AI assisted employment and training

Put Luke out of one job, then turn the pattern into many jobs.

The 300+ jobs aim is not paced by old workforce assumptions. Every role is AI assisted by default, so useful work can become teachable, repeatable and locally owned much faster.

Concept art of a coastal training room where local workstations are connected by quiet AI-assisted pathways.
Useful work becomes local capability when the pattern can be taught, checked, handed over and improved.

Rapid scale target

300+ people through AI assisted useful work.

The target can move fast because the work is built from builders, templates, checklists, prompts, training clips, shared evidence and human review.

30rapid starters

People using AI assisted forms, devices, media, admin, grant evidence and small business support from the first useful sessions.

100task owners

People holding repeatable tasks that can be prompted, checked, taught, handed over and improved.

300+AI assisted roles

Local work across co-op services, hyperlocal media, events, training, sport, assets, resilience and partner projects.

Fast lanes

Useful work can start wherever the task is clear.

AI changes the speed of the work. A form can become a builder, a conversation can become a checklist, a video can become a lesson, and a lesson can become a paid handoff. Lanes can overlap, accelerate, pause, split or recombine after first contact with residents and businesses.

Sole-trader proof

Strange but True delivers immediate AI assisted services and turns repeating tasks into usable prompts, files and builders.

Local helper bench

People learn small pieces of the work with AI beside them: forms, devices, captions, event setup, content checks, grant notes and asset registers.

Crew roles

Repeatable tasks group into crews with a human lead, AI-supported preparation, quality checks and public evidence.

Co-op services

Services emerge for businesses and clubs: admin support, training coordination, media packages, compliance notes and asset systems.

Formal engine

Distributing co-operative membership, labour hire licensing, RTO partnerships and service agreements come into focus when readiness is real.

AI assisted role families

The first job families are practical, visible and trainable.

Each role uses AI for drafting, sorting, checking, adapting or teaching, with people still holding trust, consent, judgement and local context.

Digital confidenceDevice and AI helpers

Phone setup, account recovery, scam awareness, AI basics, forms, browser use and patient one-on-one support.

Business supportProfile and admin crew

AI assisted business profiles, service listings, social posts, basic websites, booking pages, quote folders and plain-English SOPs.

MediaHyperlocal media team

AI assisted interview prep, captions, edit notes, ferry-screen packaging, event recaps and local story stewardship.

EventsSet-up and production crew

AI assisted run sheets, signage, weather checks, bump-in notes, public notices and post-event evidence packs.

Asset sharingGear and space caretakers

AI assisted check-out records, maintenance notes, charging lists, storage maps, training notes and repair follow-up.

GrantsEvidence and proposal assistants

AI assisted evidence packs from photos, attendance logs, outcomes, partner lists, quotes, budget notes and source links.

TrustCommunity hosts

AI-supported intake notes, role matching and warm handovers, with humans holding welcome, care and judgement.

Legal infoSource trail assistants

AI assisted collection of official links, dates, forms and document names for later qualified review. No legal advice.

Deep skillsDigital custodians and builders

Local AI, Markdown builders, credential systems, data stewardship, digital twins and simulation skills as practical work opens up.

Try Everything Once workforce

People stay sharper when work keeps opening new doors.

The work model is not one person locked into one narrow task forever. Residents, young people, older learners and returning workers can rotate through safe, useful AI assisted roles so they keep building confidence, relationships and practical skills.

A helper might start with phone setup, then use AI to draft captions, then help build a grant evidence pack, then learn the gear-care register. The island gains generally capable people who understand how the pieces fit together.

Why it matters

Less boredom, more capability.

Rotating through real tasks helps people avoid getting stuck, bored or written off. AI support gives the co-op a deeper bench of people who can step across media, admin, events, tech, assets, grants and care work.

Rotation paths

Learning loops, not dead-end jobs.

Each path can start simple, combine with another loop, or move quickly when a person finds the work that lights them up.

Loop 1Digital helper to media assistant

Device help, QR codes, screen-safe screenshots, AI captions, short posts and interview setup.

Loop 2Event hand to asset caretaker

Chairs, signage, projector setup, AI-supported checklists, gear check-out, charging, returns and basic repairs.

Loop 3Community host to trust mapper

Welcoming, listening, public/private sorting, AI assisted role matching and warm handovers.

Loop 4Grant helper to evidence steward

Dates, photos, attendance, outcomes, quotes, budget notes and AI-sorted source links.

Loop 5Food table to resilience helper

Shared meals, pantry notes, waste reduction, AI assisted supplier stories and emergency-ready community habits.

Loop 6Beginner coder to digital custodian

Website edits, Markdown builders, data hygiene, local AI tools and digital twin support.

Putting Luke out of work

A handoff is a success, not a loss.

Every time Luke changes projects, the goal is to leave behind a working pattern that no longer depends on him personally. AI assisted builders, checklists, prompts, public links and training clips make the handoff faster.

One useful pattern is simple: do the task, name the pattern, turn it into a builder or prompt, train someone, document the boundary, publish the public-safe version, then move the bottleneck to the next unsolved layer. Other patterns may emerge faster once residents and businesses start shaping the work themselves.

From task to role

Teachable work becomes local work.

A role becomes real when the task can be prompted, taught, checked, paid for, handed over and improved by someone other than Luke.