29-Mar-2025
Today I attended and contributed a talk to the Boston Code Camp 38 (yes, impressively, the 38th edition of this event). I made the trip with Maura (she gave a talk combining Cryptocurrency And Agentic AI) and Kevin (he gave a talk on Top 10 AI Security Risks). and we got to hang out with and chat with so many cool people from the Boston technology community.
The description of my Let’s Build a Goal-Oriented AI Agent Using Semantic Kernel talk follows, followed by a couple of relevant links, then the slide deck.
Imagine an AI not limited to answering individual questions or chatting, but actively working towards a goal you’ve assigned to it.
In this session, we’ll explore the building of an AI Agent – an autonomous actor that can execute tasks and achieve objectives on your behalf.
Along the way we will demystify:
1. 
LLMs – What is a Large Language Model (LLM)
2. 
Tokens – What is a token and what are its roles
3. 
Embeddings – What are embedding models and vectors and what can they do for us
4. 
Prompts – Beyond the basics
5. 
Tools – How can these be created and accessed using Semantic Kernel
6. 
Agents – Let’s put all these concepts to work!
The end result will be the core (or perhaps ‘kernel’ 
) of an AI Agent – your virtual coworker willing to handle tasks on your behalf without. It will be built in C# using the open source, cross-platform Semantic Kernel library.
This talk assumes user-level familiarity with LLMs like ChatGPT or Microsoft Copilot and basic prompting. Anything else will be explained.
(stole photo from Robert Hurlbut)
A couple of prominent links from the talk are:
You can find the Fun with Vectors tool here: https://funwithvectors.com/
You can find the OpenAI Tokenizer tool here: https://platform.openai.com/tokenizer
Download the slides here: