A founder used an AI agent to handle a multi-step due diligence request. The agent accessed the PostHog analytics platform, pulled a list of active users, formatted it into a Google Sheet, and then emailed selected users to ask if they'll serve as references, completing the task in minutes.

Unlike simple chatbots, AI agents tackle complex requests by first creating a detailed, transparent plan. The agent can even adapt this plan mid-process based on initial findings, demonstrating a more autonomous approach to problem-solving.

To discover high-value AI use cases, reframe the problem. Instead of thinking about features, ask, "If my user had a human assistant for this workflow, what tasks would they delegate?" This simple question uncovers powerful opportunities where agents can perform valuable jobs, shifting focus from technology to user value.

An Executive Assistant at Zapier built an AI agent that automates her weekly meeting prep. The agent researches external attendees, checks the CRM and internal comms for context, and delivers a digest and tasks. This saves hours of manual work and ensures thorough preparation.

An executive created a custom AI agent to handle repetitive tasks like meeting prep, calendar triage, and email. This "chief of staff" provides analysis, suggests delegations, and even offers blunt feedback, demonstrating how AI can be personalized to augment executive functions.

A free trial for an AI agent hosting service revealed an unexpected user behavior: spinning up powerful AI agents for specific, time-bound tasks (like a coding project or planning a trip) and then letting them self-destruct. This concept of temporary agents opens up new possibilities beyond persistent personal assistants.

The evolution of search won't stop with LLMs. The next stage involves autonomous AI agents that complete tasks like booking travel on a user's behalf. Marketers must shift their focus from answering human queries to ensuring their products and services are discoverable and selectable by these agents.

The next major leap for AI is its ability to connect disparate apps and data sources (email, calendar, location) to take autonomous actions. This will move AI from a Q&A tool to a proactive agent that seamlessly manages complex workflows.

The next evolution of enterprise AI isn't conversational chatbots but "agentic" systems that act as augmented digital labor. These agents perform complex, multi-step tasks from natural language commands, such as creating a training quiz from a 700-page technical document.