In this lecture we discuss the best large language models (LLM's) to utilize when doing Salesforce development. We discuss LLM's like Claude Sonnet, Claude Opus, GPT5, GPT4, and Gemini.

In this lecture we find out what the best LLM is for administration work in Salesforce, what a context window is, and the benefit to switching our LLM's based on the task we are currently doing.

In this lecture we discuss which AI powered IDE's and IDE plugins like Cline, Cursor, and Kiro are best for Salesforce development, and which ones are not as good.

In this lecture we install and setup the Agentforce Vibes Visual Studio code extension so that we can start leveraging it for AI assisted development.

In this lecture we install and setup the Cline extension in both Visual Studio Code and IntelliJ so that we can start leveraging Cline when writing our code.

In this lecture we install and setup the GitHub CoPilot extension in IntelliJ so that we can start leveraging artificial intelligence (AI) when writing our code.

In this lecture we install and setup the AI powered Cursor IDE so that we can start leveraging artificial intelligence (AI) when writing our code.

In this lecture we install and setup the AI powered Kiro IDE so that we can start leveraging artificial intelligence (AI) when writing our code.

In this lecture we install and setup the AI powered Agentforce for Developers plugin so that we can start leveraging artificial intelligence (AI) for free when writing our code.

Notes that add additional useful information regarding the setup of our AI tools in this section.

In this lecture we discuss what model context protocol (MCP) servers are, what the model context protocol is, why we use it, and what MCP servers really are behind the scenes.

In this lecture we find out how to setup and run the Salesforce MCP server with our AI tools.

In this lecture we discuss what the biggest security concerns are when using Model Context Protocol (MCP) servers, especially MCP servers with the stdio type.

Notes that add additional valuable context to our this section about MCP servers

In this lecture we walk through what global and workspace rules are and how to best set them up with our AI tools. Additionally we write the markdown prompt files together so we see how to create and store them.

In this lecture we discuss the difference between plan and act mode for our AI agents/tools and which mode we should ideally start our AI agent conversation in.

In this lecture we discuss the 5 critical things to feed to your AI agent with each task you give it so that you can get the best results possible with each conversation/task you give your AI tools.

In this lecture we discuss how to create reusable prompts stored in markdown files. We also discuss why we use the markdown file type to store prompts, and we build a reusable prompt together!

In this lecture we discuss the benefits of feeding an AI agent a persona (or maybe lack thereof?). We test out the effectiveness of a simple persona to see if it makes any difference at all.

In this lecture we discuss some tips and tricks to make our prompts with our AI agents more likely to produce high quality results. Additionally we explore what extended thinking mode and why we might enable it when using out AI tools.

In this lecture we discuss how to have our AI tools generate a pseudo memory that we can leverage/use as reference when we need to move between context windows.

Notes that provide additional useful context for this section covering Artificial Intelligence (AI) prompting.

In this lecture we go over what slash commands are and why we might choose to utilize them over just referencing a standard markdown prompt.

In this lecture we go over how to setup, create, and call a slash command together for use with our AI tools.

Notes with supplementary information to learn more about slash commands with respect to our AI Tools

In this lecture we discuss how to best utilize AI agents/AI Tools as a beginner developer so that they are a way for you to learn faster and more efficiently as opposed to a crutch that you rely to produce any useful code.

In this lecture we discuss how intermediate developers can best leverage AI tools to advance their career's as opposed to AI tools becoming a crutch that you rely on to get your job done.

In this lecture we discuss how advanced developers can leverage AI tools to best assist them with their day to day tasks and make their life a little simpler.

In this lecture we are going to go over all of the steps necessary to prep for our project where we utilize everything we've learned in this course about large language models (LLM) and Artificial Intelligence (AI) agents.

In this lecture we discuss how to setup our AI agent for use in this project, and how to leverage free large language models if you don't want to pay any LLM fees while completing this project.

In this lecture we utilize our AI skills we learned throughout this course to build a Salesforce application in coordination with our AI Agent. This project is uncut and shows my entire process end to end to get the AI agent to complete its task.

In this lecture we are expanding upon part 1 of our project and using our AI agent/tool to refactor our Salesforce application that we just created. This lecture will focus on instructing the AI agent to accurately refactor existing code and add net new features to it.

In this lecture we use the gpt LLM to generate a flow that generates tasks for our Users. We discuss how to properly prompt our AI agent to make sure it has the context necessary to accurately generate config items in Salesforce.

These notes provide additional context and setup links to allow you to participate and build out the final project.

Thank you all so much for taking this course over AI Powered Salesforce development! I hope you enjoyed it and find it easier to utilize these AI tools now!