Chain of Thought

As DeepSeek so aptly demonstrated, AI doesn’t need to be closed source to be successful. This week, Rizel Scarlett, a Staff Developer Advocate at Block, joins Conor Bronsdon to discuss the intersections between AI, open source, and developer advocacy. Rizel shares her journey into the world of AI, her passion for empowering developers, and her work on Block's new AI initiative, Goose, an on-machine developer agent designed to automate engineering tasks and enhance productivity. Conor and Rizel also explore how AI can enable psychological safety, especially for junior developers. Building on this theme of community, they also dive into topics such as responsible AI development, ethical considerations in AI, and the impact of community involvement when building open source developer tools. Chapters: 00:00 Rizel's Role at Block 02:41 Introducing Goose: Block's AI Agent 06:30 Psychological Safety and AI for Developers 11:24 AI Tools and Team Dynamics 17:28 Open Source AI and Community Involvement 25:29 Future of AI in Developer Communities 27:47 Responsible and Ethical Use of AI 31:34 Conclusion Follow Conor Bronsdon: https://www.linkedin.com/in/conorbronsdon/ Rizel Scarlett LinkedIn: https://www.linkedin.com/in/rizel-bobb-semple/ Website: https://blackgirlbytes.dev/ Show Notes Learn more about Goose: https://block.github.io/goose/

"In the next three to five years, every piece of software that is built on this planet will have some sort of AI baked into it." - Atin Sanyal Chain of Thought is back for its second season, and this episode dives headfirst into the possibilities AI holds for 2025 and beyond. Join Conor Bronson as he chats with Galileo co-founders Yash Sheth (COO) and Atindriyo Sanyal (CTO) about major trends to look for this year. These include AI finding its product "tool stack" fit, generation latency decreasing, AI agents, their potential to revolutionize code generation and other industries, and the crucial role of robust evaluation tools in ensuring the responsible and effective deployment of these agents. Yash and Atin also highlight Galileo's focus on building trust and security in AI applications through scalable evaluation intelligence. They emphasize the importance of quantifying application behavior, enforcing metrics in production, and adapting to the evolving needs of AI development. Finally, they discuss Galileo's vision for the future and their active pursuit of partnerships in 2025 to contribute to a more reliable and trustworthy AI ecosystem. Chapters: 00:00 AI Trends and Predictions for 2025 02:55 Advancements in LLMs and Code Generation 05:16 Challenges and Opportunities in AI Development 10:40 Evaluating AI Agents and Applications 16:07 Building Evaluation Intelligence 23:41 Research Opportunities 29:50 Advice for Leveraging AI in 2025 32:00 Closing Remarks Show Notes: Check out Galileo⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow Yash Follow Atin Follow Conor

Join Bob van Luijt, CEO and co-founder of Weaviate, an AI-native database innovator, as he dives into the future of AI infrastructure. He passionately asserts that now is the time to build and adapt to evolving tech. Bob discusses the importance of generative feedback loops and agent architectures, which could revolutionize data management. They also tackle the challenges of documentation and developer experience as key factors for successful AI implementation. Prepare for insights that inspire action and innovation in the AI landscape!

Vinnie Giarrusso, Principal Software Engineer at Twilio, discusses how AI assistants can enrich human connection rather than replace it. He presents AI as 'async junior digital employees' that handle mundane tasks, freeing humans for meaningful interactions. The conversation dives into the potential of AI in education, emphasizing personalized learning and the disruption of traditional mentorship. Vinnie also highlights Twilio's partnership with Galileo, aiming to innovate AI integration and empower users. This thought-provoking dialogue blends technology with human experiences.

This week, a panel of experts (Mehmet Murat Ezbiderli, ServiceTitan; Grant Ledford, Indeed; and Vinnie Giarrusso, Twilio) join Atin Sanyal (CTO, Galileo) and Conor Bronsdon (Developer Awareness, Galileo) to explore the challenges and opportunities of deploying GenAI at enterprise scale in a conversation that's a wake-up call for any business leader looking to harness the power of AI. Together, Atin & Conor break down key considerations like performance, cost, and model selection, emphasizing the need for robust evaluation frameworks and a shift in developer mindset. Atin then sits down with our panel of AI engineering experts to discuss their firsthand experiences with enterprise AI, including the trade-offs of building AI systems, the evolving tools and frameworks available, and the impact these technologies are having on their organizations. Chapters: 00:00 Enterprise Scale Deployment 05:17 Cost, Performance, and Model Selection 08:59 Building and Integrating GenAI Systems 15:26 Emerging Enterprise Use Cases 18:12 Predictions for AI in 2025 27:28 Panel Discussion: Deploying AI at Enterprise Scale 31:19 Gen AI Solutions and Challenges 33:12 Building & Deploying Traditional Infrastructure vs GenAI Infrastructure 34:36 How to Assemble Your GenAI Stack 40:39 Today's Best GenAI Use Cases 48:15 Enterprise AI Trends for 2025 50:36 Closing Remarks and Future Outlook Follow: Atin Sanyal: ⁠⁠⁠https://www.linkedin.com/in/atinsanyal/⁠ Mehmet Murat Ezbiderli: https://www.linkedin.com/in/mehmet-murat-ezbiderli-b894a49/ Grant Ledford: https://www.linkedin.com/in/grant-ledford-36b146a5/ Vinnie Giarrusso: https://www.linkedin.com/in/vinniegiarrusso/ Show notes: Watch all of Productionize: https://www.galileo.ai/genai-productionize-2-0

As AI agents and multimodal models become more prevalent, understanding how to evaluate GenAI is no longer optional – it's essential.  Generative AI introduces new complexities in assessment compared to traditional software, and this week on Chain of Thought we’re joined by Chip Huyen (Storyteller, Tép Studio), Vivienne Zhang (Senior Product Manager, Generative AI Software, Nvidia) for a discussion on AI evaluation best practices.  Before we hear from our guests, Vikram Chatterji (CEO, Galileo) and Conor Bronsdon (Developer Awareness, Galileo) give their takes on the complexities of AI evals and how to overcome them through the use of objective criteria in evaluating open-ended tasks, the role of hallucinations in AI models, and the importance of human-in-the-loop systems. Afterwards, Chip and Vivienne sit down with Atin Sanyal (Co-Founder & CTO, Galileo) to explore common evaluation approaches, best practices for building frameworks, and implementation lessons. They also discuss the nuances of evaluating AI coding assistants and agentic systems. Chapters: 00:00 Challenges in Evaluating Generative AI 05:45 Evaluating AI Agents 13:08 Are Hallucinations Bad? 17:12 Human in the Loop Systems 20:49 Panel discussion begins 22:57 Challenges in Evaluating Intelligent Systems 24:37 User Feedback and Iterative Improvement 26:47 Post-Deployment Evaluations and Common Mistakes 28:52 Hallucinations in AI: Definitions and Challenges 34:17 Evaluating AI Coding Assistants 38:15 Agentic Systems: Use Cases and Evaluations 43:00 Trends in AI Models and Hardware 45:42 Future of AI in Enterprises 47:16 Conclusion and Final Thoughts Follow: Vikram Chatterji: https://www.linkedin.com/in/vikram-chatterji/ Atin Sanyal: ⁠⁠https://www.linkedin.com/in/atinsanyal/ Conor Bronsdon: https://www.linkedin.com/in/conorbronsdon/ Chip Huyen: ⁠https://www.linkedin.com/in/chiphuyen/⁠ Vivienne Zhang: ⁠⁠https://www.linkedin.com/in/viviennejiaozhang/ Show notes: Watch all of Productionize 2.0: ⁠https://www.galileo.ai/genai-productionize-2-0⁠

The “ROI of AI” has been marketed as a panacea, a near-magical solution to all business problems. Following that promise, many companies have invested heavily in AI over the past year and are now asking themselves, “What is the return on my AI investment?” This week on Chain of Thought, Galileo’s CEO, Vikram Chatterji joins Conor Bronsdon to discuss AI's value proposition, from the initial hype to the current search for tangible returns, offering insights into how businesses can identify the right AI use cases to maximize their investment. Next, we’re joined by a panel of AI experts to discuss the ROI of Enterprise AI, featuring Alex Klug, Head of Product, Data Science & AI at HP; Sriram Palapudi, Sr. Dir, ML Platform Engineering at ServiceNow; and Jay Subrahmonia, Global MD for AI Research & Products at Accenture. Together, they explore effective implementation strategies, how to measure the returns of AI adoption in the enterprise, and why AI's ROI isn't always just about the bottom line. Chapters: 00:00 Current State of AI Investments 03:59 Challenges and Solutions in AI Implementation 08:30 Identifying and Prioritizing AI Use Cases 10:53 Ensuring Trust and Explainability in AI 15:29 Measuring ROI and Efficiency Gains 21:10 Panel Discussion Begins 21:54 Trust and Risk Management at HP 23:27 Accenture's Approach to Operationalizing AI 26:06 ServiceNow's Trade-offs and Prioritization 31:17 Measuring the success of AI for customers 36:29 Frameworks and Best Practices 40:57 Conclusion and Final Thoughts Follow: Vikram Chatterji: ⁠https://www.linkedin.com/in/vikram-chatterji/ Conor Bronsdon: https://www.linkedin.com/in/conorbronsdon/ Alex Klug: https://www.linkedin.com/in/alex-klug-67ba3655/ Sriram Palapudi: https://www.linkedin.com/in/sriram-palapudi-11294b1/ Jay Subrahmonia: https://www.linkedin.com/in/jayashree-subrahmonia-99963a/ Show notes: Watch all of Productionize 2.0: ⁠⁠https://www.galileo.ai/genai-productionize-2-0⁠⁠

Will 2025 be the year open-source LLMs catch up with their closed-source rivals? Will an established set of best practices for evaluating AI emerge? This week on Chain of Thought, we break out the crystal ball and give our biggest AI predictions for 2025. Listen as Sara Hooker, VP of Research at Cohere and Head of Cohere for AI predicts a trend towards smaller, more optimized AI models; Craig Wiley, Senior Director of Product, Mosaic AI at Databricks, dives into the future of multimodal AI; and Galileo’s CEO, Vikram Chatterji, shares his predictions, including the rise of open-source LLMs. Chapters: 00:00 Introduction 02:01 Vikram's top 3 predictions 06:19 AI and nuclear energy 08:30 Giving power back to the people 13:46 Craig's predictions 20:46 The "era of toolification" 30:38 Sara's predictions 35:07 AI safety Follow: Vikram Chatterji: ⁠⁠https://www.linkedin.com/in/vikram-chatterji/⁠ Yash Sheth: https://www.linkedin.com/in/yash-sheth-/ Conor Bronsdon: ⁠⁠https://www.linkedin.com/in/conorbronsdon/⁠⁠ Sara Hooker: https://www.linkedin.com/in/sararosehooker/ Craig Wiley: https://www.linkedin.com/in/craigwiley/ Show notes: Watch all of Productionize 2.0: ⁠⁠⁠https://www.galileo.ai/genai-productionize-2-0⁠⁠

AI agents have quickly emerged as the next ‘hot thing’ in AI, but what constitutes an AI agent and do they live up to the hype? Join Brian Raymond, founder & CEO at Unstructured.io, Bob van Luijt, co-founder & CEO at Weaviate, and João Moura, founder at crewAI as they discuss the shift to agentic workflows, dissect their architecture, and tackle real-world challenges in agent deployment.  From data management tips to generative feedback loops, this episode is your essential guide to operationalizing agents effectively. Chapters: 00:00 Defining AI Agents 01:16 Components of Agentic Architecture 02:16 Challenges and Solutions in Agent Deployment 03:58 Data Management and Quality Issues 05:23 Operationalizing Agents in Production 06:56 API and Security Considerations 09:04 Multimodal Information and Agentic Workflows 12:42 Future of Agentic Workflows 20:20 Best Practices for Agentic Strategies 25:30 Generative Feedback Loops 28:29 Agentic Evaluations Follow: Yash Sheth: https://www.linkedin.com/in/yash-sheth- Bob van Luijt: https://nl.linkedin.com/in/bobvanluijt Brian Raymond: https://www.linkedin.com/in/brian-s-raymond ⁠⁠⁠⁠⁠⁠⁠João Moura: https://br.linkedin.com/in/joaomdmoura Show notes: ⁠⁠⁠Watch all of Productionize 2.0: https://www.galileo.ai/genai-productionize-2-0

From ChatGPT's search engine to Google's AI-powered code generation, artificial intelligence is transforming how we build and deploy technology.  In this inaugural episode of Chain of Thought, the co-founders of Galileo explore the state of AI, from open-source models to establishing trust in enterprise applications. Plus, tune in for a segment on the impact of the Presidential election on AI regulation. The episode culminates with an interview of May Habib, CEO of Writer, who shares practical insights on implementing generative AI at scale. Chapters: 00:00 Introduction to Chain of Thought Podcast 01:27 Big News in AI: ChatGPT and Anthropic 06:34 Open Source vs Proprietary AI 12:17 The Importance of Trust in AI 20:12 Challenges in AI Development and Deployment 22:07 The Role of Human Input in AI Development 28:45 The Future of AI Regulation 34:41 Interview with May Habib co-founder & CEO at Writer 40:01 What’s Writer’s secret sauce? 43:31 Challenges in productionizing GenAI 48:08 Conclusion Follow: Vikram Chatterji: ⁠⁠⁠https://www.linkedin.com/in/vikram-chatterji/⁠⁠ Atin Sanyal: ⁠https://www.linkedin.com/in/atinsanyal/ Yash Sheth: ⁠https://www.linkedin.com/in/yash-sheth-/⁠ Conor Bronsdon: ⁠⁠⁠https://www.linkedin.com/in/conorbronsdon/⁠⁠⁠ May Habib: https://www.linkedin.com/in/may-habib/ Show notes: Watch all of Productionize 2.0: ⁠⁠⁠⁠https://www.galileo.ai/genai-productionize-2-0⁠⁠