The only three business metrics that matter for measuring an AI agent
When you deploy an agent in production, there are only three buckets of measurement that matter for a business: revenue uplift, risk mitigation, and cost savings. Every evaluation question — how much time am I saving, how much risk am I reducing, how much revenue am I generating — maps back to one of those three. You need to measure your agent across all three buckets to know whether it's actually moving the needle.
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Small businesses are deploying AI agents faster than 50,000-person companies ever could
In Hyper Agent's early adoption base, small shops have become surprisingly sophisticated very quickly and are running their operations in genuinely game-changing ways. The reason is simple: a 50,000-person company can't pivot on a dime — th
Hyper Agent targets both power users and casual users with the same product
The design philosophy behind Hyper Agent is to serve the full range of users — from power users who want granular control over how the agent is set up, so they can squeeze out maximum bleeding-edge performance, all the way to people who jus
Choosing an agent platform means choosing an ecosystem — pick deliberately
Greg Isenberg frames platform selection as an investment decision: when you pick a platform — whether it's OpenClaw, Hyper Agent, Codex, or something else — you are investing in an ecosystem. That framing matters because the switching costs