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Dev Interrupted
Making Sense of Agentic AI | ThoughtWorks Birgitta Boeckeler
Nov 12, 2024
Birgitta Boeckeler, Global Lead for AI Assisted Software Delivery at ThoughtWorks, dives into the transformative potential of AI in software development. She shares her insights on agentic AI, discussing its real-world applications and the limitations developers face, especially with legacy codes. Birgitta also emphasizes the importance of clear use cases for successful AI integration and the balance needed to avoid tool fatigue. Joining her, Dan Lines highlights how engineering leaders can measure AI's impact on their teams and refine coding practices for better outcomes.
47:40
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Quick takeaways
- Agentic AI has the potential to enhance software development by autonomously executing tasks, though it still faces challenges with legacy systems.
- Understanding the context of AI tools, including code repositories and documentation, is crucial for optimizing their effectiveness in software delivery.
Deep dives
Understanding Agentic AI
Agentic AI refers to artificial intelligence systems that operate as agents, meaning they can autonomously execute tasks and make decisions based on given parameters. This type of AI can interact with external tools and provide actionable insights or outputs, such as code generation or testing. The defining characteristic is its ability to communicate with various applications and tools, allowing it to act with a degree of independence. The potential for these systems to enhance software development processes lies in their ability to streamline tasks and improve productivity across different domains.
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