What You'll Learn
In this advanced course, participants will explore the cutting-edge of agent and tool engineering within the context of Large Language Models. From writing effective system prompts to designing autonomous agents capable of evolving their own functionality, this class covers the comprehensive skills required to innovate in the field of AI and machine learning. Participants will learn how to harness open-source tools, manage vector stores economically, and create complex agent architectures for collaborative and secretive tasks.
Course Schedule
Week 1 2 sessions
Tool Users
Focuses on writing effective system prompts for regularized output or tool use and creating agents who can utilize tools efficiently.
Automate Agent Creation
Covers creating benchmarks for LLM performance evaluation, and writing agents capable of creating tools and other agents.
Week 2 2 sessions
Tool-Using Agents with RAG
Explores the use of open-source tools designed for LLMs, managing knowledge in vector stores, and hosting vector stores economically.
Common Agent Patterns
Delves into writing agents that can take autonomous actions based on schedules or event triggers.
Week 7 2 sessions
Self-Improving Agents
Focuses on creating self-improving agents, using critical theory, and applying expert strategies for prompt optimization.
Swarms and Swarm Architecture
Teaches about creating swarms of agents for collaboration on complex goals and constructing effective agent architectures.
Week 8 1 session
MetaSwarms
Covers constructing meta-swarms with information mediators and creating an information hierarchy among agents for enhanced secrecy and collaboration.
All times shown in Pacific Time
Where This Class Leads
What you leave able to do
- reconcile agents from different toolchains into one run
- select among agent architectures
- synthesise a memory hierarchy for an agent
- synthesise a retrieval over relationships not just similarity
- synthesise a self extending agent behind a review gate
- synthesise an accountability regime for an unattended agent
- originate an operating model for managed agent teams
How you show it. A written operating model in use by at least two people, with a recorded instance of it catching a failure that the previous arrangement missed.
It sits on one path
🤖 Build production AI systems from prompt to deployment. 10 of 12 after Advanced Retrieval Augmented Generation · before Agentic SDLCAbout 24 hours of practice sit behind this one. See what your hours buy.
Who Is This Course For
Students with foundational knowledge in Prompt Engineering and Agent Engineering, looking to specialize in advanced agent and tool creation and management.
Who this is for & what you'll need
Join the Course
Pay what you can - accessible learning for all
We use a suggested price to prevent abuse, but if you need a larger discount, apply for a scholarship. We offer 100% scholarships — no one is turned away for lack of funds.
Frequently Asked Questions
How are classes delivered?
All classes are live and online via video call. Sessions are recorded so you can review them later if you miss one.
What does "pay what you can" mean?
We show a suggested price, but you can pay any amount. If you need a larger discount, apply for a scholarship — we offer 100% scholarships and no one is turned away for lack of funds.
Do I need prior experience?
🟣 Pro engineering. Built for working engineers.
What do I get when I enroll?
Live sessions with the instructor, access to course curriculum materials, community access via our Matrix chat server, and recordings of all sessions.
Want to schedule this course for your team?
Contact us: [email protected]