Instead of complex prompts, interact with AI agents as you would a human employee. When the agent makes a mistake (like a broken link), provide simple, conversational feedback. The agent can then understand the error and self-correct its process for future tasks.
Configure an AI agent to scan job boards for roles that signal budget allocation (e.g., "Head of Growth"). The agent can then identify the decision-maker, enrich their contact info, and automatically draft a personalized outreach email that references the specific job posting.
Use an AI agent to monitor messy, local data sources like Craigslist and bankruptcy filings for restaurant closures. The agent can identify undervalued equipment, calculate the arbitrage spread against market comps, and surface deals with high profit potential and zero inventory risk.
Use an AI agent to scan platforms like Product Hunt for launches from 2-4 years ago. The agent identifies products where the site is dead but organic SEO traffic remains. This creates an opportunity to acquire the asset cheaply from founders eager to offload server costs.
An AI agent can monitor domain auction sites for expired domains and automatically filter them against a predefined criteria list (e.g., niche keywords, DR score, clean backlink profile). This delivers a daily ranked list of top domains worth bidding on, automating a time-intensive process.
A repeatable framework for creating AI-powered businesses: 1) Identify a messy public data feed (e.g., auctions). 2) Find a mispriced asset within it (e.g., domains). 3) Define a trigger event (e.g., drop, hiring). 4) Target an obvious buyer. 5) Determine the monetization model (e.g., flip, broker).