals are worth checking every day.
Understand the cost model and identify the main drivers in one sitting.
Open courseBuild budget and forecast
Turn historical AI and cloud spend into a budget, forecast, and weekly review rhythm that helps teams stay ahead of invoice surprises.
Build a realistic budget and a forecast model that updates with usage.
Open courseReduce costs with engineering tactics
Prioritize the engineering changes that lower AI spend fastest without creating quality regressions or workflow drag.
Choose two high-impact cost reductions for the next sprint.
Open courseChoose cost-efficient architecture
Compare architecture and model decisions using cost, quality, and operational overhead instead of intuition alone.
Make one architecture decision with clearer economic tradeoffs.
Open courseBuild production LLM applications
Choose the right LLM pattern for structured data, retrieval, agents, chat, multimodal workflows, and ML-adjacent systems.
Choose and implement the right LLM pattern for one production workflow.
Open courseLLM reliability and governance
Build release gates, confidence checks, and operational controls that keep LLM systems useful in production.
Ship one LLM workflow with clearer evals, safety controls, and escalation paths.
Open courseRun weekly AI FinOps
Build a lightweight operating rhythm around budgets, reviews, and corrective action without creating process bloat.
Run a weekly AI cost review with clear owners and follow-up decisions.
Open courseChecklists and templates
Use diagnostic checklists and templates when you need a concrete answer now rather than a long read.
Diagnose or improve one part of the cost workflow immediately.
Open courseWhat happens next
Learn the method, then operationalize it
The Academy teaches the method first, then shows how teams turn it into a daily workflow using cross-provider cost analysis, forecast tracking, category review, and ongoing optimization.