// About the talk
Most people talk to AI like they're Googling - and get mediocre results to match. Your prompt is not a question, it's a work brief. The moment you understand that difference, every model starts giving you output you can actually rely on. A practical talk on context, constraints, and chain-of-thought - the three practices that get AI producing real output, not just answers that sound good.
// What your team walks away with
- 01Why bigger prompt ≠ better results - and what actually changes the quality
- 02Context: what the model really needs to know before you ask it anything - and what's noise
- 03Constraints: how to tell the model what not to do before it does it
- 04Chain-of-Thought: why asking a model to think out loud changes the entire output
// Who this talk is for
- 01Every employee in an organization who uses AI and wants to get more out of it
- 02Managers who want their team to extract more value from the tools they're already paying for
- 03Teams who want to learn prompt engineering from real experience - not theory
// Organizations that invited me
Technology Companies
Conferences & Community
Organizations & Institutions
//Organizer questions
What organizers ask before booking
In person or online?
Both. Every talk in the catalog is available in person or online.
Can the talk be in English?
Yes. The talks are available in Hebrew and English. (I spoke in English at PyCon UK 2025, for example.)
Is the talk tailored to our team?
Yes. Every talk gets tailored. Your industry, your challenges, your language. I don't do generic. That's the whole point.
What happens after we reach out?
Tell me about the audience and date, and you'll get a personal reply within 48 hours. (If it's not a fit, I'll say so.)
Want to bring this talk to your team?
30 minutes. No pitch. Just a conversation about what your team needs - and how this talk fits.