🤖 Design and deploy AI agents [Workshop]

Hey there.

You may have noticed that some professionals using AI feel that—even though they’re outperforming colleagues who don’t use AI—their increase in productivity has plateaued.

They've nailed a collection of important ChatGPT prompts, streamlined some emails, and maybe you've even built a few solid workflows. But all of those require a level of input and oversight.

At the same time, enterprise businesses are investing all their time into the next level of AI integration — truly autonomous agents.

Recently, OpenAI opened up access to the same technology powering enterprise transformations. And, inside The Rundown AI University, we’re helping members take advantage of this development to match the results of large teams and technical developers.

Once you know how to build effective AI agents, you’ll be able to:

Delegate complex work without constant supervision (so you can focus on strategy)

Before agents, every automated process broke down when something unexpected happened. You'd spend hours manually fixing workflows or dealing with edge cases. Unity used to have this exact problem with their customer support — agents would get overwhelmed when ticket volumes spiked, and human oversight consumed enormous resources.

Then Unity deployed AI agents with smart handoffs. Now their system automatically routes tickets between specialized agents: one sorts by urgency, another drafts responses, a third handles escalations, and a fourth manages follow-ups. As a result, they deflected 8,000 tickets and saved $1.3 million without adding a single human agent.

You can build similar delegation systems that:

• Handle your email triage and draft responses based on context and priority

• Manage your calendar by coordinating across multiple meeting types and stakeholders

• Process invoices and expenses with automatic categorization and approval routing

• Create content pipelines that research, write, edit, and publish without your involvement

For example: Individual knowledge workers can now build multi-agent teams to handle their most repetitive administrative tasks. Instead of spending 2 hours daily on email management, it’s possible to create a system that handles the vast majority of responses and only escalates what truly needs your attention.

Control outcomes automatically (so you never worry about AI going off-script)

Traditional automation fails because it can't handle exceptions effectively. You set up a workflow, it breaks on an edge case, and suddenly you're spending more time fixing it than doing the work manually. Amazon solved this by building guardrails into their recommendation agents — the systems that drive 35% of their revenue.

Amazon's agents operate within strict parameters. They can recommend products, adjust pricing within preset ranges, and personalize experiences, but they automatically escalate complex customer service issues to humans. This controlled autonomy lets them run massive automated systems while maintaining brand safety and customer satisfaction.

You can implement the same approach to:

• Deploy sales agents that qualify leads and book meetings but escalate complex negotiations

• Create content agents that maintain your brand voice but flag sensitive topics for review

• Build financial agents that process routine transactions but require approval for large amounts

• Set up research agents that gather information but verify sources before presenting findings

For example: Legal professionals can use guardrails to automate high-stakes processes with confidence. A legal document review agent can flag important clauses and suggest edits, but still ensure a human lawyer reviews anything involving liability or complex terms.

Monitor performance in real-time (so you can optimize and prove ROI)

The biggest problem with traditional automation was the black box effect. You'd set something up, hope it worked, and only discover problems when outputs were wrong. When Coinbase were building their crypto trading agents they needed complete transparency for regulatory compliance.

Coinbase's agent development team created their prototype to allow them to see exactly how each component functioned. When agents made trades, allocated resources, or assessed risk, every step was logged with reasoning, data sources, and confidence levels. This visibility let them optimize performance and demonstrate clear ROI to stakeholders.

You can achieve this level of transparency and:

• See exactly why your content creation agent chose specific topics or approaches

• Track which lead qualification criteria your sales agent weighs most heavily

• Understand how your research agent prioritizes and validates information sources

• Measure the actual time and cost savings from each automated process

For example: Busy consultants can see that their email agent is taking too long on certain message types, adjust its priorities, and immediately measure the impact on their daily workflow.

The opportunities are endless.

You’ve never been closer to completely outsourcing your most time-consuming tasks. But it won’t happen automatically…

Tomorrow, at 4 PM EDT, Dr. Alvaro Cintas is showing our members:

• What agents are and when you should build one (vs. a chatbot or simple automation)

• Key components of agent design: models, tools, and instructions

• How to orchestrate workflows with single-agent and multi-agent patterns

By the end of the workshop, you’ll confidently understand how to design, build, and safely deploy your own AI systems

This year agents are moving from experimental to essential — and not just for larger businesses. The professionals who learn to build agents now will lead their industries past the current AI plateau.

Unlock new possibilities in your career by learning how to create, deploy, and delegate important tasks to agents with a 14-day trial to The Rundown AI University.

See you in class,

Rowan & The Rundown Team

P.S. While others are still manually prompting ChatGPT for every task, our members are building systems that work autonomously to unlock career transformations, not just productivity gains. Join them by starting a 14-day trial at The Rundown AI University here.