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10 results for “early stage identification”
liking the answer, you can actually give a thumbs up. Or if you don't like the answer, sometimes customers don't give you thumbs down, but actually re regenerate the answer. So that is a clear indication that the initial answer that you generated is
35:15 / 36:25
from transcript35:15 – 36:25
of what is your what is it that you're trying to build? Like, you're trying to build a reliable application for their customers that's not going to do a bad thing. Like, it's always going to do the right thing. Or if it is doing a wrong thing, you ar
35:49 / 37:04
from transcript35:49 – 37:04
it corrects the course, fixes it, no problem, right? Now there are situations obviously when the problem is a little bit deeper than that, right? You click to try to fix but the problem persists. And sometimes even the problem persists but Lovable's
1:06:38 / 1:07:47
from transcript1:06:38 – 1:07:47
confirm what date they checked it out on, whether they have some kind of insurance on it. So those are all the subproblems that need to be figured out first. And then with that list of subproblems, you can distribute that to all different types of to
27:45 / 28:46
from transcript27:45 – 28:46
metric, you have a good visibility to how's the application and some models are performing. It might do something very dumb or it can cause you, like I know. Some something like crazy can happen. So so yeah. So so so I do think eval is very, very imp
26:13 / 27:16
from transcript26:13 – 27:16
in that sense, four different ways to debug. Attempt one of each only once, and I'll explain why in the end. First one is, again, every tool is different. I'll I'll reference Lovable's workflow, which is when something breaks, Lovable's agent is smar
1:06:00 / 1:07:04
from transcript1:06:00 – 1:07:04
Exactly. And by the way, that's not uncommon too. And it's not just time. It it takes an army of people. Look, you can imagine that any one engineer is an expert in networking and Kubernetes and storage. That's not possible. People have No. Expertise
21:01 / 22:07
from transcript21:01 – 22:07
When you give a marketing document to a chat GPT and say, I did this campaign last week. Next week, I'm going to reinvent, create a new campaign. It'll do a great job. But you can't do that with IT systems because you want Hawkeye to give you exactly
17:08 / 18:21
from transcript17:08 – 18:21
task straight up, it might kinda struggle with it. So instead, you give it this task and you say, hey. Don't answer this. Before answering it, tell me what are some subproblems that would need to be solved first? And then it gives you a list of subpr
25:30 / 26:30
from transcript25:30 – 26:30
...that really clearly to you and then goes to ask clarifying questions. So a lot of users, we believe, should not need to prompt engineer agents. Right? If your time is being spent hyper optimizing every line and question that you pass to one of these
18:02 / 19:05
from transcript18:02 – 19:05
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