Prepare the work
Select representative tasks, source documents, decision points, users, and the problems the team currently encounters.
A 2-to-4-week enablement program built around the department's real documents, decisions, recurring tasks, information boundaries, and review responsibilities.

The work starts before the workshop and continues long enough to see whether the method survives normal team use.
Training follows one representative workflow from source material to final review. The team practices the full method, not isolated prompt tricks.
Select representative tasks, source documents, decision points, users, and the problems the team currently encounters.
Define what information may enter the tools, what requires approval, and which outputs need human verification.
Use ChatGPT, Claude, or both to complete real exercises, inspect weak output, revise instructions, and assign review.
After practice, examine usage, corrections, questions, and workarounds before setting the next team standard.
The program ends with material the department can use, update, and teach to new employees.
Exercises and discussion tied to the department's own decisions, files, communication, and recurring work.
Tested instructions, source requirements, examples, expected outputs, and review checks for the selected workflows.
A plain-language record of what may be used, what needs approval, and what should stay outside an AI tool.
Named owners, practice tasks, support questions, and the small set of signals the team will review after rollout.
The program is configured around one team's actual work. It is not the same slide deck delivered to every audience.
Procedures, recurring reports, handoffs, document review, internal questions, and process records.
Research, briefs, campaign planning, interview material, drafts, analysis, and review.
User research, requirements, knowledge retrieval, response preparation, escalations, and quality checks.
Meeting material, planning, policy review, scenario analysis, and responsible team adoption.
Participants learn how to give useful instructions and how to inspect the result. A named person still owns facts, commitments, approvals, and the final work.
Start a training briefGoal, context, constraints, source material, and required output.
Compare, verify, and cite important information rather than accepting fluent output as fact.
Work with reports, policies, spreadsheets, PDFs, notes, and longer reference material.
Turn one good result into a method other employees can follow and inspect.
This engagement does not create company-wide AI policy, select and procure an enterprise platform, or build custom production software. Those needs can be scoped separately after the training evidence is reviewed.
Yes. That is the point of the program. HAWT first helps the team decide what material is appropriate to use and what should remain outside the tools.
A shared introduction can include a larger group, but the working program is strongest when one department can practice against the same responsibilities and source material.
Not always. The required plan depends on the tool and exercises. HAWT confirms access requirements before the live session.
The findings can become the starting point for a separate Workflow Pilot. Development is not added to the training scope without a new brief and decision.
Share the department, current tools, recurring work, and any privacy or approval constraints.