The last technical interview you'll ever take

The last technical interview you'll ever take

Since the day a hiring manager first wheeled a whiteboard into a conference room, software engineers have dreaded the technical interview, which can be an all-day process (or multi-day homework assignment). If you’re interviewing for multiple roles, you can expect to write out a bubble sort in pseudocode for each one. These technical interviews do no favors for hiring companies, either, because the investment needed from both parties limits the number of candidates a company can consider. In this age of data-driven decisions, perhaps there’s a way that AI and ML can help candidates and companies find each other.

On this episode of the podcast, sponsored by Turing AI, we chat with Chief Revenue Officer Prakash Gupta about building a better hiring process with AI. Turing helps companies scale their engineering programs quickly with remote developers from around the world. We talk about how to vet a profession without standard markers, the benefits of soft skills, and how AI-assisted hiring helps everyone involved.

While companies have been outsourcing development for years, COVID made the software industry almost entirely remote. Suddenly, every company has the ability to hire the best developers regardless of location. And good developers can find work at companies of all sizes without packing up and settling in Silicon Valley.

But when any company could conceivably interview any candidate, how do you vet candidates at scale? There is no standardized board certification for software engineers, after all. Every interviewer has to vet the candidates themselves, and that’s where human biases come in.

On one side, you have Fortune 500 companies developing complex systems and undergoing digital transformation projects, plus startups looking to scale their engineering organizations as their product finds market fit. On the other, you have a new generation of engineers trained on bootcamps and online resources who may not have opportunities where they live. That’s where Turing comes in, matching 1.7 million engineers from over 140 countries with jobs at hundreds of companies.

Turing strives to mitigate bias by collecting hundreds of signals about candidates over a four- to six-hour process. This process covers projects candidates have worked on, technology aptitude, and soft skills through 30-minute tests, candidates’ online presence in places like GitHub and Stack Overflow, and qualitative assessments refined over two years of feedback loops.

A process that once consisted of ten interviews can now drop to two or three at the most. Some Turing customers have eliminated interviews altogether, relying on Turing’s AI-powered solutions to surface and evaluate the best candidates. To see how Turing can streamline your interview process, either as a candidate or a company, check out turing.com today.

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Episoder(891)

What leaders need to know from the 2025 Stack Overflow Developer Survey

What leaders need to know from the 2025 Stack Overflow Developer Survey

In this episode of Leaders of Code, Eira May, B2B Editor at Stack Overflow, and Natalie Rotnov, Senior Product Marketing Manager for the Enterprise Product Suite at Stack Overflow, unpack the key takeaways from the 2025 Developer Survey for tech and business leaders. The discussion focuses on the evolving developer relationship with AI, the continued struggle with tool sprawl, and actionable recommendations for leaders looking to deliver value and improve developer experience.The discussion covers critical findings for tech leaders:The decline in developer trust in AI is linked to two main frustrations: solutions that are "almost right, but not quite" and the time wasted debugging AI-generated code.Human connection and community validation remain vital: 80% of developers still visit Stack Overflow regularly, and the number of "advanced questions" on the public platform has doubled since 2023, underscoring AI’s limitations when it comes to complex, context-dependent questions.Tool sprawl continues, as most developers use 6–10 tools, suggesting that AI tends to complicate rather than simplify workflows.Notes:Explore key insights from the 2025 Stack Overflow Developer Survey, consolidated into an executive-ready summary. Connect with Natalie Rotnov on LinkedIn.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

23 Okt 31min

Open source is giving you choices with your agent systems

Open source is giving you choices with your agent systems

Ryan welcomes John Dickerson, CEO of Mozilla.ai, to talk about the evolving landscape of AI agents, the role of open source in keeping the tech ecosystem healthy, the challenges OS communities have faced with the rise of AI, and the implications of data privacy and user choice in the age of multi-agent AI systems. Episode notes:Mozilla.ai is building the agent platform that helps organizations safely automate real work with AI agents. Connect with John on Linkedin or email him at john@mozilla.ai. Congrats to Populist badge winner Philipp Merkle, who won it for their answer to How to set the -Xmx when start running a jar file?.TRANSCRIPTSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

21 Okt 26min

Why rent a cloud when you can build one?

Why rent a cloud when you can build one?

Andrei Kvapil, founder of Ænix and core developer of Cozystack, joins Ryan to dive into what it takes to build a cloud from scratch, the intricacies of Kubernetes and virtualization, and how open-source has made digital sovereignty possible. Episode notes:Cozystack is a Kubernetes-based framework for building a private cloud environment.Connect with Andrei on Linkedin. Today’s shoutout goes to user Adam for winning a Populist badge for their answer to Regex replace text but exclude when text is between specific tag. TRANSCRIPTSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

17 Okt 29min

AI agents for your digital chores

AI agents for your digital chores

Ryan welcomes Dhruv Batra, co-founder and chief scientist at Yutori, to explore the future of AI agents, how AI usage is changing the way people interact with advertisements and the web as a whole, and the challenges that proactive AI agents may face when being integrated into workflows and personal internet use. Episode notes:Yutori is building AI agents that can reliably handle everyday digital tasks on your behalf on the web.Connect with Dhruv via his website. Congrats to the winner of today’s Populist badge, user Don Kirkby, who earned it with their answer to Find all references to an object in python.TRANSCRIPTSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

14 Okt 34min

Vite is like the United Nations of JavaScript

Vite is like the United Nations of JavaScript

Ryan welcomes back Evan You, the creator of Vite and Vue.js, to discuss the evolution of build tools in web development, the unique features of Vite from its plugins to its hot module capabilities, and the future of Vite, including its integration with Rust. Plus, they touch on Vite’s new documentary and the power of open-source communities.Episode notes:Vite is a frontend build tool powering the next generation of web applications. Check out all of the work Evan is doing at his company VoidZero. For more on the origins of Vite, watch the newly-released Cult.repo’s documentary. If you’d rather hear Evan talk about Vue.js, listen to the podcast we published with him earlier this summer. Today’s shoutout goes to user dbush for winning a Populist badge on their answer to How does printing a union itself and not its member work in C?.TRANSCRIPTSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

10 Okt 27min

Context is king for secure, AI-generated code

Context is king for secure, AI-generated code

Ryan sits down with Dimitri Stiliadis, CTO and co-founder of Endor Labs, to talk about how AppSec is evolving to address AI’s use cases. They discuss the implications of AI-generated code on security practices, the importance of human oversight in managing vulnerabilities, and how organizations should be balancing security and efficiency with AI. Episode notes:Endor Labs is AppSec for the software development revolution, helping you pinpoint critical risks whether your code is written by a human or AI. Connect with Dimitri on LinkedIn.Today’s shoutout is for user skovorodkin, whose answer for Elegant Python code for Integer Partitioning  was so good, it outscored the accepted answer. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

7 Okt 28min

One is not the loneliest number for API calls

One is not the loneliest number for API calls

Gil Feig, co-founder and CTO of Merge, joins the show to explore Merge’s approach for reducing third-party APIs to a single call, the complexities of and need for data normalization, and the role that AI and MCP plays in the future of API functionality. Episode notes: Merge connects you to any third-party system for fast, secure integrations for your products and agents.Connect with Gil on LinkedIn and X. Shoutout to user Abhijit for winning a Lifeboat badge on their answer for Complex numbers in python.TRANSCRIPTSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

3 Okt 26min

Building AI-ready teams: Why documentation and culture matter more than tools

Building AI-ready teams: Why documentation and culture matter more than tools

In the second part of this two-part Leaders of Code episode, Peter O'Connor, Director of Platform Engineering, and Ryan J. Salva, Senior Director of Product at Google Developer Experiences, dive beyond AI hype to explore the shifts reshaping how engineering teams operate and scale. From the critical role of documentation quality in AI workflows to the cultural transformations needed for successful adoption, Peter and Ryan discuss the deeper implications of integrating AI into modern software development practices.The discussion also:Explores how poor documentation creates problems as AI systems learn and repeat mistakes, making high-quality documentation essential for successful AI integrations.Covers how consistent tools and processes become more important when using AI, and why leaders should prioritize helping teams learn and experiment with AI tools instead of just measuring productivity.Offers practical advice for leaders on how to create environments where developers can learn and build confidence with AI tools.Notes:Listen to Part 1 of the conversation here.Connect with Peter O’Connor and Ryan J Salva.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

2 Okt 20min

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