Understanding, Creating and Deploying Agents (3-part series - Feb 4, 11, & 18)

Understanding, Creating and Deploying Agents A three-part course for market research and insight professionals.
February 4, 11 & 18

You can still register for this course. If you register before Wednesday 18 February, we will send you the slides and recordings from Week 1 & Week 2 and sign you up for Week 3.

Agents are rapidly becoming the key way that AI delivers systematic, scalable benefits beyond one-off experiments. In this course you'll gain hands-on experience designing, creating and deploying agents for everyday tasks, from workflow automation to core research and insight challenges.

The Course
Three 2-hour interactive online lessons, delivered by Ray Poynter. Each lesson will be accompanied by optional hands-on tasks and practical exercises to help you apply what you've learned. You will receive access to the recordings, slides, and supplementary materials after each lesson.

Lesson Outlines
Lesson 1: Foundations of Agents An introduction to agents and their transformative potential for research workflows. You'll see real-world examples of agents in action across different research scenarios and learn the fundamentals of creating instruction-based assistant agents in Gemini, Copilot, and ChatGPT. We'll work through a decision framework to help you identify which tasks and processes in your workflow would benefit most from agent deployment. By the end of this lesson, you'll have created your first simple agents and received example projects to explore and adapt for your own needs.

Lesson 2: Enhancing and Managing Agents Building on the foundations from Lesson 1, you'll learn how to transform basic agents into more powerful tools by adding custom knowledge bases, external connections, and scheduling capabilities. We'll cover essential practices for testing, iterating and maintaining your agents to ensure reliability and accuracy. The lesson will also introduce workflow automation platforms like Zapier and N8N, showing how these tools can connect your agents to existing systems and create seamless automated processes that handle repetitive research tasks.

Lesson 3: Advanced Capabilities and Deployment The final lesson explores advanced agent features including code interpretation, API integrations, and multi-agent orchestration. You'll learn how to implement Human-in-the-Loop practices to maintain quality control and address ethical considerations in agent deployment. We'll examine third-party agent creation platforms that can help you scale solutions across your team and organization. By the end of this lesson, you'll understand how to build enterprise-ready agent systems that deliver consistent value while maintaining appropriate oversight and governance.

What You Will Learn

• What agents are, why they're transforming research workflows, and where to deploy them for maximum impact
• How to audit your current workflow and identify high-value opportunities for agent implementation
• How to create and customize agents in ChatGPT, Gemini, and Copilot – plus an overview of alternative platforms
• How to evaluate, test and maintain your agents to ensure they deliver reliable, high-quality outputs
• How to use workflow automation tools like N8N to create sophisticated multi-step solutions
• How to leverage third-party tools to scale agent capabilities across your team

Who Is the Course For?
This course is for market researchers, insight professionals and team leaders who want to move beyond AI experimentation and start leveraging agents to gain systematic, scalable benefits. The course does NOT require coding skills or technical experience, but does assume reasonable familiarity with at least one of ChatGPT, Gemini, or Copilot. To fully benefit from the course and complete the practical exercises, you should ideally have paid access to at least one of these platforms.

One ticket three sessions

• February 4 - 10am to midday New York (3pm to 5pm London)
• February 11 - 10am to midday New York (3pm to 5pm London)
• February 18 - 10am to midday New York (3pm to 5pm London)

Ray Poynter, the course instructor
Ray has spent nearly five decades in market research, contributing to industry transformations from computer-assisted interviewing to AI-enhanced insights. He founded NewMR, co-founded ResearchWiseAI, and serves as a Fellow of the Market Research Society and past President of ESOMAR.
Today, Ray helps insights professionals leverage AI practically through his Mastering AI for Insights Professionals course and consulting work. His focus is on what works now, from intelligent agents to automated analysis, rather than future promises. He is the author of two Wiley handbooks on online and mobile market research, and he brings a pragmatic, evidence-based approach to AI adoption in the insights industry.

Want to know more about our thinking?
Here are three recent blogs related to the use of AI.

• How are you measuring the ROI of AI? Ray Poynter explores how organisations can judge whether AI investment is paying off. He contrasts upbeat and pessimistic studies, then introduces ideas such as the “jagged frontier” where gains in one task create risks elsewhere. The post outlines practical metrics and approaches tailored to knowledge work and market research today. Click here to read the full post.
• 10 Key Words for 2026 In a quick year-ahead note, Poynter lists ten terms he expects to shape 2026, from agentic systems and orchestration to context engineering and grounded truth. He links each word to practical implications: compute constraints, evaluation stacks, multimodal models, “AI-slop” contamination, and debates about doomer narratives and risk in practice globally. Click here to read the full post.
• The Synthetic Data Landscape This essay maps the territory of synthetic data in market research. It clarifies definitions from the ICC/ESOMAR Code, separating synthetic personas from synthetic datasets, and explains how they are created and used. Poynter proposes categories such as augmentation, synthetic, anonymised synthetic, and randomised synthetic, alongside evaluation and governance needs. Click here to read the full post.

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