Built around the work

A starting point. Then a path that adapts.

Adaptive AI training changes what each person practises next based on how they actually perform. Tosheo.ai is being built to do that with a short diagnostic, 10 to 15 minute role lessons and rubric-scored tasks that decide the next step.

tosheo.ai / Your workspaceIllustrative preview

A path for your work.

Marketing

01 / Give AI the right contextCompleted in this example
02 / Write a useful first draftCompleted in this example
03 / Make it sound like your brandPractice task / in progress
Your next move
Rewrite a launch email. Keep the promise specific. Remove the claim you cannot prove.
04 / Check before you shareUp next / evidence and judgement

Illustrative product preview

Context

Use a fictional brief, name the audience and set the constraints.

Practice

Make a draft, inspect what changed and try again with clearer instructions.

Judgement

Check evidence, protect information and explain your final decisions.

01 / Built around the work

What is adaptive AI training?

Adaptive AI training is a programme where the order, difficulty and examples of each lesson change with the learner's results, instead of everyone working through the same fixed catalogue. Two people in the same team can start in different places and move at different speeds.

In Tosheo.ai the adaptation is planned to rest on evidence of work, not on clicks or time spent. A learner submits a piece of output, the output is scored against a rubric, and that score shapes what comes next. A confident first-timer and a cautious daily user should end up with different paths, because their submitted work will be different.

02 / Built around the work

What does a manager do before the first lesson?

The manager completes a short setup and sends invites. The onboarding is being designed with a target of under ten minutes from signup to the first invite, which is a design goal we will test rather than a measured result.

Sign up

Create an account with Google or email.

Describe the company

Enter the company name, size and industry, so examples sound like your kind of work.

Choose roles

Pick from Marketing, Sales, Ops, Support, HR/Recruiting, Finance, Product and General, or add a custom role.

Choose tools

Select the AI tools the team uses: ChatGPT, Claude, Gemini, Copilot, Notion AI, Canva AI or other.

Add context, optionally

Upload 1 to 5 company documents, such as an SOP, a brand guide or a sales playbook, so exercises use your context.

Invite the team

Invite people by email or a shareable link and assign each person a role.

Start the trial

Begin the planned seven-day trial, with a card required and up to five seats.

03 / Built around the work

What does a learner see in the diagnostic?

The diagnostic is a planned 5-minute check that combines a self-rating with 4 to 6 short practical tasks. The self-rating records how confident someone feels; the tasks show what they actually do. Both are used to place the learner on a starting level for their role.

For example, a fictional account manager at Northfield Software might be asked to turn three supplied meeting notes into a follow-up email, then say which detail they would check before sending. Someone who adds an invented discount has shown a different starting point from someone who flags the missing renewal date, even if both rated themselves highly. When the diagnostic ends, the learner sees their personalised path with the first lesson ready.

04 / Built around the work

What is inside a single lesson?

Every planned lesson has three parts: a short explanation, a worked example from the learner's role and a hands-on task done in a real AI tool. The learner copies their final output and a short note on what they changed back into Tosheo.ai, where it is scored against the rubric shown on the task.

Take a fictional operations coordinator at Harbour Lane Logistics. The explanation covers why a summary needs a named reader. The worked example shows a supplier returns SOP condensed for warehouse staff. The task asks the learner to use their team's AI tool to summarise a different supplied SOP for new starters, keeping every step that has a safety check.

Feedback is meant to point at the work. A useful comment reads like this: "Your summary is clear and the right length for a new starter, but step 4 now says 'check the pallet' and the source says 'check the pallet seal and log the number'. Restore the logging step, then resubmit." A score without a reason like that is not the intended experience.

05 / Built around the work

How does the path change as a learner progresses?

The planned rules are simple. Strong performance skips ahead or raises the difficulty. Weak performance triggers a simpler re-explanation and a second attempt at a similar task. The engine selects and orders skills using the role, the diagnostic result, the tools in use and, where provided, company context.

In practice, a learner who keeps unsupported claims out of three drafts in a row might move on from output checking to a harder task with conflicting sources. A learner who repeatedly misses the reader might get a shorter lesson on setting context before trying again. This is intended behaviour. We have not measured its learning effect, and we will not claim one until we have.

06 / Built around the work

Where does the lesson content come from?

Lessons are planned to be generated at runtime, grounded in an established library of AI courses and articles to keep quality consistent and to reduce invented content. Rubrics are stored per task, and every evaluation is logged so a disputed score can be reviewed.

If a team uploads company documents, examples and exercises can use that context. Company document grounding is planned for the Growth plan. Uploaded documents are planned to stay isolated per company, to be deleted on account closure and never to be used to train models. Learners practise in the AI tools your company already pays for; those subscriptions are not included.

07 / Built around the work

When is Tosheo.ai not the right fit?

It is not the right choice if you need SSO, SCIM or LMS integration before purchase, because none of those is included at launch. It is also not hands-on engineering or coding training: data science, machine learning, AI and blockchain are planned as professional foundations, not bootcamps. It is not built for individual consumers learning on their own, or for teams that need lessons in languages other than English.

If your organisation wants to author its own courses or sign an enterprise contract with invoicing, Tosheo.ai does not offer either at launch. A larger provider with a sales-led programme is likely to suit you better.

Before you decide

A few good questions.

How long does each lesson take?

Lessons are planned to take 10 to 15 minutes, so they fit between meetings rather than replacing a working day. The diagnostic at the start is planned to take about five minutes.

Do learners need their own AI tool account?

Yes. Learners do the hands-on task in a real AI tool, such as ChatGPT, Claude, Gemini or Copilot. Subscriptions to those tools are not included in Tosheo.ai plans.

What happens if a learner fails a task?

The planned behaviour is a simpler re-explanation followed by a second attempt at a similar task. A learner can also flag a score they disagree with so it goes to a review queue.

Do we have to upload company documents?

No. Uploading 1 to 5 documents is optional and is planned for the Growth plan. Paths still use role-specific examples without them.

Is the adaptive engine proven to work?

No claim of that kind is made. Tosheo.ai is pre-build, and the adaptation rules describe intended behaviour that has not yet been tested with customers.

Give your team a path, not another playlist.

Explore the planned role-specific lessons, practical tasks and manager view.

Start free trial7 days free · Card required · Up to 5 seats