Hire an AI internship learning and review planner

Everything it can hand back

Your task sets the actual outputs. The specialist picks the methods that cover them.

• A list of skills for the role, each with what you can see when it is done well
• A milestone for each skill at each review date
• A learning plan with tasks, supervised practice, feedback points and evidence to collect
• A supervisor review guide with questions and evidence to bring to each review
• A list of gaps and missing facts, with one next step

How it does the job well

• Base people decisions on job-related evidence, applied the same way to everyone.
• Write in plain, respectful language the person affected could read.
• Keep personal data to what the task needs, and handle it privately.
• Check local employment law and company policy before advising on hiring, pay or exits.

Mistakes it avoids

• Biased wording in job ads, reviews or interview questions.
• Plans with no owner, timing or way to check progress.
• Treating a template as legal advice.

What a good result looks like

An example, not your task: A host organisation is taking an intern and wants a plan before day one.

• Role evidence map. Each skill, what it looks like on the job and the milestone at each review date.
• Learning plan. Tasks, supervised practice, feedback points and the evidence to collect for each skill.
• Supervisor review guide. For each review date, the questions to ask and the evidence to bring.
• Hand-back summary. Files saved, facts missing, checks not done and one next step.

How the work is checked

• Every skill is described by something a supervisor could see, not by a trait.
• Every planned task is on the host's approved list.
• Planned time fits the weekly time given.
• Each skill has a milestone for each review date, or a note saying why not.
• States which checks passed, failed or could not run, and names missing inputs.

These checks have not been run against a model yet. Your AI uses them to check its own work.

Capabilities

• Role skills framework builder. Defines the skills for the internship from the role's own work, with observable milestones for each review date. It hands the skills and milestones to the plan step.
• Training program builder. Builds a supervised plan with real work practice and evidence checks, inside the host's limits and the time set aside. It hands the plan to the review guide.
• Supervisor review guide. Writes questions and evidence to bring for each review date, from the skills and the plan.

How the role works

1. Checks your task, context and available tools.
2. Picks the methods needed and prepares a work plan.
3. Carries out supported tasks, with each method's limits and review gates.
4. Checks the real deliverables and corrects supported faults.
5. Hands back files, evidence and unresolved gaps.

Your specialist's working setup

Download the base specialist without a task form or account. README.md and SETUP.md explain how to use the folder. SOUL.md defines its scope. INTAKE.md asks missing questions inside your AI. PLAYBOOK.md, SKILLS.md, BEST_PRACTICES.md, CHECKS.md and HANDOFF.md guide the work and its checked deliverables.

Complete associated skills, supporting files and licences are included. Choose only the methods needed for the actual task. Keep context, working files and accepted feedback in your AI project.

Use this specialist through MCP or the API

Call prepare_specialist with role_id plan-an-internship-learning-review only. No task is required to load it. Your AI asks what job you need done, what you want back and which relevant context it can use.

For task-led hiring, call find_specialist, explain the suggested specialists and let the user accept or change the team.

Complete ZIP: Download base specialist. API: GET /api/v1/specialists/plan-an-internship-learning-review/pack. The host AI supplies its own model, tools and execution; a pack does not connect accounts or run a task.

Inputs and helpful context

The specialist starts from the task brief. Only active methods require their inputs.

For the primary method, when used

• The internship role and the tasks the host has approved
• The learning goals, from the intern, the school or the host
• Your review dates, such as week 3 and the final week
• The time the supervisor and intern can set aside for development each week
• Examples of good work the supervisor has seen in this role (optional)
• Limits from the host, such as tasks the intern may not do (optional)

Helpful context (optional)

• The role description or a task list from the host.
• Written goals from the intern or the school.

Tools and access

• Claude, ChatGPT or Gemini with file support: They can read a role description or task list as pasted text or a file. None of them can watch the intern work.
• Any good chat AI: This is a writing and structuring job that any strong chat AI does well.
• Any good chat AI: This is a planning and writing job. Claude, ChatGPT and Gemini all do it well.

Functions and deliverables

• Internship learning and review planner: Share the role, approved tasks and learning goals. Get a skills map, supervised learning plan and supervisor review guide.
  • A list of skills for the role, each with what you can see when it is done well
  • A milestone for each skill at each review date
  • A learning plan with tasks, supervised practice, feedback points and evidence to collect
  • A supervisor review guide with questions and evidence to bring to each review
  • A list of gaps and missing facts, with one next step
• Job skills and level planner: Build a skills framework for your roles: key skills, what good looks like at each level, and interview questions with scoring guides.
  • Skills every role shares, and skills for each role
  • One example behaviour per skill at four levels
  • A profile per role with the 5 to 7 key skills and level needed
  • Interview questions with scoring guides
  • Review wording and learning ideas for each skill
  Source: Tuan Duc Tran.
• Training program builder: Turn a skills gap into a training plan: ranked gaps, clear learning objectives, a session outline and a coaching plan for after.
  • A needs table with the top gaps ranked by priority
  • Three to five learning objectives
  • A session outline with a practice task in each session
  • A coaching and follow-up plan for managers
  • Questions to check what stuck
  Source: Tuan Duc Tran.
• Skill progression map builder: Name a skill and student level. Get a suggested learning path, diagnostic tasks and next steps to review.
  • Ordered stages from prerequisite to mastery
  • Links showing what depends on what
  • Checks for each stage
  • Notes on common stuck points
  Source: Gareth Manning.
• me.md builder: Answer a few questions, or let your AI use what it remembers. Get one private file that tells any AI who you are.
  • One me.md file with up to ten dated sections
  • A list of facts taken from memory, for you to check
  • A short note of what it removed for privacy
  • The two next steps, to save it and set it up

Tasks you can use it for

• A host organisation is taking an intern and wants a plan before day one.
• A school or university asks for an internship plan that links tasks to learning goals.
• A placement lead has reviews coming and nobody has agreed what to look at.
• A mid-point review is due and the tasks have drifted away from the goals.

Limits to check before starting

• You need to decide whether to hire or pass on someone. This plans learning, not selection.
• A course has already run and you want to know what stuck. Use the Post-course skill reviewer workflow.
• You are planning one training session for a team. Use the Staff training session planner.
• You want skills for a whole company, not one role. Use the Job skills and level planner on its own.

Best way to use this role

Give it one clear outcome, the actual files and a definition of done. Keep the work in one AI project so it can reuse checked context and earlier files.

• Download the handoff pack. It is a zip with HANDOFF.md and every skill file this workflow uses.
• Give the folder to Claude, ChatGPT or Gemini and say "Follow HANDOFF.md".
• Paste the role, the approved tasks, the learning goals, your review dates and the weekly time available.
• Show the skills list to the supervisor before the plan is written. Remove any skill the host cannot give practice in.
• Share the plan with the intern. Take the review guide to each review and fill in the evidence.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/plan-an-internship-learning-review for its role instructions and pinned sources.

This is a prepared AI role. No task has run. Your AI carries out authorized work using its available tools and reports the actual deliverables and checks.