3 LLM Cost Optimization Tricks Every Engineer Needs
Stop wasting tokens.
In this video, I’ll show you 3 AI token-efficiency hacks that instantly cut your LLM costs by up to 50% — with real examples engineers can use right now.
You’ll learn how to:
✅ Compress prompts without losing meaning
✅ Batch & reuse context the right way
✅ Use model-cascading to save tokens automatically
✅ Reduce output size with structured responses
✅ Build smarter, cheaper AI workflows for engineering tasks
Whether you’re using ChatGPT, Claude, Gemini, OpenAI API, Anthropic, or local LLMs, these techniques work across all models.
If you build AI tools, write technical…
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Chapters (5)
0:36
Intro on LLM Model token costing
0:37
How to batch multiple tasks into one AI request
1:34
How to reuse context to cut LLM cost
2:38
How to use model cascading to save tokens
3:16
How to structure AI outputs to reduce token count
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