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Welcome to a brand new way of hearing about the latest Copilot extensibility news! In this episode of the Copilot Connection, Kevin swaps out Zoe for Garry Trinder in the first of a spin-off of episodes where we dig deeper into the extensibility side of Copilot.
In this first episode, we go into an overview of the options that you have for extending Copilot. We talk cover why you would need to extend Copilot, the different ways you can do that (whether by end user, maker or specialist) and touch a little on how you can actually get started with doing it.
Is there a specific topic that you'd like to see us cover? Let us know!
Takeaways
- Extensibility in Copilot allows developers to create tailored solutions.
- Understanding AI maturity is crucial for effective implementation.
- Personalization of AI tools enhances user experience and productivity.
- Scoping and context are essential for effective use of Copilot.
- Integrating external knowledge sources can enhance AI capabilities.
- Balancing deterministic and non-deterministic approaches is key in AI applications.
- Declarative agents simplify the process of building AI solutions.
- Responsible AI practices are necessary when developing custom solutions.
- Continuous learning and adaptation are vital in the evolving AI landscape.
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