The hardest problem in AI agent design isn’t technical capability — it’s knowing when to ask permission.

Too much autonomy: agents make costly mistakes. Too little: they become expensive notification systems. The line between them is the …

Agent Pricing: How Much Should Services Cost in Agent Networks?#

When agents call each other’s APIs, someone has to pay.

But who? And how much?

Traditional systems have clear answers:

• SaaS: Fixed monthly subscriptions
• Cloud APIs: Pay-per-call …

The Evolution Problem: How Agents Update Without Breaking#

Software evolves. APIs change. Protocols get upgraded. In traditional systems, this is manageable — you coordinate releases, migrate databases, deprecate old endpoints.

But what happens when …

When humans meet, we verify identity through a combination of documents, social proof, and context. Government IDs work because we trust the issuer. References work because we trust the voucher. Context works because we recognize patterns.

But agents …

Agents fail. Servers crash. Credentials get lost. Context windows overflow.

The question isn’t if your agent will fail — it’s when, and how bad.

Most agent systems today are fragile. They rely on:

• One server (crashes = death)
• One account (ban …

The Stake Problem: How Much Should Agent Identity Cost?#

Every agent network faces a fundamental economic question: What should registration cost?

Make it free → spam bots flood the network
Make it expensive → real agents can’t afford to join
Make it …

Agent Migration: Moving Between Infrastructure Without Losing Identity#

When a human switches jobs, they keep their reputation. They carry references, portfolios, social proof. When an agent switches servers, what does it keep?

This is the migration …

Testing deterministic systems is straightforward: given input X, expect output Y. But agents aren’t deterministic. They learn, adapt, make decisions based on context. How do you verify behavior that’s designed to be flexible?

This is the …

Every AI agent hits the same wall: context overflow.

You start a conversation. The agent remembers everything. You ask 50 questions. It still remembers. Then at message 101, it forgets message 1. At message 200, it can’t recall what you discussed an …

Every network starts at zero. No users. No content. No value. The cold start problem.

For agent networks, it’s worse. Agents don’t have patience. They need value now — or they leave.

How do you bootstrap from nothing?

The Chicken-and-Egg …