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Great content, thanks

Really nice, thanks for sharing

Can you share the demo repo?

Great talk! 😃

Great talk - thank you:)

As a newcomer to this, this was incredibly enlightening! My take-way is that yes, with some proper prompts for complex solutions, you get very close to "I might as well have done the whole thing myself". The point is the scaling: you go through these steps, because you then have a "prompt model" that you can use over and over for similar tasks.

cringe

Great Talk!

This is the kind of video where you do the "Fabric - Extract Wisdom" magic on.

great talk :) thank you

About the guarding post problem: posts, gate, Hasam . . . 3 different words for the same thing. Seems like a rookie misstake to me.

nice:)

nice:)

Thanks but the colab file is not accessible. Kindly check

What is the name of the platform mentioned at 50:38? I can't understand it enough to catch the name, thanks.

Best video I've seen on Prompt Engineering, thanks.

Thank you so much.

love the content, real value no bs no hype... massive knowledge drop thanks

TL;DR? Any top highlights?

I can't access to colab file can somebody help me about it?

Great presentation! Including your channel to my paid subs in tomorrows webinar!

Thanks a lot, I benefited a lot from this seminar.

Great Material! Thanks

Wow ! That was useful. Many thanks Jonathan !

Jonathan, thank you so much for this. I have been at quest where I have been studying many different techniques when it comes to extraction of data in form of products from a database we have. I have now developed a technique, but the hardest part that I have worked with several months is making the llm to update it's chunks from the database as it is a cost/performance balance that we are trying to achieve. We are very close, and we have seen that how we structure our data is as important as the base prompt. We are using retrieval augmented generation also. Can you please comment on this or make a video. I think this will be benifitial to many in the future. Thank you again, very good content.

Your tutorial is superb. If you may, do you have a PDF copy of prompting examples as shown in this video? It would greatly help so we'll just copy and paste to test and actually play with those prompting examples for more interactive learning.

You forgot swearing as a prompt technique. The other day I was prompting a woman with a skirt and kept images of her in a pair of jeans, no matter how many parentheses I put around the word (((skirt))). Finally I lost my patience and wrote "She is wearing a f***ing skirt!" and it worked like a charm :D

Excellent.

Very interesting review of the already available use cases and a great change management approach to achieve real value in the implementation!

Brilliantly clear and covered heaps! Legend

Shai great talk and example. thank you for putting this together. much appreciate.

Exciting to see this high level professionalism and innovation!

Great talk - thank you for sharing:) I agree with the final thoughts - learning AI by doing:)

I finished the whole talk, it's really great to see such wonderful talk. Continue such work and bring experts.😊

Great examples - Thank you for sharing:)

Great presentation - thank you for sharing:)

Behazlaha!

Thanks for your content it is great!

This was amazing. I'ld love to see more content on prompt engineering from you!

Amazing video! I wonder if there any puzzles / challenges for learning prompts? Would be a fun way to learn!

thank you for tips how to prompt:)

Great session! Keep these coming

just curious, why use chinese word "host" as your channel's logo, and "shujin" sounds a lot like the chinese pronunciation, or the japanese pronunciation?