🐙 AI Agents

With clear and meaningful business value, these octupuses (octupi?) are the breakout stars of 2025! If you’ve ever interacted with one of those pop-up chat interfaces on a website (“How can I help you today?”), imagine that only smarter, context-aware, and capable of doing doing more meaningful tasks with clients directly, or behind the scenes supporting you and your team.

At their core, AI Agents are digital assistants that can access your systems, interpret prompts, and take multi-step actions based on user intent. Depending on how advanced they are, they use those tentacles to fetch data, update records, trigger automations, and escalate issues in real time.

To keep it simple, we’ll talk about AI agents in three tiers. In general, start with low-hanging fruit in Tier 1 and work your way up as business needs and budgets allow. 

🔑 Remember: the clearer your business goal, the better the outcome.

⚙️ Tier 1: Out-of-the-Box (No-Code) Agents

These are the AI assistants now baked into familiar tools you’re probably already using. You could consider the licensed version of Microsoft 365 Copilot Chat, which connects to M365 Apps to be an agent of sorts (simliar concept). Others may be familair with Breeze (HubSpot AI), or Zoho One’s Zia.

These tools feel familiar because the interface is mostly chat-based, only now they can interact directly with your files, calendar, or CRM to pull answers or execute actions.

There’s little setup required, aside from possibly purchasing an upgrade or add-on, then learning how to use it.  Then simply ask questions like:

• “What’s the status of my last invoice?”
• “Summarize today’s client emails.”
• “Show me new leads from last week.”

🔧 Tier 2: Low-Code, Workspace-Aware Agents

This next level requires some setup and configuration for strategic deployment, but nothing too cumbersome.

It includes tools like Coda AI, Notion AI, and enhanced GPTs that can access and respond to your internal files, docs, or structured workspaces.

These agents can be further configured to:

• Pull from internal knowledge bases
• Auto-generate content or insights from project or data tables
• Suggest or create tasks based on page context or user input

These tools start to feel like “mini operations managers”, especially if you’ve already built out templates, project plans, SOPs, or dashboards. They’re responsive and adaptable within their environment, but still depend on well-structured data and clearly scoped tasks.

🧠 Tier 3: Custom Agents with Embedded Knowledge & Triggers

Here’s where things get a lot trickeier and more costly, but with a lot of potential for certain businesses and industries. 

Using platforms like Microsoft Copilot Studio, Google’s Vertex AI Agent Builder, or in some cases, advanced API-connected GPTs, you can now build workflow-powered agents that:

• Trigger multi-step workflows based on condition
• Maintain session context across tools and trigger actions based on evolving input
• Apply advanced lead qualification criteria across multiple data points
• Use RAG to more effectively and selectively pull from knowledge bases and other sources

These setups can offer tremendous value to the right businesses, but they require more planning, permissions, and technical configuration. Honestly, these start to get into overkill territory for most freelancers and small teams. 

For a more agile alternative in the same ballpark, Zapier’s AI Interfaces let you create lightweight, chat-style experiences that combine AI + automation logic without code or complexity. It’s a solid middle-ground if you want to trigger smart workflows after exploring all tier 1 and 2 options, but without building a full-scale AI agent.

🚧 An Eye Toward Agentic AI

If you’re considering Tier 3 solutions, keep an eye on advances in Agentic AI before dropping too much money on customization. Technically parts of this technology are already inherent in Agents, but, I digress. 

Where AI Agents are designed to respond to you, Agentic AI is built to pursue goals with less input, shifting away from traditional query/prompt/command patterns and toward more autonomous decision-making. 

Think of it as the ambitious younger sibling watching what the big sibling agents do, then one-upping them and taking all the credit. We’re not quite there yet as most advanced Agentic models are still in enterprise labs, but the shift is coming.

🌐 What Else is Lurking in GenAI’s Shadow?

Before we wrap up, do know Agents and Agentic AI aren’t the whole story. They are just what's most important to spotlight right now. Next week, we’ll explore other categories that aren’t “must-do-now,” but will absolutely influence your tech investments soon:

• ⌚ Wearables are leveling up and due for a major seismic shift
• 🧠 Smart Devices are evolving into Smart Environments
• 💻 AR/VR is still lurking and will eventually be a disruptor +
• 📲 Exploring where Meta AI, Meta Business Suite + Metaverse stand to change the business landscape in that AR/VR Space
  
• 💼 Exploring where Microsoft is going in that Arena. Don't forget about their after Activision acquistion some time ago
  
• 🍎 Will Apple keep up and stay competitive in the small business or enterprise space after its lackluster debut of Applie Intelligence & Vision Pro? 

🎯 Bringing It All Home

Beyond all the constant hype, AI Agents are your best bet for scalable, high-ROI time savings. Especially when you build them around real business needs, not just "buy and try".  Even entry-level agents can save hours of admin time, especially when connected to your calendar, inbox, or CRM.

• ✅ Focus on Tier 1 first
• ⚙️ Move to Tier 2 when your internal systems are ready
• 🚀 Don’t touch Tier 3 until you’ve clearly mapped out the ROI (and by then we may be in a different landscape). 

Just remember that AI Agents are most valuable when upfront integration is minimal. They’re not plug-and-play magic. You get out what you put in. If you: 

 • Want it to prioritize internal info over internet answers, you’ll need to build and connect your Knowledge Base properly

 • Want it to trigger automations, you’ll need to define logic, roles, and conditions.

 • Want it to act  more like a real team member, you need to train it, test it, and manage it.

Investment in the latest tools and tech only work when you know what problem you’re solving, whats just  rebranded hype,  whats actually helpful, and whats coming next. So before you rush to adopt the next AI tool, latest iPhone, or wearable, ask yourself: What’s the actual business problem? Is it an issue tech can solve well, or is it another type of issue. What existing alternatives are there ? 

📆 Still Need Help? Click below to scheuled some time with me. 

And don't forget about the AI Guide I  mentioned above that will walk you through the fundamentals.