Custom Metadata Types vs Custom Settings vs Custom Labels 💬 In plain words: Three lookalikes: Custom Metadata = configuration that DEPLOYS with your code (best for app settings). Custom Settings = org/user-specific values, changeable at runtime (hierarchy type is great for bypass switches). Custom Labels = translatable text for the UI. 📌 Example: API endpoint URLs per environment → Custom Metadata (deploys with code, sandbox vs prod values). A 'Bypass_Automation__c' checkbox an admin flips during data load → hierarchy Custom Setting. The word 'Submit' translated to Hindi → Custom Label. 🎬 Real-Life Example: The Fee Table Trapped Inside Code Skyline charges a different delivery fee per city. Apex needs those rates on every booking. The Old/Bad Way: if (city == 'Delhi') fee = 50. Else if (city == 'Mumbai') fee = 65. … Every rate change is a code change, a test run, and a deployment. Why this is bad: Business data is trappe...
Generative AI is a type of artificial intelligence that can create new content based on existing data. This can be used to generate text, images, sounds, and other types of content. In Salesforce, generative AI can be used for a variety of purposes, including:
- Creating personalized customer experiences: Generative AI can be used to create personalized content for customers, such as product recommendations, email campaigns, and customer support tickets.
- Improving sales productivity: Generative AI can be used to generate leads, qualify prospects, and create sales proposals.
- Automating marketing tasks: Generative AI can be used to automate tasks such as email marketing, social media marketing, and content creation.
- Increasing operational efficiency: Generative AI can be used to automate tasks such as customer service, data entry, and reporting.
There are a number of different techniques that can be used for generative AI, including:
- Transformers: Transformers are a type of neural network that can be used to generate text. They are often used for tasks such as machine translation and text summarization.
- Generative adversarial networks (GANs): GANs are a type of neural network that can be used to generate images. They work by training two neural networks against each other. One network is the generator, which tries to create realistic images. The other network is the discriminator, which tries to distinguish between real and fake images.
- Variational autoencoders (VAEs): VAEs are a type of neural network that can be used to generate images and text. They work by encoding data into a latent space and then decoding it back into the original format.
Generative AI is a powerful tool that can be used to improve a variety of business processes. In Salesforce, generative AI can be used to create personalized customer experiences, improve sales productivity, automate marketing tasks, and increase operational efficiency.
Here are some resources where you can learn more about generative AI in Salesforce:
- Salesforce Trailhead: Generative AI Basics: https://trailhead.salesforce.com/content/learn/modules/generative-ai-basics
- Salesforce Blog: 3 Ways Generative AI Will Help Marketers Connect With Customers: https://www.salesforce.com/blog/outreach-marketing-use-cases-generative-ai/
- The 360 Blog from Salesforce: AI From A to Z: The Generative AI Glossary for Business Leaders: https://www.salesforce.com/blog/category/generative-ai/
I hope this blog has given you a basic understanding of generative AI in Salesforce. If you're interested in learning more, I encourage you to check out the resources I've linked to.