Chain of Thought
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Top 10 Chain of Thought Episodes
Goodpods has curated a list of the 10 best Chain of Thought episodes, ranked by the number of listens and likes each episode have garnered from our listeners. If you are listening to Chain of Thought for the first time, there's no better place to start than with one of these standout episodes. If you are a fan of the show, vote for your favorite Chain of Thought episode by adding your comments to the episode page.
03/12/25 • 43 min
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At MongoDB, Rachelle's forward-deployed AI engineering team is tackling the challenge of transforming complex, outdated codebases, freeing developers from technical debt.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 Welcome
00:58 Challenges in Modernizing Legacy Applications
02:52 Real-World Examples of Code Modernization
04:00 The Role of LLMs in Code Modernization
08:01 Measuring Success in AI-Powered Modernization
12:28 The Future of AI in Engineering
16:17 Evaluating Modernization Success
21:12 Returning to Your Startup Roots
29:07 Forward Deployed AI Engineers
35:36 Importance of Academic Research in AI
42:10 Conclusion and Farewell
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Rachelle PalmerMongoDBApplication Modernization Factory
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03/05/25 • 29 min
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 Announcement
01:14 Welcome to Dev Interrupted
01:42 Challenges in AI Adoption
03:16 Balancing Business Needs and AI
06:15 Crawl, Walk, Run Approach
10:52 Building Trust and Prototyping
13:07 AI Agents as Smart Routers
13:50 Galileo's Role in AI Development
16:25 Evaluating AI Systems
25:36 Skills for Engineering Leaders
27:35 Conclusion
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Do I Need Agents? | Gartner’s Haritha Khandabattu
Chain of Thought
02/19/25 • 45 min
If you’re an engineering leader or CIO and haven’t already implemented agents, you’re probably being asked to. But the question you should ask yourself isn’t simply why; it’s where.
This week, Haritha Khandabattu, Senior Director Analyst for AI at Gartner, joins us to cut through the hype surrounding AI agents. She provides real-world examples of successful implementations and reveals how to avoid common pitfalls. Listen now to discover the crucial questions leaders should ask before taking the plunge, including assessing your organization's needs and identifying the right use cases.
Chapters:
00:00 The Hype and Reality of AI Agents
05:33 Challenges and Ethical Considerations of AI Agents
14:18 Evaluating AI Agents: Benchmarks and Misconceptions
22:21 Building vs. Buying AI Solutions
26:43 Collaboration Between Data and Software Engineering Teams
33:48 AI's Impact on Software Development
37:37 The Zone of Deep Productivity
40:44 Practical Takeaways for Implementing AI Agents
44:15 Conclusion and Farewell
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LinkedIn: https://www.linkedin.com/in/harithakhandabattu/
Show Notes
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04/23/25 • 40 min
Are we on the verge of removing all language barriers with AI?
Olga Beregovaya, VP of AI at Smartling, joins host Conor Bronsdon to tackle this question, discussing the evolution from rule-based NLP to today's powerful LLMs. Together, they confront the persistent challenges that stand in the way, like the English-centric nature of AI, domain-specific inaccuracies, and the unpredictability of model hallucinations. Olga unpacks the difficulties faced when striving for accurate, nuanced translation across all languages, especially under-resourced ones.
Beyond these hurdles, the conversation explores the cutting-edge opportunities and technical innovations driving progress, including RAG, the rise of purpose-built models, agentic AI workflows, and the potential of multilingual multimodality. Olga shares insights into boosting translator productivity, achieving more predictable quality, and the path toward human parity in translation, examining how technology and human expertise will shape the future of global communication.
Chapters
00:00 Introduction and Guest Welcome
01:14 Evolution of NLP: From Rule-Based to Machine Learning
02:40 Challenges in AI Translation
04:21 Biases in Language Models
05:28 Inference Time and Latency
05:44 English-Centric AI Models
08:53 Opportunities in AI Translation
09:14 Industries Benefiting from Language AI
10:36 Human-in-the-Loop Translation
12:06 Architectural Innovations in Language AI
16:20 Success with RAG Architectures
17:58 Multilingual Vectorization
19:54 Agentic AI in Translation
24:35 Data Sets and Data Privacy
28:30 Using Smaller, Purpose-Built Models
32:10 Future of AI in Translation
36:37 Conclusion and Farewell
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LinkedIn Olga Beregovaya
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Welcome to Chain of Thought
Chain of Thought
10/29/24 • 1 min
We are living in the age of AI. It's transforming everything around us, from the way we work and communicate, to how we solve global challenges.
But for many, AI still feels like a black box.
Introducing Chain of Thought, the podcast for software engineers and leaders that demystifies artificial intelligence.
We’ll be joined by AI innovators, tech founders, and expert researchers such as Cohere’s Sara Hooker.
Join us as we unravel actionable strategies and practical techniques for building effective GenerativeAI applications.
Discover how AI is being productionized at companies like HP, Twilio and Databricks, as each week we’ll discuss the rapid-evolving AI industry, exploring its potential to create a more productive world, and build a better, trustworthy future.
Subscribe now to Chain of Thought wherever you get your podcasts.
Chain of Thought. Trace the logic of innovation.
Is There an Agent Bubble? | Spot AI’s Kelly Vaughn
Chain of Thought
03/19/25 • 35 min
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 Welcome
01:13 Is Agentic AI a Bubble?
02:40 Startup Challenges and Market Noise
11:02 Building AI Products vs. Traditional Software
17:31 Ethical Implications and Governance
19:48 Constructing AI-Enabled Teams
22:07 AI Tooling and Productivity
26:00 Questioning Productivity Claims
32:28 Conclusion and Final Thoughts
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Kelly’s Newsletter The Modern Leader
LinkedIn Kelly Vaughn
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The Real ROI of Enterprise AI | HP, ServiceNow & Accenture
Chain of Thought
11/27/24 • 41 min
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
04/30/25 • 38 min
Agentic AI exploded in 2025, but how do businesses move beyond prototypes to deploy reliable, valuable agents at scale?
Join host Conor Bronsdon and Lyzr AI CEO Siva Surendira as they discuss the complexities of building and managing AI agents for enterprises. Siva shares his journey creating Lyzr, focusing on making powerful agent frameworks accessible and trustworthy for enterprise developers. They discuss the critical hurdles businesses face, including productionization challenges, ensuring responsible AI, and bridging the gap between rapid innovation and the stringent requirements of regulated industries.
Listen as Siva explains Lyzr's approach to embedding safety guardrails natively and learn about the nuances of multi-agent orchestration, including managerial, DAG, and hybrid flows. Siva also offers insights into the limitations of "vibe coding" for enterprise use cases and stresses the crucial role of robust evaluation (evals) and choosing the right models—from local open-source options to frontier LLMs. Explore the bottlenecks hindering adoption, like custom application integration and data readiness, and learn why Siva believes the biggest opportunity for agent companies may not lie in replacing SaaS platforms but rather in automating the mundane work currently performed by humans.
Chapters
00:22 Introduction and Guest Welcome
00:52 Enterprise Agent Framework
02:48 Building Enterprise-Friendly AI Frameworks
04:56 Enterprise Concerns with Vibe Coding
09:23 Safe and Responsible AI Implementation
11:05 Multi-Agent Orchestration
14:13 Challenges in Multi-Agent Systems
14:22 Enterprise Integration Bottlenecks
17:37 The Role of Low-Code and No-Code Solutions
19:55 Inter-Agent Communication Standards
21:49 Future of AI Agents in Enterprises
29:37 Evaluating AI Agents
36:34 Conclusion and Final Thoughts
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Website: lyzr.ai
LinkedIn: Siva Surendira
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AI in 2025: Agents & The Rise of Evaluation Driven Development
Chain of Thought
01/15/25 • 33 min
"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:
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GenAI Predictions for 2025 | Databricks & Cohere
Chain of Thought
11/20/24 • 40 min
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
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FAQ
How many episodes does Chain of Thought have?
Chain of Thought currently has 23 episodes available.
What topics does Chain of Thought cover?
The podcast is about Podcasts and Technology.
What is the most popular episode on Chain of Thought?
The episode title 'Do I Need Agents? | Gartner’s Haritha Khandabattu' is the most popular.
What is the average episode length on Chain of Thought?
The average episode length on Chain of Thought is 38 minutes.
How often are episodes of Chain of Thought released?
Episodes of Chain of Thought are typically released every 7 days.
When was the first episode of Chain of Thought?
The first episode of Chain of Thought was released on Oct 29, 2024.
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