Chain of Thought

Charity Majors, co-founder and CTO of Honeycomb, shares her sharp insights on the challenges AI brings to engineering teams. She argues that while generative AI is a hot topic, it won't build effective teams or replace the essential roles of junior engineers. The conversation dives into hiring practices, emphasizing the importance of potential over experience. Charity also highlights the complexities of system ownership and the risks of cognitive decay from over-relying on AI, stressing the need for deep understanding among engineers.

In this engaging talk, Maryam Ashoori, Head of Product for watsonx AI at IBM, shares her expertise from over 15 years in enterprise AI. She discusses how watsonx simplifies the AI stack and automates processes, enabling businesses to scale AI operations cost-effectively. Maryam highlights the balance of using open-source and commercial models while addressing the challenges of implementing AI agents, emphasizing the importance of data management and governance in regulated industries.

What if everyone in your organization had equal information at all times? Would meetings even exist? This week, we dive into the concept of information symmetry with Manoj Agarwal, co-founder and president of DevRev. Manoj, along with hosts Conor Bronsdon and Yash Sheth, explores how DevRev is connecting data, personalizing schemas, and automating complex tasks, offering a glimpse into the next generation of AI-driven workflows. This is revolutionizing enterprise data and decision-making by breaking down the silos that create information asymmetry.Learn how AI is reshaping business outcomes and collaboration, moving us closer to a world where everyone has the information they need.Chapters:00:00 Welcome to Chain of Thought00:57 Information Symmetry in Enterprises02:03 Challenges of Decision Making03:41 Recency Bias and Product Management04:58 Data Silos and Information Waste05:23 Structured vs. Unstructured Data06:04 Collaboration and Data Retrieval Issues08:17 DevRev's Approach to AI and Data Integration09:23 Building a Business-Centric Knowledge Graph10:00 Conversational AI and Automation12:57 Agentic Interactions and Skills Programming20:05 Multi-Agent Systems and Future Vision21:25 Challenges in Multi-Agent Communication25:10 Data Cleanliness and Governance28:14 Trust and Reliability in AI Systems36:58 Conclusion and Future OutlookFollow the hostsFollow⁠⁠⁠⁠⁠⁠⁠⁠ Atin⁠⁠⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠⁠⁠⁠ Conor⁠⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠⁠ Vikram⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠ ⁠⁠⁠⁠Yash⁠⁠⁠⁠⁠⁠⁠⁠Follow Today's Guest(s)devrev.aiDevRev UniversityLinkedIn Manoj AgarwalCheck out Galileo⁠⁠⁠⁠⁠⁠⁠Try Galileo⁠⁠

Is the agentic AI bubble about to burst? Kelly Vaughn, Director of Engineering at Spot AI, questions whether the agent craze is overpromising potential and leading startups down a path of unsustainable expectations.Never one to shy away from a hot take, Kelly joins host Conor Bronsdon for a pragmatic look at AI, discussing the differences between building AI-enabled and traditional software, why replacing humans with AI teams will backfire (looking at you customer service), and the proliferation of AI tools.Kelly also shares insights on constructing AI teams, navigating data governance, and building user trust while avoiding common startup pitfalls. Chapters:00:00 Introduction and Guest Welcome01:13 Is Agentic AI a Bubble?02:40 Startup Challenges and Market Noise11:02 Building AI Products vs. Traditional Software17:31 Ethical Implications and Governance19:48 Constructing AI-Enabled Teams22:07 AI Tooling and Productivity26:00 Questioning Productivity Claims32:28 Conclusion and Final ThoughtsFollow the hostsFollow⁠⁠⁠⁠⁠⁠⁠ Atin⁠⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠⁠⁠ Conor⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠ Vikram⁠⁠⁠⁠⁠Follow⁠⁠⁠ ⁠⁠⁠⁠Yash⁠⁠⁠⁠⁠⁠⁠Follow Today's Guest(s)Kelly’s Newsletter The Modern LeaderLinkedIn Kelly VaughnCheck out Galileo⁠⁠⁠⁠⁠⁠Try Galileo⁠⁠

Imagine cutting your legacy code modernization timeline from years to months. It’s no longer science fiction and this week’s guest is here to tell us how. Rachelle Palmer, Director of Product Management at MongoDB, joins hosts Conor Bronsdon and Atindriyo Sanyal, for a discussion on the groundbreaking ways AI is modernizing legacy applications. At MongoDB, Rachelle's forward-deployed AI engineering team is tackling the challenge of transforming complex, outdated codebases, freeing developers from technical debt. She details how LLMs are automating tasks like improving documentation, test generation, and even business logic conversion, dramatically reducing modernization timelines from years to months. What once demanded teams of dozens can now be achieved with a small, highly efficient team.Chapters:00:00 Introduction and Host Welcome00:58 Challenges in Modernizing Legacy Applications02:52 Real-World Examples of Code Modernization04:00 The Role of LLMs in Code Modernization08:01 Measuring Success in AI-Powered Modernization12:28 The Future of AI in Engineering16:17 Evaluating Modernization Success21:12 Returning to Your Startup Roots29:07 Forward Deployed AI Engineers35:36 Importance of Academic Research in AI42:10 Conclusion and FarewellFollow the hostsFollow⁠⁠⁠⁠⁠⁠ Atin⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠⁠ Conor⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠ Vikram⁠⁠⁠⁠Follow⁠⁠ ⁠⁠⁠⁠Yash⁠⁠⁠⁠⁠⁠Follow Today's Guest(s)⁠Rachelle PalmerMongoDBApplication Modernization FactoryCheck out Galileo⁠⁠⁠⁠⁠Try Galileo⁠⁠

This week, we're sharing a special episode courtesy of 'Dev Interrupted.' Our co-host, Galileo CEO Vikram Chatterji, recently joined theDev Interrupted team for an engaging discussion on AI strategy. We were so impressed by the conversation that we wanted to share it with our audience, and they were kind enough to let us. We hope you enjoy it!From Dev Interrupted:"Vikram Chatterji joins Dev Interrupted’s Andrew Zigler to discuss how engineering leaders can future-proof their AI strategy and navigate an emerging dilemma: the pressure to adopt AI to stay competitive, while justifying AI spending and avoiding risky investments.To accomplish this, Vikram emphasizes the importance of establishing clear evaluation frameworks, prioritizing AI use cases based on business needs and understanding your company's unique cultural context when deploying AI."Chapters:00:00 Introduction and Special Announcement01:14 Welcome to Dev Interrupted01:42 Challenges in AI Adoption03:16 Balancing Business Needs and AI06:15 Crawl, Walk, Run Approach10:52 Building Trust and Prototyping13:07 AI Agents as Smart Routers13:50 Galileo's Role in AI Development16:25 Evaluating AI Systems25:36 Skills for Engineering Leaders27:35 Conclusion Follow the hostsFollow⁠⁠⁠⁠⁠ Atin⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠ Conor⁠⁠⁠⁠Follow⁠⁠⁠ Vikram⁠⁠⁠Follow⁠ ⁠⁠⁠⁠Yash⁠⁠⁠⁠⁠Follow Dev InterruptedPodcastSubstackLinkedInFollow Dev Interrupted HostsAndrewBenCheck out Galileo⁠⁠⁠⁠Try Galileo⁠⁠

Logan Kilpatrick, Senior Product Manager at Google DeepMind, shares fascinating insights into the making of Gemini 2.0. He discusses Gemini's strength as a premier AI model, showcasing its multimodal capabilities and unique function calling approach. Logan highlights the role of Google's hardware in enhancing performance and long-context capabilities. The conversation also touches on the potential of vision-first AI agents and how Gemini is set to revolutionize developer experiences by integrating seamlessly into existing ecosystems.

Hosts dive into the significant impact of DeepSeek's latest R1 model on the open-source AI landscape. They discuss export controls and their mixed effects on global innovation, hinting at a shift towards "Agents as a Service." The necessity for robust evaluation frameworks for increasingly complex agentic systems takes center stage, revealing challenges in measuring performance. The launch of customizable evaluation tools is highlighted as a game-changer for developers, promising a safer trajectory for AI agents.

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