A shared picture
Some people use AI every day, some never tried it, some are worried about it. A good talk brings everyone to the same starting point in one session.
A lecture on AI that people act on the next morning.
No hype and no science fiction. A clear, practical picture of what AI does in daily work today, with live examples from real systems and a short list of what to do next. For a company meeting, a team day or a conference.
What a room needs
What a room usually needs.
Real examples, not slides of logos
People remember what they saw working: an agent drafting a reply, a meeting turned into tasks. A live example beats a prediction.
A next step
An inspiring session is wasted if nothing changes the following week. Every talk ends with concrete first steps people can take on their own.
Talks
Talks and a hands-on workshop.
Each talk is adapted to the audience and the industry. These topics are the starting point; the final outline is agreed with you.
- AI at work, without the hype. What the tools really do today, where they fail, and how teams use them safely. For any audience.
- From tools to systems: AI agents in daily operations. Live examples of agents that sort email, summarize meetings and build reports, and what it takes to run them responsibly.
- Why AI projects stall, and what makes them stick. The people side: habits, concerns, rules and ownership. Built on a background in behavioral change.
- Hands-on workshop. Participants work on their own tasks with the tools, and leave with a short guide to keep.
What the organizer gets
A short coordination call to fit the content to the audience, the talk itself, and a one-page summary with the first steps, to share with participants afterwards.
How it runs
How booking a talk works.
Short call
Date, audience, size, format and what you want people to leave with.
Outline
I send a short outline adapted to your audience and industry, for your approval.
The talk
In person or online, in Hebrew or English, with live examples and time for questions.
After
A one-page summary for participants. If the room wants more, the next step can be a workshop for a team.
Who brings what
What we need, and what people take away.
What we need from you
- The date, the place or the online link, and the expected audience size.
- A few words on who will be in the room and what they already know.
- A screen and a stable internet connection for the live examples.
- A contact person on the day.
What participants take away
- A clear picture of what AI does well today, and where it fails.
- Real examples they can connect to their own work.
- Simple rules for using AI safely with company data.
- Three first steps to take the following week.
Proof
What this looks like in practice.
A digital analytics firm: three AI systems at work
One mapping session, then three systems built on the firm's own Claude account: email triage with replies drafted in the owner's writing style and a folder opened automatically for every new client, meeting summaries with decisions and tasks, and client-branded reports built from analytics data.
All three were running within two weeks of the first working session. Anything that goes to a client stays a draft until the owner sends it. The client's name stays private until they agree to be named.
My own business runs the same way
Agents prepare my meeting summaries, follow-ups, client records and draft replies. I read, correct and approve what goes out. I use what I recommend.
The AI Daily Brief
Every morning a pipeline I built reads about 30 sources, checks each item against its source and publishes up to three updates in Hebrew and English. It runs on its own, within written rules on what it may publish.
Five stages, written down
Every engagement follows the Leverage‑to‑Ownership Method: map, train, build, lock in the rules, hand over. You always know which stage you are in and what you own at the end of it.
Questions
Straight answers, before you book.
Lecture, workshop or implementation: what's the difference?
A lecture gives a room a shared picture in one session. A workshop gets a team using the tools on its own tasks. Implementation builds systems into the work itself. A lecture is often the first step before the other two.
How long is a talk?
Usually 45 to 60 minutes, including questions. A hands-on workshop runs about 3 hours.
Can it fit our industry?
Yes. The examples are chosen for the room: a law firm sees document work, an operations team sees reporting, a sales team sees follow-ups.
In person or online?
Both work. In person in Israel, or online from anywhere.
Hebrew or English?
Either. The slides and the summary come in the same language as the talk.
What drives the cost?
The format and length, in person or online, travel, and how much the content is tailored. There are no prices on this site: send the date and the audience, and you get a written proposal.
Do you show real systems or slides?
Real systems wherever the setting allows: agents at work and real drafts, with client details removed.
What about data and safety?
Every talk covers the basics: what may go into which tool, how to check AI output, and what needs a person's approval.
What it isn't
What the talk is not.
- Futurism and predictions for 2040. The talk is about the work of the coming weeks.
- A sales pitch dressed up as a talk. The talk stands on its own.
- A technical session for developers.
Next step
Tell me the date and the audience.
There are no prices on this site. After the first conversation you get a scoped proposal in writing. On WhatsApp, the message opens with a few short questions, so the first reply can already be useful.
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