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How AWS Sales uses generative AI to streamline account planning

AWS Machine Learning

These documents are internally called account plans (APs). In 2024, this activity took an account manager (AM) up to 40 hours per customer. In this post, we showcase how the AWS Sales product team built the generative AI account plans draft assistant. Its a game-changer for serving my full portfolio of accounts.

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Your guide to generative AI and ML at AWS re:Invent 2024

AWS Machine Learning

In this session, learn best practices for effectively adopting generative AI in your organization. Learn how they created specialized agents for different tasks like account management, repos, pipeline management, and more to help their developers go faster. This session covers best practices for a responsible evaluation.

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New year, new CS: 2023 recap and what’s to come in 2024

Totango

As we kick off 2024, it’s time to reflect on the past year and look forward to what the future holds for customer success. We’re proud to have dedicated 13 years to cultivating best practices and expertise in the customer success software category.

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Best practices for building robust generative AI applications with Amazon Bedrock Agents – Part 1

AWS Machine Learning

This two-part series explores best practices for building generative AI applications using Amazon Bedrock Agents. It’s also a best practice to collect any extra information that would be shared with the agent in a production system. None What is the balance for the account 1234? Your appointment ID is XXXX.

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Build your gen AI–based text-to-SQL application using RAG, powered by Amazon Bedrock (Claude 3 Sonnet and Amazon Titan for embedding)

AWS Machine Learning

Prerequisites To create this solution, complete the following prerequisites: Sign up for an AWS account if you dont already have one. The produced query should be functional, efficient, and adhere to best practices in SQL query optimization. Enable model access for Amazon Titan Text Embeddings v2 and Anthropics Claude 3.5

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From RAG to fabric: Lessons learned from building real-world RAGs at GenAIIC – Part 2

AWS Machine Learning

The prompt uses XML tags following Anthropic’s Claude best practices. The analyst may ask questions such as “Show me all wells that produced oil on June 1st 2024,” “What well produced the most oil in June 2024?”, or “Plot the monthly oil production for well XZY for 2024.” Put your the code in tags. -

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2024 Expectations: The forefront of the next generation of customer success

Totango

We polled our Customer Advisory Board (CAB) at the end of last year to gauge which way they saw the pendulum shifting for CS in 2024. In fact, 63% of CAB members said their top 2024 prediction was that businesses would put more strategic and bottom-line emphasis on expansion versus acquisition to drive revenue growth.

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