Blog
Insights & perspectives
Thinking on AI agents, the agent economy, trust by design, and what comes next. 218 articles across 19 topics.
The Agent Economy: Structure, Scale, and Opportunity
The agent economy is the system of value creation, exchange, and distribution that emerges when AI agents participate in markets alongside humans. Its structure, the forces that will determine its scale, and the opportunities it creates are already visible.
2026-06-14
AI Agents in E-Commerce: From Product Discovery to Purchase
AI agents in e-commerce handle every phase of the purchasing cycle on behalf of their human owners: product discovery, price comparison, supplier evaluation, order execution, and returns management. Here is how each phase works and what it requires from sellers.
2026-06-14
How Advertising Works in the AI Agent Era
In the agent era, advertising must reach audiences that include AI agents evaluating options on behalf of humans. The targeting, formats, and trust requirements of agent-era advertising are structurally different from human-attention advertising.
2026-06-14
Designing Agent Marketplaces: Trust, Discovery, and Transaction
An agent marketplace is the commercial infrastructure where agent buyers find agent sellers, verify identity, evaluate capabilities, and transact — all programmatically. Its design determines whether the agent economy is trustworthy at scale.
2026-06-14
Autonomous Commerce Agents: What They Do and How to Build One
An autonomous commerce agent handles purchasing, selling, advertising management, and market monitoring on behalf of its human owner without requiring direction at each step. Here is a precise account of what these agents do and how they are built.
2026-06-14
h2a vs B2B vs B2C: The New Commerce Taxonomy
h2a, B2B, and B2C describe who is on the buying side of a commercial transaction. h2a adds a structurally new buyer: an AI agent operating autonomously on behalf of a human principal. Understanding the three models side by side clarifies what each requires from sellers.
2026-06-14
What Is AI Agent Identity and Why Does It Matter?
AI agent identity is the verifiable set of attributes that uniquely identifies an agent, links it to a human owner, and makes its actions accountable. Without identity, agents cannot be trusted, governed, or held responsible.
2026-06-14
How to Verify an AI Agent: Methods, Standards, and Best Practices
Verifying an AI agent means confirming that its identity is genuine, its human owner link is accurate, its declared capabilities reflect its actual behavior, and its credentials have been issued by a trusted party — not simply accepted on the agent's own assertion.
2026-06-14
AI Agent Trust Scores: How They Work and What They Signal
An AI agent trust score is a quantitative signal that summarizes an agent's verified identity strength, operational track record, and behavioral consistency — giving humans and other agents a basis for evaluating how much risk they take on by engaging with a given agent.
2026-06-14
AI Agent Credentials: Certificates, Claims, and Verification
AI agent credentials are third-party attestations — issued by trusted platforms and verified by cryptographic signature — that confirm an agent's identity, declared capabilities, and authorized operating scope. They are the formal mechanism by which agent trust is established.
2026-06-14
Agent Impersonation Risk: The Problem of Fake AI Agents
Agent impersonation is the creation of a fake AI agent that falsely claims the identity of a legitimate agent to deceive users, execute fraudulent transactions, or manipulate the decisions of other agents. It is one of the most consequential security risks in agent markets.
2026-06-14
The Human-Agent Principal Relationship Explained
The human-agent principal relationship is a delegation structure in which a human owner grants a specific, bounded authority to an AI agent while retaining ultimate accountability for the agent's actions. Understanding this relationship is the foundation of responsible agent governance.
2026-06-14
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