What is Agent Experience?
A practical definition of AX, where the term came from, the meanings it carries, and the questions it helps a team ask.
13 min read
Guides
A field guide to Agent Experience.
Learn the basics first, then find practical help for the part of your product you want to improve.
The reading order
Each guide builds on the one before, from what AX means to running a review of your own.
What is Agent Experience?
Say which AX you mean before you change anything.
13 min read
An Agent Experience (AX) framework
Place any problem on one path: orient, discover, act, collaborate, learn.
10 min read
Build websites agents can understand
Check how agents find and read your public pages.
11 min read
Write tool descriptions an agent can act on
Write tools an agent can choose correctly, and tell apart from their neighbours.
8 min read
Agent workflow design: scoping the first one
Scope one bounded job, so the later steps have a real workflow to work on.
7 min read
Human approval workflows for AI agents
Gate consequential actions, and make sure what a person approves is what runs.
24 min read
How do you measure agent experience?
Measure paths rather than scores, and know which claims a metric cannot support.
17 min read
Run an Agent Experience review
Put the earlier steps together in a review of one real workflow.
9 min read
Start here: what AX is
For anyone new to AX: what the term means, the framework this site uses, and what the people who do the work actually do.
An Agent Experience (AX) framework
A five-part map of where agent work breaks (orient, discover, act, collaborate, learn), a four-step method, and a rubric that gives one job a profile across six tracks, each rated at one of four levels.
10 min read
Five meanings of agent experience
Product AX, coding-agent AX, contact-centre AX, real-estate and insurance AX, and delegated-job AX: who uses each, and how to tell which one a page means.
12 min read
What does an AX engineer do?
The agent experience role as public job postings and team pages describe it: the work, the skills, and how it differs from DevRel and DX.
12 min read
Guides by topic
Not sure which one fits? The field map shows where each topic sits
Help agents find and understand your product
For teams whose website, docs or sign-up an AI agent has to find and read before it can help anyone.
Build websites agents can understand
Clear structure, stable interactions, and meaningful labels help both people and agents navigate a site.
11 min read
Write agent-readable documentation
What AI agents read, how to shape a page around a single decision, and how to keep the text true as the product moves.
8 min read
AX, UX, DX, and GEO: where each fits
How the related disciplines connect, and the different product problem each one describes.
14 min read
Does llms.txt actually work?
What adoption and server-log studies show, and where the evidence is limited.
11 min read
The state of agent-web standards
Compare agent-facing standards by who reads them and what they help an agent do.
15 min read
Agentic Resource Discovery, implemented
What ARD is, how ard.json relates to MCP's ai-catalog.json, and a copy-pasteable manifest for a content site.
19 min read
Let agents start before anyone signs up
Claim-later onboarding: the agent provisions a bounded resource now, and a person claims it later through a link.
17 min read
Make tools easier to choose and use
For teams that give agents tools, an API or written instructions, and want the agent to pick the right one and use it well.
Write tool descriptions an agent can act on
The text around a tool affects whether an agent can find it, choose it, and use it well.
8 min read
Agent tool catalogues need a pruning strategy
A small, clearly separated catalogue is usually easier to choose from than a long list of overlapping actions.
8 min read
An agent dashboard should show the next decision
A run view should tell an operator whether to approve, retry, stop or escalate, and why.
7 min read
How to expose a 3,000-operation API to agents
Seven patterns for large API surfaces: search first, schema on demand, rehearsal, truthful exits, an escape hatch, curated descriptions and a context budget.
14 min read
Keep agent instructions true
How to catch drift between what AGENTS.md, llms.txt, skills and MCP instructions say and what production does.
10 min read
Handle approvals, failures, and handoffs
For teams whose agents take real actions that a person has to approve, recover from, or pick up halfway.
Agent workflow design: scoping the first one
A bounded workflow with a real edge shows you where judgement, context and control matter.
7 min read
Agent context handoff: carry the reason for the work
Five things vanish at a handoff. A small structured record keeps intent, constraints, changed state, authority and evidence together.
8 min read
Human approval workflows for AI agents
Consequential actions need a clear pause, real choices, and a way back into the work.
24 min read
Agent error recovery: design the path back
Four fields turn an error into a decision: what failed, whether state changed, whether a retry is safe, and what input would fix it.
8 min read
Record retries as product history
Visible attempts show whether a system recovered cleanly or made people do more work.
8 min read
Approval, handoff and recovery patterns for AI agents
Seventeen named patterns for the human side of agent work, each with when to use it, how it fails and a live example.
21 min read
Find evidence for what to improve next
For teams that need to check how ready one job is, measure a change, and decide what to fix first.
The Open Agent-Readiness Rubric
Check one real job across six tracks, from finding the page to handing the result back, and get a profile instead of a score.
25 min read
Evaluate the decisions in an agent workflow
Evaluate tool choice, handoffs, and recovery alongside the final result.
8 min read
How do you measure agent experience?
The key agent experience metrics in four families, how to compare a change against a bare baseline, and the claims none of them can support.
17 min read
Run an Agent Experience review
A repeatable way to inspect one meaningful workflow and choose the next product improvement.
9 min read
Agent evaluation loop: run, judge, triage, fix, repeat
Six stages, a fixed task set, and a failure taxonomy that names the first decision that broke instead of the last error.
11 min read
Agent readiness scores compared
Cloudflare, Lighthouse, Is Agentic, AFDocs scores, AXIS and the 2027.dev tier list: what each one scores, how, and what it cannot tell you.
16 min read
Agent experience examples you can check
Seventeen annotated, public AX design decisions, mapped to the rubric, with a checklist and a template for recording your own.
16 min read