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.

Platforms like Nebula allow founders to move beyond simple automation. By providing a high-level directive and connecting services, AI agents can run entire business functions, like a content blog that researches, writes, and publishes daily with minimal human intervention.

Instead of manually researching venture capital firms for fundraising, an AI agent can investigate dozens of targets simultaneously. It pulls data on fund size, relevant partners, investment theses, and recent social media activity, then organizes everything into a ready-to-use spreadsheet, saving weeks of analyst work.

To manage the overwhelming pace of AI advancements, the Minimax team built an internal AI agent. This tool automatically tracks new articles, papers, and blogs, then dispatches, summarizes, and analyzes them. This "internal researcher" filters the information firehose for the human team.

Instead of static documents, companies can embed their strategy into an AI agent. This agent assists in planning, identifies cross-departmental conflicts, and can be queried in real-time during decision-making to ensure constant alignment, making strategy a dynamic part of daily operations.

Venture capital firms are leveraging AI tools like Google's NotebookLM to process deal flow. They ingest investment memos and legal documents to analyze them against their investment thesis and even simulate a preliminary legal review.

The business model is shifting from selling software to selling outcomes. Instead of creating a tool and inviting users, create pre-trained agents that perform valuable work. Then, invite companies to a workspace where this 'team' of AI employees is ready to start delivering value immediately.

Package pre-configured Autoresearch loops to solve a single, painful problem for a specific niche, like an Amazon listing optimizer or an email tuner for realtors. Sell it as a simple, automated monthly subscription service.

The era of prompt engineering is ending. The future is proactive AI agents working in the background to surface critical information. These agents will automatically monitor for and alert teams to competitor launches, new patent filings, and regulatory changes, shifting from a manual 'pull' to an automated 'push' model of intelligence.