Skip to main content
NNextGen AI Learn
← All courses
intermediateProductionCostOperations

Cost-Aware AI Engineering

Ship AI features with a defensible bill — five habits that cut cost 40-70%.

SRE-grade discipline applied to LLM workloads: per-feature cost attribution, written token budgets, prompt caching at every stable prefix, model routing for the right call, continuous cost regression in CI, and the self-hosting math. Ends with a capstone that walks all five habits across one real feature, dropping the bill 87.5%.

Start courseCertify on CertQuests

7h

Duration

8

Lessons

920

Learners

Course map

Lessons unlock as you complete the previous one. Your progress is saved on this device.

  1. Lesson 1

    Why cost is now an engineering concern

    8m35 XP

  2. Lesson 2

    Per-feature cost attribution

    9m35 XP

  3. Lesson 3

    Token budgets per request

    10m40 XP

  4. Lesson 4

    Prompt caching at every stable prefix

    10m40 XP

  5. Lesson 5

    Model routing — the right model for the right call

    11m45 XP

  6. Lesson 6

    Continuous cost regression in CI

    9m35 XP

  7. Lesson 7

    Self-hosting math — when to leave the API

    10m40 XP

  8. Lesson 8

    A capstone — running the playbook on a real feature

    12m50 XP

Take next

Courses that pair well after — or alongside — Cost-Aware AI Engineering.

MA

Multimodal AI

Beyond text — vision, audio, video, in production.

intermediate · 7h

AS

AI Safety & Alignment for Engineers

Ship AI features that don't become incidents.

intermediate · 9h

L&

LLMs & Transformers

See inside the model — without the math wall.

intermediate · 9h