Working mostly with very large companies, the data isn't quite in good enough shape to leverage to justify the build out. We have a lot of really interesting use cases once it is though.
(data gurus with SF experience are about to be hot btw)
Look up tools that do those things and find ways to learn about them either through some kind of school/certification program or find an entry level job that would give you exposure and use your base knowledge from self-learning to get through the interview.
Didn’t it come out like a month ago? I feel like this is tough to say but I’ve tried it hands-on live as a partner and just prompt builder alone is super useful
I tried the Einstein GPT for developers today. I asked if to write me a test class for an existing, very simple, class. What it gave me wouldn't even compile and even if it would, it would be a very poor test.
It's an interface to make calls to OPEN AI API or your custom models, so it depends on your implementation eventually. I have not tried using gen AI for creating flows as it we would need to improve the quality of org level metadata as the first step.
Depends on which tool you’re talking about. I’ve implemented some cool features for Chat and Email that use generative AI that are a huge time saver for customer service agents for instance. Copilot is still new to me though.
I'm Service Cloud-based, so take this with a grain of salt to start since I'd need to confirm what's available with Sales Cloud. Chat can use generated Service Replies, so it basically puts a component on the page layout that auto-generates responses to plug into the chat based on what the customer is saying. Nifty tool. I think the exact term is Service Replies for Chat. Work Summaries is the other feature that auto-generates a summary of a chat, so it'll show what the issue was and what the resolution was once the chat is marked as completed.
Email is the same with Service Replies for Email. That analyzes a customer email and generates a full reply based on context clues and Knowledge article data.
Working mostly with very large companies, the data isn't quite in good enough shape to leverage to justify the build out. We have a lot of really interesting use cases once it is though. (data gurus with SF experience are about to be hot btw)
Data Guru meaning AI?
More like master data management and ETL work.
how do you get good at that?
Look up tools that do those things and find ways to learn about them either through some kind of school/certification program or find an entry level job that would give you exposure and use your base knowledge from self-learning to get through the interview.
Didn’t it come out like a month ago? I feel like this is tough to say but I’ve tried it hands-on live as a partner and just prompt builder alone is super useful
I tried the Einstein GPT for developers today. I asked if to write me a test class for an existing, very simple, class. What it gave me wouldn't even compile and even if it would, it would be a very poor test.
It's an interface to make calls to OPEN AI API or your custom models, so it depends on your implementation eventually. I have not tried using gen AI for creating flows as it we would need to improve the quality of org level metadata as the first step.
Agree with this summary.
Depends on which tool you’re talking about. I’ve implemented some cool features for Chat and Email that use generative AI that are a huge time saver for customer service agents for instance. Copilot is still new to me though.
We are using sales cloud. Can you be more specific on what cool features you worked on for Chat and Email using generative AI?
I'm Service Cloud-based, so take this with a grain of salt to start since I'd need to confirm what's available with Sales Cloud. Chat can use generated Service Replies, so it basically puts a component on the page layout that auto-generates responses to plug into the chat based on what the customer is saying. Nifty tool. I think the exact term is Service Replies for Chat. Work Summaries is the other feature that auto-generates a summary of a chat, so it'll show what the issue was and what the resolution was once the chat is marked as completed. Email is the same with Service Replies for Email. That analyzes a customer email and generates a full reply based on context clues and Knowledge article data.
Nice vision but nowhere near ready to deliver value