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Practical AI Lunch-and-Learn

One live hour on a real problem your team already has.

The Practical AI Lunch-and-Learn is a $750, one-hour virtual session for up to 30 people, built around a real business topic instead of a general AI demonstration. It's the lowest-commitment way to bring practical AI training to your team.

$750

One fixed proposal price, paid in full when scheduled.

Includes up to 30 attendees. Custom development, if needed, is $250/hr quoted in advance. Recording license: $750.

Who this is for

Teams who want a low-commitment first step: practical instruction, Q&A, and one specific recommendation for what to do next. A good fit for a first conversation with a new team, or a focused refresher for a specific department.

What's included

  • One live virtual hour for up to 30 attendees
  • Practical instruction built around a topic you pick
  • Live Q&A
  • One specific recommendation for what to do next

What you have at the end

A team that's heard the same instruction at the same time, and one concrete next step to act on. Add the internal-use recording license ($750) if you want people who missed it to catch up.

What this does not include

Common questions, plain answers.

How is this different from a public workshop?

A public workshop is open registration for individuals. A Lunch-and-Learn is a private session for your team, built around a topic you pick, not a general AI demo.

Can we get a recording?

Not by default. A permanent internal-use recording license is available for an additional $750.

What if our topic needs new material?

If the session needs original research, new examples, revised slides, or exercises, custom development is $250 per approved hour, quoted in advance and rolled into one fixed price before you decide.

Do you come onsite?

This offer is delivered live, virtually. Onsite training is available as a larger engagement — see the rate card on the Services page.

When is pricing reviewed?

Pricing is reviewed on January 31, 2027. Any change will be based on the actual customer base at that point rather than promised in advance.