Zapier Copilot Lets Users Build Custom AI Research Agents for Content Strategy.

Zapier users can now build custom AI agents using Copilot, the platform's conversational assistant for workflow automation. The feature allows users to create specialized research agents that monitor industry trends, identify high-demand topics, and generate content ideas without manual data gathering.

Speaker and coach Anthony Trucks demonstrated the capability in a LinkedIn post, describing an agent he built to track trending topics in the professional speaking industry. The agent monitors what event planners are searching for and converts those insights into content scripts and ideas.

Zapier Copilot works through natural language prompts. Users describe the workflow they want to automate, and Copilot generates the necessary steps, connecting to relevant apps and data sources.

Trucks' agent performs three core tasks: spotting trending topics in the speaking world, flagging what event planners are actively searching for, and turning those insights into usable content ideas and scripts. The workflow runs automatically, eliminating the need for manual trend monitoring and topic research.

The approach addresses a common content creation bottleneck. Many creators struggle to identify which topics will resonate with their target audience, often relying on intuition or outdated playbooks rather than real-time market data.

Copilot represents a layer on top of Zapier's existing automation infrastructure. Where traditional Zaps require users to manually configure triggers, actions, and data mappings, Copilot handles that configuration through conversation.

Under the hood, these agents still rely on Zapier's connections to over 9,000 apps, including Google Sheets, Airtable, Slack, and various AI models. The difference is speed: users can prototype and deploy agents in minutes rather than hours.

For researchers and content strategists, this means less time wrestling with API documentation and more time refining the questions they want answered. An agent might pull data from multiple sources (Reddit threads, Google Trends, LinkedIn engagement metrics, industry newsletters) and synthesize that information into a weekly report or content calendar.

The Copilot interface guides users through the setup process, suggesting connections and refinements as they describe their workflow. Once configured, agents run on schedules or triggers, feeding results back into the tools creators already use.

Trucks' post emphasizes relevance over volume. His argument: speakers who win today are not just skilled on stage but strategically visible off it. Attention creates opportunity, and relevance drives demand.

This reflects a broader shift in content marketing. Rather than publishing consistently on a fixed editorial calendar, creators are increasingly optimizing for real-time alignment with what their audience is actively searching for or discussing. AI research agents accelerate that feedback loop.

The agent Trucks built is publicly accessible, allowing other Zapier users to clone and modify it for their own industries. This shareability is a key feature of Copilot-built workflows, turning individual solutions into community resources.

Zapier continues to expand its AI capabilities. Earlier this year, the company launched an SDK for AI builders and extended its Model Context Protocol support to give AI assistants like Claude direct access to thousands of app actions. Copilot-built agents sit alongside these developer-focused tools, targeting users who prefer conversational interfaces over code.

For small business owners and solo creators, the value proposition is clear: automate the research grind, so you can focus on execution. Whether that means more stage time, better content, or faster go-to-market, the pattern is the same. Let the agent handle data collection and synthesis while you handle strategy and delivery.