Using AI to Modernize Your Legacy Applications | MongoDB’s Rachelle Palmer

03/12/25 • 43 min

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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At MongoDB, Rachelle's forward-deployed AI engineering team is tackling the challenge of transforming complex, outdated codebases, freeing developers from technical debt.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 Palmer MongoDB Application Modernization Factory

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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.

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

Follow the hosts

Follow⁠⁠⁠⁠⁠⁠ Atin⁠⁠⁠⁠⁠⁠

Follow⁠⁠⁠⁠⁠⁠ Conor⁠⁠⁠⁠⁠

Follow⁠⁠⁠⁠ Vikram⁠⁠⁠⁠

Follow⁠⁠ ⁠⁠⁠⁠Yash⁠⁠⁠⁠⁠⁠

Follow Today's Guest(s)

⁠Rachelle Palmer MongoDB Application Modernization Factory

Check out Galileo

⁠⁠⁠⁠⁠Try Galileo⁠⁠

Previous Episode

Can Your AI Strategy Be Future-Proof? | Galileo’s Vikram Chatterji

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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Follow⁠⁠⁠⁠⁠ Conor⁠⁠⁠⁠

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Next Episode

Is There an Agent Bubble? | Spot AI’s Kelly Vaughn

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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