Chain of Thought

Olga Beregovaya, VP of AI at Smartling, dives into the captivating world of AI and translation. She discusses how AI has evolved from rule-based systems to sophisticated models that tackle language barriers. Key challenges like English-centric biases and the unpredictability of AI outputs are explored. Olga highlights opportunities in specialized language models and innovative workflows that enhance translator productivity. The potential for multilingual multimodality raises exciting possibilities for the future of global communication and more nuanced translations.

Rodrigo Coutinho, Co-founder and AI Product Manager at OutSystems, dives into the world of AI-driven application development. He discusses the groundbreaking potential of transforming requirements into full enterprise apps within minutes. Rodrigo highlights challenges in managing AI-generated code and the evolution of a developer's role from focusing on syntax to strategy. The use of low-code platforms like OutSystems Mentor empowers developers while maintaining the necessity for human creativity and effective validation, paving the way for a faster and innovative development cycle.

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.