Reading List

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 This page is my reading list of various articles on AI and Cloud and some random notes.

Memory Management in ADK

Production Ready AI Systems

Tricks for AI Assisted Coding


























Tools
Nano Bot (OpenClaw alternative)


Evals

Pending



New Agentic Fw



Inferencing

Ideas

ML System Design:
🔹Youtube videos:
1. How to Master ML System Design
→ https://lnkd.in/d89ywdkp
→ Step by step guide (went through it - its good)

2. Stanford MLSys Seminars (playlist)
→ https://lnkd.in/gP3UDqwn
→ How Netflix/Uber actually scale

🔹Interview examples:
1. Spotify ML Question - Design a Recommendation System 
→ https://lnkd.in/dr87ADq8

2. Instagram ML Question - Design a Ranking Model 
→ https://lnkd.in/dqMxqgNc

🔹 Github Repo:
1. System Design Primer
→ https://lnkd.in/gmAg4nBb
→ Master the patterns that matter


Protocols:
• ACP – Standardizes cross-agent workflow communication
• AGP – Secure gateway between agents and enterprise systems
• Tool Abstraction Protocol – Makes tools structured and callable
• OAP – Open interoperability across frameworks
• RDF-Agent – Knowledge graph–driven semantic reasoning
• AgentOS – Runtime for long-lived enterprise agents
• TDF – Structured task planning and constraints modeling
• FCP – Safe function calling and structured execution




Embedding models:
static-retrieval-mrl-en-v1
all-MiniLM-L6-v2 model 



Skills Vs Tools
Every tool's schema, name, and description are added to the system prompt, consuming significant tokens upfront.
Skills are stored as Markdown files. They are only loaded into the prompt when needed. (Progressive disclosure)

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