The Observatory

If you're using agents to run discovery conversations at scale, the failure mode isn't volume — it's baking your assumptions into every question your system asks. Fix the question design first.

If you're deploying agents to compete in a crowded category, you're spending compute to race to zero margin. The 0→1 logic cuts harder now because agents lower the cost of imitation almost to nothing.

If you are designing a system where agents handle execution, the drag you feel is almost never capability — it is the overhead of keeping everyone, human and silicon alike, aligned. Avichal Garg's thinking lands differently once you read it that way.

If your agents are handling the work, the humans you bring in are pure judgment — which means a bad hire is now catastrophically expensive, not just annoying.

If you're building an AI-native company right now, the hardest question isn't what your agents can do — it's what you're supposed to do while they're doing it. Greg Brockman worked that out the hard way at Stripe, and his thinking translates almost uncomfortably well.

If you're staffing your company with agents rather than headcount, you're not automating a business — you're probably building one that incumbents structurally cannot copy. That distinction is worth thinking through carefully before you price anything.

The hardest thing to delegate to an agent is legitimacy. Before you automate your community into a ghost town, understand what actually holds people together.

If you're the human holding judgment in an AI-native company, you've already switched roles — and your old scheduling habits will quietly wreck your throughput anyway.

Wasserman's data shows that most startups die from people problems baked in on day one — and agents don't fix that fragility, they amplify it fast.

If you're deploying agents to do work, you still have to get users in the door, and the founders who treat that as a system to instrument rather than a story to tell will win the channel before everyone else figures out it exists.

Founders drowning in async agent output often skip the operating layer entirely — and that's where everything quietly rots. The Mochary Method gives you the cadences and decision hygiene to stay coherent when execution is no longer human-paced.

The foundational pressure in Sam Altman's Startup Playbook — make something people want, then grow or die — doesn't soften just because your headcount is three humans and forty agents. If anything, it sharpens.