Speakers in the public record
Claim mix
evaluation 6belief 4recommendation 4uncertainty 1preference 1
Evidence policy
Every row below preserves an exact excerpt. Identified speakers are linked; unresolved voices are labeled and excluded from people counts.
Claim ledger
The useful parts, with receipts.
16 published records
“Well, that won't affect the performance of the model all that much, because the main thing it takes away from the few-shot prompt is the structure of the output rather than the content of the output.”
- Speaker
- Not verified from transcript
- Publisher
- Latent Space
“Then once you get to thought generation, people start to think, what is going on here? So I think everybody, well, not everybody, but people that were tweaking with these things early on saw the take a deep breath, and things step-by-step, and all these different techniques that the people had.”
- Publisher
- Latent Space
“I think you've done a great job at grouping the types of mistakes that people make.”
- Publisher
- Latent Space
“Just to set the timeline, when did each of these things came out? So Learn Prompting, I think was like October 22.”
- Publisher
- Latent Space
“I actually might tweak my approach based on that, because I was trying to give bad examples of do not do this, and it still does it, and maybe that doesn't work.”
- Publisher
- Latent Space
“I guess the best way to go through this, you know, you picked out 58 techniques out of your, I don't know, 4,000 papers that you reviewed, maybe we just pick through a few of these that are special to you and discuss them a little bit.”
- Publisher
- Latent Space
“I would absolutely recommend using these, DSPy in particular, because it's just so easy to set up.”
- Speaker
- Not verified from transcript
- Publisher
- Latent Space
“I think for AI companies, it's definitely useful to have like a prompt engineer who knows everything about prompting because their clientele wants to know about that.”
- Speaker
- Not verified from transcript
- Publisher
- Latent Space
“There's a couple of papers that directly analyze the technique and show it doesn't work in a lot of cases.”
- Speaker
- Not verified from transcript
- Publisher
- Latent Space
“Prompt Layer, Braintrust, PromptFu, and HumanLoop, I guess would be my top picks from that category of people. And there's probably others that I don't know about.”
- Publisher
- Latent Space
“So obviously there's a lot of interest. And I think some of the initial jailbreaks, I got fine-tuned back into the model, obviously they don't work anymore.”
- Publisher
- Latent Space
“I think one problem for me for designing these things with cost awareness is the question of, well, okay, at the baseline, you can just use the same model for everything, but realistically you have a range of models, and actually you just want to sample all range.”
- Publisher
- Latent Space
“Endorse all that. And I think getting things into structured output and doing those scoring is a very core part of AI engineering that we don't talk about enough.”
- Publisher
- Latent Space
“I'll call out two recent papers which people might want to look into, which is a Salesforce yesterday released a paper called Diversity Empowered Intelligence, which is a, I think a shot at the bow for scale AI.”
- Publisher
- Latent Space
“You've done very well. And I think you've honestly done the community a service by reading all these papers so that we don't have to, because the joke is often that, you know, what is one prompt is like then inflated into like a 10 page PDF that's posted on archive.”
- Publisher
- Latent Space
“We just assume that people roughly know, but yeah, I think a dedicated episode directly on this, I think is something that's sorely needed. And then, you know, something I prompted Sander with is when I wrote about the rise of the AI engineer, it was actually a direct opposition to the rise of the prompt engineer, right?”
- Publisher
- Latent Space