What's an Agent? Do We Have Some? Do We Need Some?

By Bryce Stuckenschneider | Published 2026-05-01 | Industry | 8 min read

One year in, and the conversation has officially shifted from 'should we look at AI?' to 'do we have agents yet?' Here's everything a business leader needs to know about agents right now — what just happened, what an agent actually is, and five real ones we've already built.

It's Friday and time for another Huddle. This one is a big one for us — today is the one year anniversary of Trailblaze Labs. We're grateful for the companies (and the people behind them) who trust us to help translate the most complicated era in the history of technology.

This issue is everything I'd want a business leader to know about agents right now. What just happened, what an agent actually is (and isn't), and five real ones we've built with clients in the last few months.

Vocab Corner: Agent vs. Chatbot

If you're going to navigate the next 18 months of AI conversations, the chatbot-vs-agent distinction is the one to internalize.

A chatbot answers your questions. It waits for prompts, doesn't carry memory between sessions, and lives inside one window. An agent does the work. It has access to your tools and systems, holds memory across runs, can be triggered by a schedule or a Slack message, and can take real actions like sending an email, updating a spreadsheet, or pulling data from your CRM.

A chatbot answers. An agent acts.

A chatbot lives in a window and waits for you to open it. An agent has its own logins, its own memory, and its own reasons to be working at 6am before you've had your first coffee.

Headlines That Actually Matter

OpenAI's Workspace Agents (April 22)

OpenAI introduced Workspace Agents inside ChatGPT on April 22, framing them as the direct successor to Custom GPTs. They're built on Codex, run in the cloud, and plug into Slack, Salesforce, Google Drive, Notion, and Microsoft 365. You build one, share it with your team, and it keeps working even after you've closed the laptop.

Why this matters: Custom GPTs were one-person creations that waited for someone to ask them a question. Workspace Agents are shared, persistent, and able to take action across multiple tools. That's the chatbot-to-coworker change.

Google's Gemini Enterprise Agent Platform (also April 22)

Google announced the Gemini Enterprise Agent Platform from the Cloud Next stage in Las Vegas. It's the evolution of Vertex AI, designed as a single place to build, govern, scale, and optimize agents across an organization. They've baked in 200+ models in the Model Garden, a low-code builder called Agent Studio, an Agent Registry to track every agent in the company, and an Agent Gateway that enforces security and prompt-injection protections.

Why this matters: Google is making the case that if you're going to deploy agents at any kind of scale, you'll want them on a platform that handles identity, security, and governance from day one.

Microsoft Agent 365 (live today, May 1)

Microsoft's announcement is less about a new agent you'll go build and more about the wiring underneath. Agent 365 is the layer that lets IT and security teams see every agent running across the business, who built it, what it can touch, and whether it's behaving. Their internal team is already running 500,000+ agents on it.

The "OpenClaw" Curveball

OpenClaw is an open-source AI agent you run on your own hardware — most commonly a Mac Mini — and connect to messaging apps like WhatsApp, Telegram, and iMessage. It launched in late 2025, hit 214,000 GitHub stars by February, and inspired thousands of developers to set up dedicated Mac Minis as personal "Chiefs of Staff."

Five Digital Team Members We've Already Built

The Data Analyst. A client was paying for PowerBI plus a data analyst to refresh dashboards. We built an agent connected to their data warehouse that takes natural-language questions and responds with the chart and the narrative behind it.

The HR Generalist. The agent has read the entire employee handbook, the relevant state and federal regulations, benefits administration, and the company's internal policies. When a question comes up about FMLA, ADA accommodations, or how to write up a sensitive conversation, she has a thoughtful first draft in 30 seconds with sources cited.

The Leadership Coach. We trained an agent on the personality profiles of an entire organization — 200+ people. Any leader on that team can now ask it for help prepping for a 1:1, a quarterly review, or a hard conversation.

The Chief of Finance. A client with a Director of Finance retiring after 20+ years was facing a six-month gap. We built an agent loaded with their accounting practices, vendor relationships, and the "why-we-do-it-this-way" context.

The Private Eye. A competitive intelligence agent that tracks competitor product launches, industry events, pricing changes, and key hires. It runs on a schedule and pings the marketing leader via email the moment something material happens.

Training Tip: Pick the Boring One First

The mistake I see businesses make is building the cool agent before the useful one. When clients ask where to start, I tell them to find one workflow that hits three conditions: it happens repeatedly, it currently lives across two or three different tools, and the person doing it doesn't enjoy it. That's the agent that should exist.

The Buzzer

Agents in 2026 remind me of a young, talented team in training camp. The plays are starting to work and the chemistry is showing up, but you'll see a missed handoff every once in a while. The teams who draft early and develop their own talent are going to look very different in two years than the teams who sit on the sidelines waiting for a finished product.