3 KiB
Executable file
3 KiB
Executable file
Lesson 01 | Course Agenda
Links
Notes
course agenda
- no need for code
- walk through step by step builds
- 15 builds
course topics
- ai agents
- n8n foundations
- step by step workflows
- apis & http requests
- ai agents tools & memory
- multi agent architecture
- prompting
- webhooks
-
mcp servers
- what it is
- hosting setup
- lessons
what are ai agents
- what is it at its core
- what can it do
- why do we need them
what it does
- take input
- process input
- get output
how to use it
-
send the output to a tool
- gmail
- latex
- anything
-
when we add an LLM to a tool we get
- ai workflow
- ai agent
workflow vs agent
ai workflow
pros
- reliability
- cost efficiency
- easier debugging and maintenance
- scalability
what we are doing
- input
- tools to process input
- call the LLM
-
tool chain
- process output before final output
- final output
practical example
-
hubspot tool
- passes in lead
-
perplexity tool
- does research
-
LLM
- takes research
- send email
ai agent
how it works
- takes input
- has a set of tools at it's disposal
- uses internal logic to decide what to do
disadvantages
- not linear
- expensive
when to use it
- if the task is unpredicatable
anatomy of an ai agent
outside features
- input
- LLM
- output
in the agent
-
brain
-
LLM
- anthropic
- gemini
-
memory
- long term
- short term
- it won't forget what we need it to remember
-
-
instructions
-
system prompt
- differnt than input in that it stays the same
- input changes regularly, ie every interaction you have with chatgpt
- what is your role
- what do you do
- this is what you got to work with
-