Agentic Empathy
Agentic Empathy
Section titled “Agentic Empathy”Agentic empathy means reducing uncertainty for constrained, tool-using agents that fetch, parse, compare, cite, and sometimes act on behalf of a human.
Use this page when you need the source-backed expansion behind the Agentic Empathy slide in the Codeable Skill Chat deck.
This is not anthropomorphism. The useful move is to respect agent constraints: entry path, context budget, fetch loss, provenance, and action boundaries.
Agentic empathy is the habit of asking:
If an agent lands here with a task, a tool budget, and an imperfect fetch pipeline, what can it find, understand, trust, cite, and safely do?
The Codeable deck now treats this as a two-step explanation:
- What it is and why it matters: design for what an agent can actually perceive, preserve, verify, and safely do on a human’s behalf.
- What it looks like: source-backed examples of structure, fetch quality, crawler lanes, and bounded actions.
What it is
Section titled “What it is”Agentic empathy is not anthropomorphism. It is a practical design habit: respect the agent’s entry path, context budget, fetch loss, source uncertainty, and action risk.
That makes it close to familiar UX empathy, but aimed at a different immediate reader. Human UX empathy asks what the visitor is trying to do and where the experience creates friction. Agentic empathy asks what a constrained, tool-using agent can perceive and carry forward while acting for a human.
Why it matters
Section titled “Why it matters”Agents increasingly mediate discovery, citation, comparison, and actions. If a site’s truth does not survive fetch, parsing, citation, and action boundaries, the agent may guess, skip the site, cite a competitor, or follow an unsafe affordance.
Microsoft’s Design Foundations for Agents is useful general support for this framing: trusted agent experiences require more than visual polish, including reliability, safety, privacy, transparency, accountability, human-centered scope, and error recovery.
This page expands the source-linked examples from the slide deck.
Source examples
Section titled “Source examples”| Example | What it teaches | Why it matters |
|---|---|---|
| Vercel Agent Readability | Agent-readable pages need discoverable structure, metadata, context, Markdown-friendly content, and validation. | Structure is empathy: it gives agents a predictable path through the page. |
| Cloudflare AI consumability and Markdown for Agents | A large docs site can expose index.md, llms.txt, llms-full.txt, page-level Markdown, and content negotiation. | Markdown and source maps are useful affordances, but they should point back to maintained source content. |
| Agent-Friendly Documentation Spec | Coding agents can lose content through truncation, tabbed docs, redirects, soft 404s, auth gates, broken Markdown, and oversized pages. | Fetch loss is real. If the important answer disappears in serialization, the agent may never see it. |
| OpenAI crawlers, Anthropic crawler controls, and Perplexity crawlers | Search/index crawlers, user-directed fetchers, and training/model-development crawlers are separate policy lanes. | Entry path matters. “Block AI bots” is too blunt when the site still wants AI-search or user-fetch visibility. |
| Microsoft agentic risk guidance and Simon Willison on the lethal trifecta | Tool-using agents need boundaries around permissions, approvals, logs, private data, untrusted content, and external communication. | Actions need boundaries. A capability signal should describe something real, scoped, and monitored. |
Empathy map
Section titled “Empathy map”| Agent question | Website signal |
|---|---|
| Can I find it? | Sitemap, internal links, llms.txt, and search crawler access. |
| Can I fetch it? | Clean 200 responses, low redirects, WAF allowlists, and user-fetch bot access. |
| Can I parse it? | Semantic HTML, clear headings, low boilerplate, and Markdown alternatives. |
| Can I trust it? | Dates, authorship, visible sources, methodology, and schema parity. |
| Can I cite it? | Short answer passages, named entities, stable URLs, and visible facts. |
| Can I act safely? | Real APIs or tools, explicit auth, scoped permissions, approvals, and logs. |
Talk wording
Section titled “Talk wording”- “Empathy here does not mean the agent has emotions. It means we respect its constraints.”
- “The agent may be reading a compressed, converted, truncated version of the page.”
- “A pretty accordion can be a hostile document if the answer disappears in serialization.”
- “Dates, sources, and direct answer passages are not SEO tricks. They are how an agent knows what it can responsibly quote.”
- “Do not make fake doors for agents. If a manifest says there is a tool, auth flow, or API, it needs to be real.”