Outcome School Newsletter
Outcome SchoolOutcome School by Amit Shekhar
| Platform |  | Pricing | Only free issues | Publishes | Twice weekly |
|---|---|---|---|---|---|
| Issues | 59 | Founded | 9 months ago | Last Issue | 12 days ago |
| Active | |||||
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outcomeschool.substack.comLatest Issues
LLM Inference Optimization
Techniques like KV Cache, Paged Attention, Flash Attention, Speculative Decoding, and Continuous Batching are what make LLMs fast and scalable in production.
Let’s learn all of these techniques one by one.
KV Cache in LLMs
In this blo...
Context Engineering, Routing, GraphRAG, Reflection, Speculative Decoding
Five new blogs. Each one breaks down a topic that matters in modern AI engineering: Context, Routing, Retrieval, Agents, and Inference Speed.
Let’s get into it.
1. Context Engineering
The model is the engine. The context is the f...
AI Agent, Memory, ReAct, RAG, Multi-Agent
We published a series of blogs on AI Agent:
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AI Agent Explained
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AI Agent Memory
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ReAct Agent
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Agentic RAG
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Multi-Agent Systems
Read them in this order. Each one builds on the previous.
1. AI Agent Explained
T...
RMSNorm, DeepSeek-V4, LoRA, RoPE, GQA, and Cross-Entropy Loss
It has been a productive few days. Six new blogs are now live on Outcome School, each one decoding a core building block of modern Large Language Models in the simplest way possible.
Here is a quick walkthrough of what is now published.
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AI Concepts Every AI Engineer Should Know
Foundations
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Tokens & Tokenization
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Embeddings
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Vector Similarity
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Context Window
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Temperature & Sampling
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Top-k / Top-p
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System / User Roles
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Inference vs Training
Models & Architectures
- LLMs...
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