Help teams move from asking AI to getting work done.
Designed and led practical training in AI and agents for business teams, covering safe use, task planning, WorkBuddy and reusable workflows. Assessed assignments and reviewed employee-built tools to support adoption.
Employees were already trying AI. Applying it to real work required more than access to a tool: they needed to choose suitable tasks, supply context, set permissions and check results through examples relevant to their roles.
Role-based tasks, WorkBuddy practice and assignment assessment connect goals, context, execution boundaries and acceptance criteria. Practical outputs inform further coaching and identify applications worth reviewing.
Use red, amber and green data categories, minimization and de-identification to explain input boundaries. Cover hallucinations, prompt injection and human review so employees can decide what to share and what to verify.
Choose suitable work and specify the goal, role, context, constraints, output format and acceptance criteria. Use follow-up questions to uncover missing information before execution.
Bring together workspaces, files, tools, permissions and task decomposition. Explain execution loops, context, memory and collaboration, with checkpoints, human handoffs and result review.
Capture useful task briefs, processing steps and review rules as role-specific Skills and workflows. Make the method reusable, adaptable and transferable to other tools.
Exercises cover file handling, information gathering, simple websites and repetitive tasks. Employees work with concrete inputs and deliverables, making the results useful to discuss and possible to inspect.
Task instructions are paired with permissions, context, checkpoints and human verification. Goals and acceptance criteria help employees decide whether an agent has finished, needs correction or requires a handoff.
Assess business relevance, completion and difficulty. Connect pre-training interest with practical performance to inform coaching, identify potential internal champions and select cases for further review.
89 employees at grade P3 and above attended. All 67 assignments were assessed; 44 earned high ratings in both business relevance and completion. Of the submitters, 21 also met the advanced task criterion and were identified as high-potential candidates. Exercises covered four types of work.
Design executable workflows for file handling, data preparation and repetitive operations.
Use prompts and Skills to collect and organize industry updates into usable outputs.
Turn a clear need into a working page and practice the journey from a task brief to a visible result.
Define users, inputs, outputs and scope for an efficiency tool or website, creating a basis for further development.
I built the curriculum around employee AI use and role-specific needs, and designed a separate management track for questioning, diagnosis and option comparison.
OUTPUTCourse outline, speaker notes, operation checklists and a decision-card template
I led two internal AI training sessions, connecting concepts with WorkBuddy demonstrations of task briefs, permissions and result review.
OUTPUTLive teaching, tool demonstrations and role-based exercises
I assessed assignments for relevance, completion and difficulty, then compared practical performance with pre-training seed scores.
OUTPUTAssignment ratings, department and role analysis, and potential champion identification
I reviewed employee-built tools for their use cases, supporting evidence, execution boundaries and maintainability, identifying what to verify and improve.
OUTPUTTool ratings, follow-up questions and adoption recommendations
Let’s discuss role-specific tasks, practical training and assessment for your team.
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