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pydanticai

Pydantic AI

The evaluation of agentic applications is most effective when integrated into the development process, rather than being an afterthought. For this to succeed, developers must be able to mock both internal and external dependencies of the agent being built. PydanticAI introduces a groundbreaking framework that supports dependency injection from the start, enabling developers to build agentic applications with an evaluation-driven approach. An architectural parallel can be drawn to the historic Krakow Cloth Hall, a structure refined over centuries through evaluation-driven enhancements. Similarly, PydanticAI allows developers to iteratively address challenges during development, ensuring optimal outcomes. Challenges in Developing GenAI Applications Developers of LLM-based applications face recurring challenges, which become significant during production deployment: To address non-determinism, developers must adopt evaluation-driven development, a method akin to test-driven development. This approach focuses on designing software with guardrails, real-time monitoring, and human oversight, accommodating systems that are only x% correct. The Promise of PydanticAI PydanticAI stands out as an agent framework that supports dependency injection, model-agnostic workflows, and evaluation-driven development. Its design is Pythonic and simplifies testing by allowing the injection of mock dependencies. For instance, in contrast to frameworks like Langchain, where dependency injection is cumbersome, PydanticAI streamlines this process, making the workflows more readable and efficient. Building an Evaluation-Driven Application with PydanticAI Example Use Case: Evaluating Mountain Data By employing tools like Wikipedia as a data source, the agent can fetch accurate mountain heights during production. For testing, developers can inject mocked responses, ensuring predictable outputs and faster development cycles. Advancing Agentic Applications with PydanticAI PydanticAI provides the building blocks for creating scalable, evaluation-driven GenAI applications. Its support for dependency injection, structured outputs, and model-agnostic workflows addresses core challenges, empowering developers to create robust and adaptive LLM-powered systems. This paradigm shift ensures that evaluation is seamlessly embedded into the development lifecycle, paving the way for more reliable and efficient agentic applications. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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copilots and agentic ai

Transforming Industries and Redefining Workflows

The Rise of Agentic AI: Transforming Industries and Redefining Workflows Artificial Intelligence (AI) is evolving faster than we anticipated. No longer limited to predicting outcomes or generating content, AI systems are now capable of handling complex tasks and making autonomous decisions. This new era—driven by Agentic AI—is set to redefine the workplace and transform industries. From Prediction to Autonomy: The Three Waves of AI To understand where we’re headed, it’s important to see how far AI has come. Arun Parameswaran, SVP & MD of Salesforce India, describes it as a fundamental shift: “What has changed with agents is their ability to handle complex reasoning… and, most importantly, to take action.” Unlike previous AI models that recommend or predict, Agentic AI executes tasks, reshaping customer experiences and operational workflows. Agentic AI in Action: Industry Applications At a recent Mint x Salesforce India deep-dive event on AI, industry leaders explored how Agentic AI is driving transformation across sectors. The panel featured: Here’s how Agentic AI is already making an impact: 1. Revolutionizing Customer Support Traditional chatbots have limited capabilities. Agentic AI, however, understands urgency and context. 2. Accelerating Business Decisions In finance and supply chain management, AI agents analyze vast amounts of data and execute decisions autonomously. 3. Transforming Travel & Aviation Airlines are leveraging AI to optimize booking systems, reduce costs, and enhance efficiency. 4. Automating Wealth Management AI agents in financial services monitor markets, adjust strategies, and offer personalized investment recommendations in real time. The Risks & Responsibilities of Agentic AI With great autonomy comes great responsibility. The potential of Agentic AI is vast—but so are the challenges: The Future of Work: AI as a Partner, Not a Replacement Despite concerns about job displacement, AI is more likely to reshape rather than replace roles. What Are AI Agents? AI agents go beyond traditional models like ChatGPT or Gemini. They are proactive, self-learning systems that: They fall into two categories: “AI agents don’t just wait for commands; they anticipate needs and act,” says Dr. Tomer Simon, Chief Scientist at Microsoft Research Israel. AI Agents in the Workplace: A Shift in Roles AI agents streamline processes, but they don’t eliminate the need for human oversight. Salesforce’s Agentforce is a prime example: “Companies need to integrate AI, not fear it. Those who fail to adopt AI tools risk drowning in tasks AI can handle,” warns Dr. Omri Allouche, Chief Scientist at Gong. The Road Ahead: AI-Driven Business Growth Agentic AI is not about replacing people—it’s about empowering them. As organizations re-evaluate workflows and embrace AI collaboration, the companies that act early will gain a competitive edge in efficiency and innovation. Final Thought The AI revolution is here, and Agentic AI is at its forefront. The key question isn’t whether AI will transform industries—it’s how organizations will adapt and thrive in this new era. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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