★7 min read
How to Make Your Online Store Agent-Accessible
A practical guide for developers on making an online store usable by AI agents: discovery endpoints, machine-readable product data, agent authentication, and x402 payments.
Windrose AI is about how the agentic web actually works.
Not the demos. Not the buzzwords.
The real systems - protocols, APIs, trust layers, and the messy constraints that show up in production when software is used by agents instead of humans.
If you're building or reasoning about these systems, this is where the details matter.
★8 min read
Human-in-the-Loop: When to Pause Autonomous Agents
A practical framework for deciding when an autonomous agent should stop and ask for confirmation, based on reversibility, spend, ambiguity, and novelty.
★7 min read
llms.txt: How to Make Your Website Readable by AI Agents
What llms.txt is, why it matters for agent-native websites, and how to write one that helps AI systems find the right content without guessing.
★7 min read
MCP Explained: The Protocol That Gives AI Agents Hands
A first-principles explanation of Anthropic’s Model Context Protocol: what MCP is, how clients and servers work, and what agents can actually do with real tool calls.
★8 min read
How to Monetize an Agent-Accessible API
When agents become your API customers, pricing models behave differently. This post compares per-call pricing, subscriptions, usage-based billing, and payment-at-request, with a focus on what actually works at agent scale.
★7 min read
Rate Limiting and Abuse Prevention for Agent APIs
Practical ways to protect agent-accessible APIs from abuse using token-bound identity, payment as proof of intent, and tiered rate limits.
★7 min read
Streaming Responses and Real-Time Tool Calls in LLM APIs
How streaming LLM responses work when models emit tool calls mid-generation, including SSE framing, partial argument assembly, and UI patterns for rendering responsive agent interfaces.
★8 min read
How to Test Autonomous Agent Workflows
A practical guide to testing autonomous agent workflows with scenario-based tests, mock tool environments, canary runs against real APIs, and safeguards for catching hallucinations before production.
★7 min read
Building Trust in AI Agent Transactions
For people to trust an AI agent to buy on their behalf, the transaction has to be legible: who acted, what was approved, what was purchased, and how to dispute mistakes. That requires identity verification, receipt standards, audit trails, and clear recourse.
★9 min read
USDC and Agent Wallets: A Practical Guide
A practical guide to how AI agents can hold and spend USDC on Base, with a look at Coinbase AgentKit, Crossmint, and Circle developer wallets—and what is actually production-ready today.