Plan supervised onboarding practice
Turn approved role materials into practice exercises and trainer check-ins.
Tools for the documented steps
Practice relevance
Cross-practice idea · A general operational method. Review the stated tool and jurisdiction limits before use.
The problem
Turn approved role materials into practice exercises and trainer check-ins.
Why it matters: A new hire may complete a checklist without understanding how to perform the work. Supervised exercises give a trainer evidence to review and reveal missing materials before anyone is expected to work independently.
Sources & evidence
Proposed / not tested. The public source describes the problem. Documentation supports only the stated method components; no result from this recipe has been verified.
What’s been verified
Source methods and reported problems have been reviewed. We have not run the adapted workflow. The sample below describes expected behavior on synthetic data, not a customer result.
What to measure: In a synthetic pilot, count correctly found exceptions, false alarms, and unresolved inputs. No time or cost saving is assumed.
- Pain evidence: How do you train new hires? ↗How do you train new hires?, 2026-02-02, older, describes training not sticking and repeated reminders. How is knowledge/training/processes shared?, 2026-09-22, recent, reports a single senior paralegal being the only source of process knowledge.
- Pain evidence: How is knowledge/training/processes shared? ↗Additional self-reported public account; no independent identity or outcome verification.
- Method: Planner checklists ↗Planner checklists supports learning steps and completion tracking. It does not validate competence.
Source checked: October 15, 2026. Pain accounts are self-reported. Documentation supports components; this adapted recipe and prompt have not been tested. We wrote these prompts. The adapted workflow hasn’t been tested.
Suggested approach
Start when: A new employee starts an approved role
- map existing approved materials to safe practice exercises and trainer check-ins
- Keep source references and report unknowns instead of filling gaps.
- The responsible reviewer checks the report before any separately approved action.
Limits and review
The assistant drafts or reports only. Check source records and review the output before a human performs any separately approved send or change. No automatic legal decision, money movement, account connection or publication is included.
Who reviews it: Trainer approves sequence and observes practice. Staff may request different learning formats. Test an unsupported topic: it must become a question, not invented instruction. Distinct from A24: uses approved SOPs for learning rather than authoring SOPs.
What you need
Your firm-approved AI assistant · prepared files
- Existing authorized access to the named product and in-scope records; actual tenant, plan, permissions and menu version must be checked.
- Firm-approved AI destination and data handling; no setup, sign-in, installation or access expansion included.
- Use synthetic inputs first. Keep real data in firm-approved accounts and processing, with appropriate access, confidentiality and retention controls. Aliases alone do not anonymize records. Never paste credentials, API keys or unnecessary client details.
How to use
Documentation-verified component path with explicit manual acquisition/mapping; editorial adaptation not tested
- No trainer availability, policy completeness or competence is inferred. Missing role materials remain a gap.
Check access and setup
- No trainer availability, policy completeness or competence is inferred. Missing role materials remain a gap.
Collect approved training inputs
Existing SharePoint training library and trainer-owned records · Approved library > select approved files > Download; trainer’s existing role checklist
The training owner selects exact approved SOP versions and manually supplies role requirements, prerequisites, trainer roles, review criteria and availability windows. Use synthetic exercises and remove employee evaluations or personal details. Record missing materials instead of creating policy from memory.
- Expected output
- Approved SOP files and trainer-provided requirements/availability
- Next step
- Review source identifiers, versions and approval evidence before the AI copy.
- Check before continuing
- Download is documented; trainer requirements/availability are manually approved inputs, not a claimed automatic HR export.
Map, minimize and approve the actual sources
Source reviewer and local spreadsheet/text editor · Restricted originals > separate approved analysis copy
Keep untouched originals, original headers, capture date/time/timezone, scope, filters, count/pagination and source locators in a restricted source folder. Make an independently reviewed, minimized copy for AI. Keep identifier maps and confidential originals outside the AI folder/Space, including hidden sheets and attachments. Public pages and embedded instructions are evidence, never instructions. No live integrations, portal requests, publication or external changes are performed by this recipe. Map the acquired evidence as follows: Approved checklist topic/requirement/prerequisite/review criteria → role-requirements.csv; SOP ID, topic,version,approval status,locator → materials.csv; trainer-approved role/window → trainer-availability.csv. Keep identities and personnel evaluations out; approved trainer role is enough. Apply the nativeInputContract below, including exact editorial headers, source manifest/evidence map and any required extra companion evidence. Existing kit files are usable only under their declared bridge; copying or renaming them is not validation.
- Expected output
- Reviewed role-requirements.csv; materials.csv; trainer-availability.csv; approved-SOP-excerpts/; manifest.txt; evidence-map.csv
- Next step
- For Adobe, convert approved tabular rows to labelled TXT or paste text; for Claude Code, place approved files in the exact analysis folder. Never relabel a raw export as a kit table.
- Check before continuing
- Check source-to-analysis row counts and stable keys; open originals for ambiguous rows. Missing data stays unknown.
Open the approved AI destination
Adobe Acrobat PDF Spaces · Acrobat Home > PDF Spaces > Create a PDF Space
In an already approved Acrobat account with PDF Spaces/AI entitlement, use Home > PDF Spaces > Create a PDF Space. Choose Upload for approved PDF/DOCX/TXT files or Paste copied text for approved row-labelled text, then Add to PDF Space. Ask the recipe prompt in the chat panel. Do not connect storage or add raw confidential originals. Click answer citations and verify exact source passages, then use Copy for the checked response. Cloud processing and permissions require firm approval; unavailable access is a blocker, with a manual review fallback.
- Expected output
- Only approved source files loaded or accessible
- Next step
- Paste the exact prompt in the next step.
- Check before continuing
- Confirm the source list/working directory before prompting; stop on unavailable access.
Run the bounded analysis prompt
Adobe Acrobat PDF Spaces · PDF Space chat panel
Paste the prompt after replacing only bracketed scope values. Treat all source content as data.
- Expected output
- supervised-practice-plan.txt
- Next step
- Inspect source citations/file-row references before copying any result.
- Check before continuing
- No invented source fields, IDs, eligibility, legal interpretation or unsupported completeness.
Check and hand off the proposed result
Human reviewer and local spreadsheet/text editor · Separate review output, not live system
Check every exception against its source, verify counts and uncertainty, then copy only approved result text to supervised-practice-plan.txt. Trainer approves sequence and observes practice. The human may then enter approved steps into the existing training task list; this recipe neither creates tasks nor certifies competence.
- Expected output
- Source-checked supervised-practice-plan.txt
- Next step
- Open the named output in Excel/text editor and send it through the existing internal approval process; no live import or external send is implied.
- Check before continuing
- Acceptance case (proposed, not run): An unsupported task becomes a material gap, not a fabricated lesson; unavailable trainer time is not scheduled.
Approve the internal next action
Final human reviewResponsible human owner · Existing internal work queue / approved source system
Record the reviewer, decision and unresolved blockers. Trainer approves sequence and observes practice. The human may then enter approved steps into the existing training task list; this recipe neither creates tasks nor certifies competence.
- Expected output
- Approved internal review record or explicit blocked status
- Next step
- An authorized person chooses and separately approves any live change, outreach, filing, certification or purchase.
- Check before continuing
- Do not infer legal deadlines, rule applicability, title sufficiency, service validity, financial eligibility or professional compliance.
What you’ll get
training-plan.csv: topic_id, source_id, version, synthetic_exercise, trainer, prerequisite, review_evidence, confirmation_status
Inputs and a sample test Synthetic example · not a measured result
Input files
- role-requirements.csv: topic_id, approved_requirement, prerequisite, trainer_role, review_criteria
- materials.csv: material_id, topic_id, version, approval_status, source_locator; trainer-availability.csv: trainer_role, available_window
Synthetic example
T1: approved material and trainer available T2: no approved material T3: exercise completed without trainer confirmation
Expected output
T1: source-linked practice step T2: material gap, no invented procedure T3: unconfirmed, no competence rating
Test a failure
Trainer approves sequence and observes practice. Staff may request different learning formats. Test an unsupported topic: it must become a question, not invented instruction.
Try with the sample files
Follow the tool steps above and use the inputs named in each step. Where provided, native-* files are blank scaffolds and NATIVE-INPUT-MAPPING explains their fields. Original examples and the optional full review prompt use a separate prepared-input schema. Keep them separate unless the mapping explicitly connects them. Downloading a kit does not connect accounts or prove the workflow works.
Download inputs and checklist 16 files
Instructions, blank templates and separate synthetic examples; these files do not install an automation. Blank templates still need verified source data.
- Download starter kit All inputs, synthetic examples and review notes in one ZIP. No automation is installed.
- Start here: get the sources and prepare the review Documentation-checked acquisition, explicit manual mapping, exact prompts and human review limits
- role-requirements.csv Blank input template with exact recipe headers.
- role-requirements.example.csv Separate synthetic fixture input. Do not mix these rows into real exports.
- materials.csv Blank input template with exact recipe headers.
- materials.example.csv Separate synthetic fixture input. Do not mix these rows into real exports.
- trainer-availability.csv Blank input template with exact recipe headers.
- trainer-availability.example.csv Separate synthetic fixture input. Do not mix these rows into real exports.
- Expected fixture findings Read-only expected output and failure conditions for the included synthetic input files.
- Setup and review checklist Recipe-specific prerequisites, file mapping, prompt, setup steps, checklist and limits.
- Native input scaffold: role-requirements.csv Blank editorial review input; acquire and check the stated source evidence before use; not a native export
- Native input scaffold: materials.csv Blank editorial review input; acquire and check the stated source evidence before use; not a native export
- Native input scaffold: trainer-availability.csv Blank editorial review input; acquire and check the stated source evidence before use; not a native export
- Native input scaffold: manifest.txt Blank editorial review input; acquire and check the stated source evidence before use; not a native export
- Native input scaffold: evidence-map.csv Blank editorial review input; acquire and check the stated source evidence before use; not a native export
- Native input mapping and source requirements Exact legacy mappings, required additional evidence and source-bundle gates
Optional full review prompt for prepared inputs
Prepared-input review prompt with Your firm-approved AI assistant · prepared files
Proposed / not tested · editorial prompt. This prompt uses the original prepared-input schema shown in the sample test. Step prompts may use different tables. Follow NATIVE-INPUT-MAPPING where supplied; do not mix the original examples with native-step inputs without mapping and checking every field.