Concept of Operation<\/a>. It is being kept deliberately simple. Parents and carers will be able to learn about Levi Swim services via a WordPress.com website, request lessons through a booking form, and receive personal confirmation directly from Levi. Bookings will continue to be recorded in a shared bookings calendar, implemented, as now, in an Excel spreadsheet stored on Google Drive. Invoicing and payments will continue to be handled as a third-party service through Community Support Team (CST), using their own accounting tools.<\/p>\n\n\n\nPhase 1 does not<\/strong> include automated booking, live availability display, integrated payment processing, nor automated reminder functions. These capabilities are recognised as desirable but are planned for later phases.<\/p>\n\n\n\nPurpose of the Lab<\/h2>\n\n\n\n
To explore the potential usefulness of AI to the enterprise, judging this against what a micro-business can sustain without unreasonable risk.<\/p>\n\n\n\n
Opportunities for use of AI<\/h2>\n\n\n\n
Levi Swims is a classic micro-enterprise built around a single skilled practitioner. The work involves a few high-level operational processes: lesson delivery, booking and calendar management, parent communication, coordination with third-parties, and the handling of SEND\/safety information. Phase 1 will rely on manual routines and tools: a static website, standard email capabilities, and a spreadsheet-based bookings calendar.<\/p>\n\n\n\n
Strengths of AI in this context<\/h2>\n\n\n\n
Creating simple procedural workflows that reduce human load. <\/p>\n\n\n\n
Capturing structured information from unstructured messages.<\/p>\n\n\n\n
Drafting clear, consistent customer communications.<\/p>\n\n\n\n
Triage: spotting missing information, contradictions, or conflicts.<\/p>\n\n\n\n
Scheduling optimisation and constraint-checking (within limits).<\/p>\n\n\n\n
Automating recurring admin: reminders, confirmations, follow-ups.<\/p>\n\n\n\n
Summarising or condensing overlong information into actionable points.<\/p>\n\n\n\n
Template-driven document or message generation.<\/p>\n\n\n\n
Basic data hygiene (spotting duplicates, inconsistencies).<\/p>\n\n\n\n
Mapping of AI strengths across high-level processes<\/h2>\n\n\n\nA. Booking and Calendar Management<\/h3>\n\n\n\n
Tasks Levi performs:<\/p>\n\n\n\n
\n- Receiving booking requests.<\/li>\n\n\n\n
- Extracting key details.<\/li>\n\n\n\n
- Spotting missing information.<\/li>\n\n\n\n
- Checking availability in the spreadsheet.<\/li>\n\n\n\n
- Negotiating alternatives.<\/li>\n\n\n\n
- Confirming bookings.<\/li>\n\n\n\n
- Maintaining the calendar manually.<\/li>\n<\/ul>\n\n\n\n
AI match: very high. It can parse requests, extract details, flag missing fields, draft responses, and detect clashes. It cannot replace the spreadsheet calendar or make safety decisions.<\/p>\n\n\n\n
B. Parent Communication<\/h3>\n\n\n\n
Tasks Levi performs: initial responses and clarifications, explaining SEND considerations, confirmations, reminders, handling cancellations.<\/p>\n\n\n\n
AI match: high. It can draft replies, generate explanations, and maintain consistent tone. Levi must always send messages himself.<\/p>\n\n\n\n
C. Third-Party Coordination<\/h3>\n\n\n\n
Tasks Levi performs: communicating invoice details, responding to payment flags, ensuring calendar consistency.<\/p>\n\n\n\n
AI match: moderate. It can draft summaries for CST and detect mismatches. It cannot integrate with Xero or make credit decisions.<\/p>\n\n\n\n
D. Lesson Planning and Delivery<\/h3>\n\n\n\n
Tasks Levi performs: planning and delivering lessons, tailoring approach, ensuring safety.<\/p>\n\n\n\n
AI match: very low. AI can suggest ideas or summarise notes but cannot replace judgment.<\/p>\n\n\n\n
Tasks Levi performs: sifting information, extracting essentials, writing concise notes, deleting unnecessary material.<\/p>\n\n\n\n
AI match: high but delicate. AI can summarise long messages and highlight relevant points while Levi retains all safety decisions.<\/p>\n\n\n\n
Analysis:<\/h2>\n\n\n\n
Where could AI Provide Benefit?<\/p>\n\n\n\n
\n- The biggest operational pain point is booking administration. Many use cases and scenarios revolve around manual admin, potentially creating delays and errors. This problem is well suited to AI.<\/li>\n\n\n\n
- Parent communications are frequent, repetitive, and not safety-critical; AI could support drafting and clarification.<\/li>\n\n\n\n
- SEND\/safety note extraction could benefit from AI\u2019s ability to condense overshared information.<\/li>\n\n\n\n
- Third-party coordination could benefit to a small extent. <\/li>\n\n\n\n
- Lesson delivery gains nothing.<\/li>\n<\/ul>\n\n\n\n
AI could assist in booking admin, parent communication, and SEND\/safety information triage.<\/p>\n\n\n\n
Constrain the AI\u2019s role to that of administrative augmentation, not automation, the goal being a safe, valued, low-risk application.<\/p>\n\n\n\n
Approach to Lab Work<\/h2>\n\n\n\n
Model Levi Swim’s business operation, defining processes and creating a minimal synthetic data environment.<\/p>\n\n\n\n
Apply the principles of the three-layer context model to produce the context window components needed to configure a Booking Admin Copilot.<\/p>\n\n\n\n
Deploy the Copilot and then run a progression of experiments to:<\/p>\n\n\n\n
\n- extract structured data, <\/li>\n\n\n\n
- identify missing information, <\/li>\n\n\n\n
- draft clear responses, <\/li>\n\n\n\n
- summarise SEND notes, <\/li>\n\n\n\n
- flag potential scheduling conflicts, and <\/li>\n\n\n\n
- prepare invoice requirements.<\/li>\n<\/ul>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","protected":false},"excerpt":{"rendered":"
Levi Swims Lab Brief Transparency label: human-led (human-authored, with AI input limited to suggestions, edits, or fact-checking) The Scenario Levi Swims is a micro-enterprise; it provides swimming lessons to children and young people, with a particular emphasis on those who have special educational needs and disabilities (SEND). Lessons are delivered one-to-one or in small groups […]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-917","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/anapoly.co.uk\/labs\/wp-json\/wp\/v2\/pages\/917","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/anapoly.co.uk\/labs\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/anapoly.co.uk\/labs\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/anapoly.co.uk\/labs\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/anapoly.co.uk\/labs\/wp-json\/wp\/v2\/comments?post=917"}],"version-history":[{"count":10,"href":"https:\/\/anapoly.co.uk\/labs\/wp-json\/wp\/v2\/pages\/917\/revisions"}],"predecessor-version":[{"id":934,"href":"https:\/\/anapoly.co.uk\/labs\/wp-json\/wp\/v2\/pages\/917\/revisions\/934"}],"wp:attachment":[{"href":"https:\/\/anapoly.co.uk\/labs\/wp-json\/wp\/v2\/media?parent=917"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/anapoly.co.uk\/labs\/wp-json\/wp\/v2\/categories?post=917"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/anapoly.co.uk\/labs\/wp-json\/wp\/v2\/tags?post=917"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}