Outcome School Newsletter
Outcome SchoolOutcome School by Amit Shekhar
| Platform |  | Pricing | Only free issues | Publishes | Twice weekly |
|---|---|---|---|---|---|
| Issues | 65 | Founded | 10 months ago | Last Issue | 9 days ago |
| Active | |||||
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outcomeschool.substack.comLatest Issues
vLLM, Function Calling, and World Models explained
How does vLLM work?
In this blog, we will learn about how vLLM works. We will also see why we need it, how it manages memory so cleverly, and where it is used in the real world to serve large language models to many users at once.
Serv...
How Prompt Caching, RAG, and GGUF actually work
This week I wrote six blogs. Each one takes a single idea and explains it slowly, in very simple words, until a complete beginner understands every single word.
Together they cover the pieces behind modern AI search, RAG, and local inferen...
AI Agents Learning Roadmap with Resources
If you want to learn AI Agents the right way, here is a complete roadmap. 16 blogs that take you from what an AI Agent is, all the way to building, evaluating, and shipping one in production. Read them in order.
1. AI Agent Explained...
Why is the Context Window limited in LLMs?
Let's understand in simple words.
The context window is the maximum amount of text an LLM can read at once. For example, GPT-4 has a context window of 128K tokens, which is roughly the size of a 300-page book.
So, why can't we jus...
AI Agents: Loop, SubAgents, Communication, Observability
This week was all about AI Agents: how a single one runs, how many of them split work, how they talk to each other, and how we see inside them.
Let’s get started.
1. AI Agent Loop
Every AI Agent has an engine that keeps it goi...
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