JetBrains Research Podcast

Could human-made ideas become a luxury in a world of AI-generated content? Join machine learning researcher and educator Anastasia Yanina, Igor Slinko, and Ilya Zakharov as they explore the future of ML research. Drawing on Anastasia's experience at Samsung AI Center and Meta Reality Labs, they discuss what foundation models leave for researchers to invent, AI-written papers and peer review, and the value of human creativity. The conversation also covers PhDs, teaching, first jobs, AI coding agents, and whether human code review will survive.Chapters00:00:00 Teaser00:00:27 Welcome and introductions00:01:25 From art and architecture to machine learning00:08:13 Switching between computer vision and LLMs00:10:35 Building 3D avatars at Meta Reality Labs00:14:01 What's left for ML researchers to invent?00:19:35 When AI writes and reviews research papers00:22:39 Scientific publishing and the peer review crisis00:30:25 Can AI agents reproduce research papers?00:36:34 Bringing research into industry00:40:06 Will human-made ideas become a luxury?00:43:11 Is a PhD still worth it?00:48:24 Teaching and assessment in the age of AI00:55:01 Finding your first job in ML00:59:39 Should students still learn to code?01:02:36 Writing code with AI agents01:06:30 Reviewing AI-generated code01:09:03 The future of pull requests01:16:45 Changing your mind as a researcher01:20:35 Advice for a new ML researcherMentions & Links:- Anastasia Yanina — LinkedIn: https://www.linkedin.com/in/anastasia-ianina/-Anastasia Yanina — profile (in Russian): https://www.setters.media/setters-a-list-2025/yanina- Yandex Machine Learning Handbook (in Russian): https://education.yandex.ru/handbook/ml- Hugging Face — What We Learned by Reproducing 2,200 Papers from ICML: https://huggingface.co/blog/icml-2026-open-reproductions- ICML — On Violations of LLM Review Policies: https://blog.icml.cc/2026/03/18/on-violations-of-llm-review-policies/- Harbour.Space University: https://harbour.space/

In our fifth episode, we chat with Dr. Cat Hicks, Founder and Chief Scientist of Catharsis Consulting. She is a psychologist and author of The Psychology of Software Teams, published July 2026. Episode links: Dr. Hicks' LinkedIn: https://www.linkedin.com/in/drcathicks/ Catharsis Consulting: https://catharsisinsight.com/ "No Silver Bullets" paper: https://arxiv.org/pdf/2503.05040 Our previous episodes can be found here: https://jb.gg/rsrch-pdcst Find out more about JetBrains Research here: https://jb.gg/rsrch Chapters: 00:00 Intro 00:46 Meet Dr. Cat Hicks, psychologist for humans in technology 04:15 Why write a book about software teams? 08:49 Building a "third place" between academia and industry 17:10 Why publish research when technology moves so quickly? 27:07 Why study teams instead of individual developers? 31:13 Team culture, developer identity, and AI skill threat 37:55 "More bands, fewer rock stars": The lone-genius myth 43:37 Code-review anxiety and code review as a learning practice 47:27 How AI creates uncertainty about belonging and expertise 53:03 Overproduction pressure: When AI becomes a productivity hammer 55:47 Context engineering and scaling human mental models 58:40 Culture is infrastructure—and invisible work matters 1:01:36 Being a public expert when the answers keep changing 1:07:02 What should we research about AI next? 1:11:14 Take-home message: Your actions matter

Join us as Thomas Petricek, a program and language researcher, discusses the diverse "cultures of programming," highlighting how a humanistic approach can foster better understanding and interaction with software, moving beyond mere automation. Our previous episodes can be found here: https://jb.gg/rsrch-pdcst Find out more about JetBrains Research here: https://jb.gg/rsrch Chapters 00:00:00 Programming Cultures Overview 00:01:41 Thomas's Background 00:03:50 Current Research Focus 00:06:05 Code Poetry Explained 00:09:00 Critical Software Architecture 00:11:51 Cultures of Programming 00:17:27 Mathematical Culture 00:22:39 Hacker Culture 00:25:32 Tacit Hacker Knowledge 00:30:00 Tacit Knowledge Undervalued 00:38:43 Managerial Culture 00:40:20 Engineering Culture 00:44:48 Spec-Driven Development 00:51:48 Humanistic Culture 00:54:40 Programming Field Pluralism 00:56:48 Personal Cultural Sympathies 01:01:21 AI and Future Cultures 01:04:14 Lessons from History 01:06:17 Making Programming Easy 01:09:09 Future Research Directions 01:11:43 Take-Home Message 01:13:20 Advice for JetBrains Mentions & Links: Tomas Petricek https://tomasp.net/ "Cultures of Programming" book https://www.cambridge.org/core/books/cultures-of-programming/075A2D1DE611EE47807A683147B21691 Psychology of Programming Interest Group (PPIG) https://www.ppig.org/ Code Poetry https://en.wikipedia.org/wiki/Code_poetry Whitespace Programming Language https://en.wikipedia.org/wiki/Whitespace_(programming_language) CompCert https://compcert.org/compcert-C.html -Smalltalk https://en.wikipedia.org/wiki/Smalltalk On the Limits of Making Programming Easy https://tomasp.net/academic/papers/limits/

In our newest episode, we chat with Alexander Kulikov, head of the Computer Science and Artificial Intelligence B.Sc. program at Neapolis University Pafos. Episode links: https://www.linkedin.com/in/alexanderskulikov/ https://www.coursera.org/specializations/data-structures-algorithms https://cogniterra.org/course/697/promo https://compeau.cbd.cmu.edu/online-education-projects/programming-for-lovers/ https://lean-lang.org/ https://www.manim.community/ Our previous episodes can be found here: https://jb.gg/rsrch-pdcst Find out more about JetBrains Research here: https://jb.gg/rsrch Chapters: 00:00 – Introduction and STACS Conference02:00 – AI in Theoretical Computer Science 04:30 – Bachelor Program and Evolving Curriculums 08:30 – Boolean Circuit Synthesis Competitions 12:00 – The "Game of Life" and Modern AI Iterations 16:45 – LLMs Winning IMO Medals 22:00 – Formal Verification and the Lean Language 25:30 – The Chess Analogy: AI Replacing Mathematicians 33:00 – AI Coding Agents and Don Knuth's $2.56 Check 38:30 – Distributed Algorithms and Complexity Theory 41:00 – Large-Scale Online Education and Adding JavaScript 48:45 – The Importance of Algorithmic Thinking 56:00 – Real-World Application: The Google Maps Polygon Problem 1:01:30 – Bioinformatics, SPAdes, and Fundamental vs. Applied Research 1:10:00 – Sabbatical Dreams: P vs. NP and Linear Time Limits 1:18:00 – Creating Mathematical Animations with Python 1:21:30 – AI Interpolation vs. Extrapolation and Joke Generation 1:25:00 – "Birds vs. Frogs": Research Styles in the AI Era 1:30:15 – Surprises, Rapid Changes, and the Future of AI 1:33:30 – Advice for New PhD Students: Follow Your Passion 1:36:30 – Outro and Final Thoughts

In our second episode, we chat with Ibragim Badertdinov from Nebius about SWE-rebench, coding agents, and his path from dentistry and AI. Our first episode can be found hereEpisode links: SWE-rebench: https://swe-rebench.com/ConTree: https://contree.dev/ Ibragim: https://x.com/ibragim_bad Also mentioned: https://huggingface.co/datasets/nebius/SWE-bench-extra https://scale.com/leaderboard/swe_bench_pro_public https://swe-bench-live.github.io/ Find out more about JetBrains Research: https://lp.jetbrains.com/research/software-engineering/ Chapters: 00:00:00 Teaser & Introduction 00:02:41 Ibrahim's Non-Traditional Background: From Dentistry to Tech 00:10:45 The "School 42" Bootcamp Experience 00:13:00 Getting into Machine Learning & Kaggle 00:17:20 The First Internship & Learning from a Great Mentor 00:20:10 Contrasting the Worlds of Medicine and Tech 00:26:56 What Are Coding Agents? 00:33:40 Explaining SWE-bench: How Coding Tasks Are Evaluated 00:37:15 RLVR (Reinforcement Learning with Verifiable Rewards) 00:43:10 The Creation of SWE-Rebench 00:50:00 The Main Challenges with Task Quality and Scale 00:55:00 What's New in SWE-Rebench V2 (and Kotlin support) 00:58:42 Will AI Change Code Review? 01:02:00 contree.dev: A New Checkpointing & Forking Tool for Agents 01:09:35 The Open-Source Community's Reaction to SWE-Rebench 01:15:20 SWE-Bench Pro vs. SWE-Rebench 01:18:20 Why Nebius Invests in Open-Source Research 01:21:00 Predictions for the Future of AI and Programming 01:26:00 Final Advice for Career Switchers

We discuss the legacy of OpenCV, the future of Computer Vision, how AI can transform professional sports through biomechanics, and why real-world technology adoption remains so slow. Episode links OpenCV: https://opencv.org/ FitWise AI: https://www.thefitwise.com/ Anna Kogan: linkedin: / anna-kogan-44b24673