savings

AI Economics & Cost Engineering

Token economics, GPU pricing, model selection, optimization techniques, agent cost control, and AI FinOps — everything you need to understand what AI actually costs and how to spend wisely
Co-Created by Kiran Shirol and Claude
Topics Token Economics GPU Pricing Model Selection Cost Optimization Agent Costs AI FinOps
home Learning Portal play_arrow Start Learning summarize Key Insights dictionary Glossary 8 chapters · 3 sections
Section 1

Token Economics — The Currency of AI

What tokens are, how they’re priced, the hidden multipliers that inflate your bill, and what real-world AI systems actually cost per month.
1
toll
What Is a Token?
The taxi meter analogy. How BPE breaks “Unbelievable” into 3 tokens. Why code costs more than English. The 1,000x cost collapse from $20/M tokens (2022) to $0.40/M (2026).
arrow_forward Learn
2
receipt_long
The Token Price Tag
The restaurant analogy — reading the menu (input) is cheap, the chef cooking (output) is expensive. Why output tokens cost 3–8x more. The 375x price variance across models.
arrow_forward Learn
3
visibility_off
Hidden Multipliers
The iceberg analogy. Invisible reasoning tokens that 20x your bill. Quadratic attention scaling. Context surcharges, cached discounts, and the full cost formula.
arrow_forward Learn
4
request_quote
Real-World Bills
The electricity bill analogy. Five worked examples with March 2026 pricing — from a $50/mo code assistant to a $12,000/mo agent fleet. The 90% underestimation problem.
arrow_forward Learn
Section 2

Infrastructure & Decisions

GPU economics, the API vs self-hosting decision, and the optimization playbook that can cut your bill by 60–70%.
5
memory
The GPU & Infrastructure Layer
The real estate analogy — renting (API) vs buying (self-hosting). NVIDIA’s GPU stack. The 84% margin on B200 chips. Why APIs win for 87% of use cases.
arrow_forward Learn
6
tune
The Optimization Playbook
The water conservation analogy. Model routing (40–60% savings), prompt caching (50–90%), distillation (5–30x), and how to combine them for 60–70% total reduction.
arrow_forward Learn
Section 3

Agents & Business

Why AI agents are inherently expensive, how to monitor and control their costs, and measuring ROI across your AI portfolio.
7
smart_toy
Agent Cost Engineering
The employee analogy — agents bill by the minute and sometimes spin in circles. Doom loops as cost disasters. The 4-layer monitoring setup. Teams without monitoring lose $8K–23K/month.
arrow_forward Learn
8
trending_up
AI FinOps, ROI & The Future
The portfolio analogy. AI FinOps as a leadership imperative. Hidden costs are 40–60% of total investment. 95% of pilots fail to show measurable returns. The future of AI pricing.
arrow_forward Learn
link

Related Courses

bolt
AI Infrastructure
GPUs & serving engines
layers
Context Engineering
Token budgeting & optimization
precision_manufacturing
Harness Engineering
Cost as a constraint
memory
Small Models & Local AI
Distillation & quantization
cases
AI for Executives
ROI & strategy