Agentic Ai Sys
Description
Agentic AI System Design with Case Studies
Installation
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open the source below and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
README
Agentic ML System Design
**From Messy Workflows to Intelligent Agents**
*By Ayush Singh | 2026 Edition*
*"Every business has a human doing 12 steps manually. Your job is to see those 12 steps and know which ones become ML, which become rules, which become LLM, and how they talk to each other."*
About
A comprehensive, case-study-first guide to designing agentic machine learning systems. This book teaches you to look at real, messy business workflows and redesign them into clean, intelligent systems using four building blocks: Triggers, Deterministic ML, LLMs, and Tools.
No fluff. No theory without practice. Ten real industries. Seven named design patterns. One design template you can apply anywhere.
Table of Contents
Part 1 — Foundations
| # | Chapter | Description |
|---|---|---|
| 01 | See the Mess | The universal messy workflow pattern. How to ask the right 3 questions. Why humans can't see their own workflows. |
| 02 | The Vocabulary | The 4 component types (Trigger, Deterministic ML, LLM, Tool). The Golden Rule. Agent complexity levels 0-3. Orchestration and memory. |
Part 2 — Case Studies
| # | Chapter | Industries | Key Lessons |
|---|---|---|---|
| 03 | Insurance, Recruitment, Accounting | Insurance, HR, Finance | The Golden Rule in action. Embeddings for matching. Multi-agent parallel processing. |
| 04 | Real Estate, EdTech, Marketing | Real Estate, Education, Marketing | Memory + personalisation. Lead scoring. Creative generation with human review gates. |
| 05 | Hospital, Support, Legal, Supply Chain | Healthcare, E-commerce, Legal, Logistics | Triage classification. Sentiment-aware escalation. Citation require |
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