Building Agentic AI Applications with Large Language Models (BAALLM) – Outline

Detailed Course Outline

1. Fundamentals of Agent Abstraction and LLMs

  • Discuss LLM capabilities & pitfalls
  • Introduce agents as a task decomposition abstraction.
  • Demonstrate minimal agent with free-text LLM calls.

2. Structured Output & Basic Fulfillment Mechanisms

  • Bottlenecking LLMs with JSON/task-based outputs.
  • Ensure domain alignment & stable schema enforcement.
  • Introduction to cognitive architectures.

3. Retrieval Mechanisms & Environmental Tooling

  • Formalize environment access strategies for agents to interface with other systems.
  • Develop tool interfaces for external data repositories (DBs, APIs)
  • Use vector-RAG-coded for semantic retrieval over document sets.

4. Knowledge Graphs & Document Graphs

  • Plan progression of data from raw docs to canonical forms.
  • Motivate threshold/equilibrium objectives for driving event loop.
  • Build state pools/ontologies for robust domain coverage

5. Multi-Agent Systems & Frameworks

  • Decompose tasks among specialized agents
  • Formalize communication buffers and process distribution schemes.
  • Differentiate between different frameworks and their unique approaches.

6. Data Flywheels & System Hardening

  • Capture usage logs, refining domain constraints, or sub-models
  • Implement human-in-the-loop oversight for error correction
  • Iterative improvement & pipeline simplification using real/synthetic data.

7. Scaling & Productionalization

  • Discuss production-oriented considerations like resource management, concurrency, resource utilization, multi-tenancy
  • Motivate framework-agnostic modular deployments (meta-frameworks) and their selection criteria.

8. Final Assessment

  • Deploy an agent endpoint that can support multiple different interactions.
  • Run a distributed dialog loop across the deployed server to assess satisfaction.

9.1. [Optional] Real-Time Agents

  • Discuss multimodal considerations and agentic use-cases that interact with the physical world.
  • Explore recent advances in robotics, audio systems, and world models.

9.2. [Optional] Responsible Agents

  • Discuss common failure modes in software design that introduce unfairness, liability, and poor software experiences.
  • Consider checks-and-balances systems, standards creation, and evaluation needs.