CSOT GenAI/Agentic Track 2026

Introduction

Welcome to the GenAI/Agentic track of CAIC Summer of Technology 2026.

Five weeks. One project, built entirely from scratch.

This track takes you from your first LLM API call to shipping a real, working AI agent — the kind that doesn’t just generate text, but takes action. You’ll implement every layer by hand: tool dispatchers, agent loops, memory systems, execution environments. No frameworks doing the heavy lifting (Langchain is overrated anyway). Just you and the primitives.

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Why the Agents Track?

AI powered engineering is moving fast — from prompt design to orchestration to smarter checks to make it harder for developers to shoot themselves in the foot. Here’s what this track gives you:

• Manual Orchestration Mastery: Understand the exact mechanics of tool calling, function schemas, and multi-turn loops by coding them yourself — without high-level abstractions hiding the details.

• State Management Architecture: Move beyond stateless APIs by designing context buffers, working memory, and evolving long-term memory stores that persist across sessions.

• Real-World Execution Capabilities: Bridge the gap between text generation and environment interaction — your agent won’t just describe what to do, it’ll do it.

• Leaderboard-Driven Validation: Each week ships to an auto-graded eval set. You know exactly where you stand.

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What Are We Building?

The project reveals itself as the weeks progress. Each week you add a new capability layer, and by Week 5 those layers compose into an agent you could actually hand to someone.

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Weekly Roadmap

Week 1: LLM APIs, API-Key Safety & Conversation State

Foundation week — get the fundamentals right so everything built on top of them is solid.

Focus on:

• Understanding LLM API mechanics: requests, responses, tokens, and how to read a response object properly.
• Understanding chat templates: How the conversation is represented as system, assistant and user dialogues.
• Strict API-key hygiene using .env files, python-dotenv, and .gitignore — keys that leak cost you more than just money.
• Managing the stateless nature of LLM APIs by building manual, role-assigned conversation history from scratch.

✅ Deliverable: A terminal chatbot that holds a coherent multi-turn conversation, with the API key loaded from the environment and never touching the source code.

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Week 2: Tools, Agents, and TUIs

The heart of the course. A tool is a contract between your code and the model. An agent is a loop around tool calls. Once you see it, you can’t unsee it.

Focus on:

• Implementing tool calling from scratch using a custom text format — so the SDK abstraction is never magic.