Your next visitor may arrive through an AI assistant. Help them find a clear answer about your business, then take a useful next step on the website you already have.
See what is implemented on this website
An agent-ready approach begins with the organization's existing website. Its pages and actions need to remain understandable to the people who use them.
Decide which information and tasks an agent should be able to help with. That gives the work a concrete scope.
WebMCP tools represent actions a compatible agent can request from the page. Each action needs a clear purpose and the inputs required to perform it.
Choose the browser and assistant experience you intend to support, then test the task there. A connection that works in one experience may need a different approach in another.
A reading view presents the information an agent needs in a usable form. It complements the website's ordinary pages.
Keep both views aligned with the same maintained content. A change should reach every place a visitor or agent may read it.
Maintained organizational knowledge supports the information exposed through the site. Someone needs to own the facts and decisions behind that content.
Use the same review discipline when the website changes. An agent should receive current information with clear boundaries around what it can do.
Readable pages, useful actions and maintained knowledge support different parts of the visitor’s task. Keep them aligned so an answer can lead to the right next step.
Choose one visitor task and verify it end to end. That is the starting point for deciding which capabilities should follow.
An agent-ready approach begins with the organization's existing website. Its pages and actions need to remain understandable to the people who use them.
Decide which information and tasks an agent should be able to help with. That gives the work a concrete scope.
WebMCP tools represent actions a compatible agent can request from the page. Each action needs a clear purpose and the inputs required to perform it.
Choose the browser and assistant experience you intend to support, then test the task there. A connection that works in one experience may need a different approach in another.
A reading view presents the information an agent needs in a usable form. It complements the website's ordinary pages.
Keep both views aligned with the same maintained content. A change should reach every place a visitor or agent may read it.
Maintained organizational knowledge supports the information exposed through the site. Someone needs to own the facts and decisions behind that content.
Use the same review discipline when the website changes. An agent should receive current information with clear boundaries around what it can do.
Readable pages, useful actions and maintained knowledge support different parts of the visitor’s task. Keep them aligned so an answer can lead to the right next step.
Choose one visitor task and verify it end to end. That is the starting point for deciding which capabilities should follow.
A customer may ask an assistant about your business before opening your site, or bring an agent to help them use it. Either way, they need a clear, current answer. Search access, training permissions and browser actions are separate decisions; make each one deliberately.
An agent-ready approach begins with the organization's existing website. Its pages and actions need to remain understandable to the people who use them.
Decide which information and tasks an agent should be able to help with. That gives the work a concrete scope.
WebMCP tools represent actions a compatible agent can request from the page. Each action needs a clear purpose and the inputs required to perform it.
Choose the browser and assistant experience you intend to support, then test the task there. A connection that works in one experience may need a different approach in another.
A reading view presents the information an agent needs in a usable form. It complements the website's ordinary pages.
Keep both views aligned with the same maintained content. A change should reach every place a visitor or agent may read it.
Maintained organizational knowledge supports the information exposed through the site. Someone needs to own the facts and decisions behind that content.
Use the same review discipline when the website changes. An agent should receive current information with clear boundaries around what it can do.
Readable pages, useful actions and maintained knowledge support different parts of the visitor’s task. Keep them aligned so an answer can lead to the right next step.
Choose one visitor task and verify it end to end. That is the starting point for deciding which capabilities should follow.
An agent-ready approach begins with the organization's existing website. Its pages and actions need to remain understandable to the people who use them.
Decide which information and tasks an agent should be able to help with. That gives the work a concrete scope.
WebMCP tools represent actions a compatible agent can request from the page. Each action needs a clear purpose and the inputs required to perform it.
Choose the browser and assistant experience you intend to support, then test the task there. A connection that works in one experience may need a different approach in another.
A reading view presents the information an agent needs in a usable form. It complements the website's ordinary pages.
Keep both views aligned with the same maintained content. A change should reach every place a visitor or agent may read it.
Maintained organizational knowledge supports the information exposed through the site. Someone needs to own the facts and decisions behind that content.
Use the same review discipline when the website changes. An agent should receive current information with clear boundaries around what it can do.
Readable pages, useful actions and maintained knowledge support different parts of the visitor’s task. Keep them aligned so an answer can lead to the right next step.
Choose one visitor task and verify it end to end. That is the starting point for deciding which capabilities should follow.
Choose a task an agent could help a visitor complete, such as preparing an enquiry. WebMCP lets a page describe its tools and forms to compatible browser agents. Support varies by browser, so test the task where visitors are. On this site, Send stays with the person.
Readers such as Claude, ChatGPT and Microsoft 365 Copilot give people a place to ask questions and begin work. Connect them to the business knowledge needed for the task.
Current facts and recorded decisions give the next conversation a useful starting point. Your team spends less time explaining what the business already knows.
MCP gives a configured agent a way to request business knowledge. For Microsoft 365 Copilot, this requires an agent with a supported connection; connecting one reader does not connect them all.
Decide which knowledge each role can retrieve. Configure and test access for each connection, so people receive the context their work requires.
The wiki holds current facts, procedures, rules and workflow steps. Retrieval brings the relevant material into the task, keeping the context focused on the work at hand.
Keep the sources clear enough for an expert to inspect and correct. A useful answer should rest on knowledge your team can find, understand and maintain.
Operators using Claude Code and Codex maintain the wiki through read and write access. They review corrections, retire outdated rules and preserve useful lessons from completed work.
Updating the shared source makes the correction available to the next task. Give operators the time and AI allowance to do that work; their role differs from someone running a proven workflow.
Managed agents plan, work and review using the maintained business context. The review checks the result against what the task was meant to achieve.
Use that result to decide what happens next: continue, retry within an allowance, or ask a specialist or person. Useful failures become cases the next version must handle.
Readers use the knowledge, operators keep it current, and agents apply it to defined work. Each role has its own access, responsibility and AI quota.
That continuity lets useful work carry forward with less repeated input from you. Decisions and working methods remain available while your experts handle the judgement the task still needs.
Readers such as Claude, ChatGPT and Microsoft 365 Copilot give people a place to ask questions and begin work. Connect them to the business knowledge needed for the task.
Current facts and recorded decisions give the next conversation a useful starting point. Your team spends less time explaining what the business already knows.
MCP gives a configured agent a way to request business knowledge. For Microsoft 365 Copilot, this requires an agent with a supported connection; connecting one reader does not connect them all.
Decide which knowledge each role can retrieve. Configure and test access for each connection, so people receive the context their work requires.
The wiki holds current facts, procedures, rules and workflow steps. Retrieval brings the relevant material into the task, keeping the context focused on the work at hand.
Keep the sources clear enough for an expert to inspect and correct. A useful answer should rest on knowledge your team can find, understand and maintain.
Operators using Claude Code and Codex maintain the wiki through read and write access. They review corrections, retire outdated rules and preserve useful lessons from completed work.
Updating the shared source makes the correction available to the next task. Give operators the time and AI allowance to do that work; their role differs from someone running a proven workflow.
Managed agents plan, work and review using the maintained business context. The review checks the result against what the task was meant to achieve.
Use that result to decide what happens next: continue, retry within an allowance, or ask a specialist or person. Useful failures become cases the next version must handle.
Readers use the knowledge, operators keep it current, and agents apply it to defined work. Each role has its own access, responsibility and AI quota.
That continuity lets useful work carry forward with less repeated input from you. Decisions and working methods remain available while your experts handle the judgement the task still needs.
If customers or staff use ChatGPT or Claude, start with what they need to ask about your business and which knowledge may be shared. Decide whether the task needs an answer or an action, then test the connection in the intended account.
Good examples show what useful work looks like. Code, written work and images give an expert something concrete to explain and compare.
Choose examples that reflect the standard you want. Keep their context clear so an agent can use them for the right kind of task.
Existing systems hold the files, records and tables the business works with. Decide which sources a second brain needs for the first useful workflow.
Keep those sources recognizable to the people responsible for them. They need to be able to correct outdated information and explain what it means.
Expert operators contribute the judgement that examples and systems cannot explain by themselves. They identify the exceptions and decide whether a result is useful.
Give that expertise a maintained form in facts, procedures and rules. The next task can use what has already been learned while the expert handles what is new.
The agent harness supplies instructions and workflows for a defined task. It connects the business context to the actions and checks the work needs.
Revise those instructions when review exposes a weakness. A useful method needs an owner who keeps it aligned with the work.
The access model sets the scope for people and their work. Decide which knowledge each role needs and who can maintain the source.
Test those boundaries with the actual workflow. Access is part of building a useful second brain, not a decision to postpone until more people join.
Maintained outputs include checked documents and workflows. Keep the useful result available with the context needed to understand and reuse it.
Review changes as the business moves on. A result that was right for one task may need revision before someone relies on it again.
Examples, existing systems and expert judgement supply the context. Instructions, access and maintained outputs make that context usable in real work.
Start where an expert can judge the result and maintain the knowledge. What work would become easier if its context carried into the next task?
Good examples show what useful work looks like. Code, written work and images give an expert something concrete to explain and compare.
Choose examples that reflect the standard you want. Keep their context clear so an agent can use them for the right kind of task.
Existing systems hold the files, records and tables the business works with. Decide which sources a second brain needs for the first useful workflow.
Keep those sources recognizable to the people responsible for them. They need to be able to correct outdated information and explain what it means.
Expert operators contribute the judgement that examples and systems cannot explain by themselves. They identify the exceptions and decide whether a result is useful.
Give that expertise a maintained form in facts, procedures and rules. The next task can use what has already been learned while the expert handles what is new.
The agent harness supplies instructions and workflows for a defined task. It connects the business context to the actions and checks the work needs.
Revise those instructions when review exposes a weakness. A useful method needs an owner who keeps it aligned with the work.
The access model sets the scope for people and their work. Decide which knowledge each role needs and who can maintain the source.
Test those boundaries with the actual workflow. Access is part of building a useful second brain, not a decision to postpone until more people join.
Maintained outputs include checked documents and workflows. Keep the useful result available with the context needed to understand and reuse it.
Review changes as the business moves on. A result that was right for one task may need revision before someone relies on it again.
Examples, existing systems and expert judgement supply the context. Instructions, access and maintained outputs make that context usable in real work.
Start where an expert can judge the result and maintain the knowledge. What work would become easier if its context carried into the next task?
Keep one agreed source for your services, experience and decisions, maintain the site from it, and derive agent-readable information from the published pages. Claude and Codex use this website's maintained knowledge between sessions, and Matt reviews the result.
Start with useful content people can read on the page: clear service descriptions, links between services and examples, and structured descriptions that match what is visible, kept current and consistent. Google applies its established search guidance to its AI features; no special file guarantees inclusion, and citing you remains the assistant's decision.
This site builds its agent-readable information from eligible published pages, so it can be checked against what a visitor reads. This preview is excluded from search indexing, service pages under review are left out of agent content, and browser-tool compatibility is still to be checked.
Bring one visitor task and the website it needs to work on. The work builds on your existing site where the platform supports it.
Take one task a visitor needs to complete, assess the content and the obstacles an assistant meets, and scope the tools worth testing.
Set up an agreed source for your services and experience, maintain the site from it, and derive agent-readable information from published pages.
A website assistants can read, with people in control of what it does.
Matt can assess your content, identify obstacles to finding or using it, and scope the tools or connections worth testing.
Start with one task a visitor needs to complete.