Instructions with context
Practice defining a task, supplying context and describing a useful result.
I help teams use AI tools on real tasks, evaluate results and understand limitations. We start with how you work, not a list of features.
Let’s talkFor teams with access to AI tools that want to move from individual experiments to clear, useful everyday practices.
Practice defining a task, supplying context and describing a useful result.
Compare output against sources, identify assumptions and discuss when a response is not reliable enough to use.
Take a recurring task and try an AI-assisted approach with explicit review points.
Possible use cases, not client results.
Exact deliverables are agreed together, based on scope and available access.
Discuss roles, current experience, approved tools and the tasks your team wants to improve.
Work through examples, compare results and adjust the approach. Use only data appropriate for the chosen tools.
Define practices the team can repeat and identify questions that need more exploration.
Training does not replace internal data and access policies. Examples must respect those rules, and confidential information should not be entered into unapproved tools.
Not for sessions on practical use of AI tools. For integration or development topics, we adapt the content to the group’s technical experience.
Yes, that is the starting point. We select examples together and use approved, anonymized or fictional data as appropriate.
We start with objectives, group size, participants’ experience and available time. Then we agree on topics, format and duration rather than assuming one session suits everyone.
Tell me how many people are involved, which tools you use and which tasks you would like to approach with AI.
Let’s talk