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Atmrix

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C

Carlos

05/24/25

@ LangChain

Defining use cases and metrics before jumping on new tools is crucial for measuring success in AI implementations.

Video

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How AI Automation Powers 60% of Cisco’s 1.8M Support Cases | LangChain Interrupt

@ LangChain

How AI Automation Powers 60% of Cisco’s 1.8M Support Cases | LangChain Interrupt

05/24/25

Related Takeaways

SC

Sequoia Capital Cast

05/07/25

@ Sequoia Capital

Inspecting metrics like adoption, engagement, and retention is essential to understand how users interact with an AI product and its effectiveness.

DS

David Silver

04/11/25

@ Google DeepMind

We must be cautious about how we define metrics for AI systems to avoid unintended consequences, such as optimizing for the wrong outcomes.

a

a16z Cast

05/29/25

@ a16z

The challenge lies in defining the right measures of progress in AI evaluation, moving beyond traditional benchmarks.

a

a16z Cast

05/29/25

@ a16z

The challenge lies in defining the right measures of progress in AI evaluation, moving beyond traditional benchmarks.

C

Carlos

05/24/25

@ LangChain

Cisco's approach to AI involves defining use case criteria before implementation, ensuring that only valuable use cases are pursued.

WA

Waseem Alshikh

03/27/25

@ LangChain

Enterprise clients often have established metrics and performance indicators, allowing us to track how much time is spent on tasks and the impact of AI adoption.

JW

Josh Woodward

03/18/25

@ Sequoia Capital

Finding the right market fit is as crucial as developing the right product, especially in early-stage AI projects.

YC

Y Combinator Cast

11/06/24

@ Y Combinator

Don't just research new AI tools; be a real user and actively use them to improve your work efficiency.

MS

Michael Seibel

09/06/18

@ Y Combinator

Setting up metrics early in your company is crucial; it helps you understand product usage and inspires new ideas.