Craig Brandt
Director of Business Development
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Craig Brandt leads business development at ArchitectNow, a Microsoft Solutions Partner that builds custom software, AI applications, and cloud solutions for mid-market and enterprise clients across North America. ArchitectNow holds four Solutions Partner designations (Digital & App Innovation, Data & AI, Azure Infrastructure, and Support Services) plus the AI Apps on Azure Specialization, putting it among a small group of partners with credentials across both the AI and cloud sides of the Microsoft ecosystem.
Based in Tampa, Florida, Craig works with executives many industries who are trying to figure out what AI and cloud should actually do for their business. His role puts him at the intersection of sales, strategy, and technology, which is where he developed his point of view on AI: the real opportunity is in giving it complete jobs and letting it execute.
He's a salesperson by trade, not an engineer, and that's exactly why his perspective on AI lands with non-technical, and technical audiences. He uses AI in his own work every day, which is where his point of view comes from. He believes the next decade of AI adoption will be defined by business users who are willing to rethink how they work, and use AI as a coworker that you delegate tasks to.
Kill the Chatbot. Build-A-Coworker: Give Your Team AI That Executes, Not a Chatbot That Suggests
The world has changed, and in the last 6 months the world of AI has rapidly accelorated. Most organizations are still treating AI like a smarter search engine; typing prompts, getting answers, copy-pasting results, and wondering why the productivity gains haven't shown up. The problem isn't the technology. It's the mental model.
The next wave of AI value isn't conversational. It's operational. It comes from giving AI complete jobs, workflows that previously required a person, and letting it read the inputs, make the calls, draft the outputs, and queue them for human approval. Not a chatbot that suggests. A coworker that executes.
In this session, Craig shares the workflows he built, the patterns that worked, and the ones that failed.
You'll leave with:
A framework for spotting which workflows in your department are ready to automate
The Read → Decide → Draft → Approve → Execute pattern that separates AI tools from AI teammates
Why "prompt engineering" is the wrong skill to invest in, and what's actually driving real business ROI
Why human-in-the-loop isn't a constraint on AI, it's the unlock that makes AI valuable to a business
Why your competitive advantage in 2026 won't come from having AI, it'll come from how you deploy it
For executives and business users in any department. No technical background required.
Chatbot Killed: Now the Agents Are Lying
You killed the chatbots. Good. The agents you replaced it with are the new problem.
They do real work now. They also make things up, lose the thread, and do the wrong thing with total confidence, and they look great doing all of it. That confidence is why most agent projects stall before production. Nobody can promise the thing will not lie to a customer.
I'm not a developer. I run sales and marketing motions at ArchitectNow. And I delegate a big chunk of some of my day to day tasks to a team of AI agents.
Here's what I learned. Most people try to build one agent smart enough to do the whole job. That's the trap. The version that actually ships looks more like a team you manage: a handful of narrow specialists, a manager over them, and one agent whose only job is to catch the others lying.
This is the case study, with the real system on screen. How I hired the team, the agent that interrogates the rest before anything ships, the dumb checks I trust more than the smart ones, and where I still keep a human in the loop.
One agent does the work. One agent catches it lying. I'll show you exactly how mine fit together.
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