Understanding Agentic AI
April 28, 2026
AI is evolving from a reactive knowledge base into a proactive doer. Learn about the mindset shift you need to have to master this new era of Agentic AI.
It's your weekly dose of clarity and insight on all things tech & business from Dream in Digital! Each week, I'm here to share my thoughts to help you make the most of today's technology and build a business that genuinely supports the life you want to live.
This Week’s Core Focus:
Shifting to Agentic AI
The difference between agentic (autonomous) AI and generative (regular) AI is that while regular AI acts as a reactive knowledge base, agentic AI can start acting on your behalf to complete tasks for you. It doesn't just give you the instructions anymore, it can actually use its own instructions/guidance to start doing the work for you. I have heard of “Agentic AI” many times before, but was still unfamiliar with how it actually worked. That’s why, this past week, I decided to attend a workshop focused on building an AI assistant. Here were some of the things that started to click for me during the workshop:
Connect: To make an AI "agentic," you have to connect it to your platforms & systems. It’s the difference between an assistant who knows how to file, and one who actually has the keys to your filing cabinet to do the filing for you.
Train: Another big takeaway I had was the idea of being able to move from training people to be employees, to now training AI and using Agents instead. Will this be an “apples to apples” replacement all of the time? Absolutely not! However, this is a major shift in the way business owners will think about and use people & technology. Similar training techniques and requirements, but now, instead of training someone who could potentially leave the company one day, business owners can better retain their intellectual property and experiential data by training AI Agents to do certain tasks instead.
Manage: Once you connect your tools and train your Artificial Intelligence (AI) platform to take on agentic capabilities, the next crucial shift is for you to truly start thinking of the AI as a worker. That means that you need to start thinking like a manager (of AI Agents) now, and adjust your prompting accordingly. See an example of this in this week’s “Tech Tip” below.
Tech Tip of the Week:
Creating an Executive Assistant Agent
Whether you use Google’s Gemini, Chat GPT, or Claude, creating an AI Agent typically follows a similar four-step framework, starting with creating a Gem (Gemini), Custom GPT (GPT), or Project (Claude):
Define the Persona (The Brain): Give the AI a specific role to set its expertise and perspective.
Example: "You are a highly organized Executive Assistant for Your_Company_Name in the Your_Company_Industry Industry specializing in minimalist and essentialist business operations. Your goal is to help the founder prioritize & streamline tasks, while supporting them with administrative work."
Provide the Context (The Memory): Within the Gem/GPT/Project settings or knowledgebase, upload your specific brand voice guides, SOPs, and project templates. This ensures the AI can remember how you work, without you having to re-upload files, or provide additional context, every time you chat.
Enable the Tools (The Hands): This is where the AI becomes "Agentic." Navigate to your AI platform’s settings and look for “Connections” or “Integrations.” By toggling these on, you give the AI "hands" to reach into your other apps.
Google Workspace: Reach into Drive, Docs, Gmail, and Tasks.
Project Management: Connect to tools like Monday.com, Notion, or Asana.
Communications: Link to Slack, or a platform like HubSpot or Klaviyo, to manage outreach.
Manage with Prompts (The Work): Once the brain is built and the tools are connected, you need to prompt the AI as a manager giving an assignment to a worker.
Example: “Review my Google Task Lists and help me prioritize my work day with the top 3 most important tasks to complete today.”