Dr Cat Hicks is a psychological scientist and the founder of Catharsis, a human-centred research consultancy that works with engineering organisations. After self-funding her first open-access study into developer motivation, she was recruited to lead the Developer Success Lab at Pluralsight — a three-year programme that generated large-scale empirical research across hundreds of companies and more than 11,000 developers. Her book, The Psychology of Software Teams, brings that evidence to bear on the question her industry keeps asking: why do smart people in smart organisations so often struggle to work well together? We talk about the hidden costs of treating developers as interchangeable units, what large-scale cycle time data reveals about individual performance, and how product managers can build the conditions for teams to actually thrive. Key takeaways The "brains and jars" model — treating developers as interchangeable, isolated computing units — does not just feel demeaning; it actively undermines the collaborative, social work that makes software teams effective, and is linked to burnout, self-censorship, and a breakdown of trust. Cycle time data from 216 companies and over 11,000 developers shows that individual performance fluctuates dramatically week to week — it is not a stable personal trait — which means slow periods are usually an environmental problem, not a personal one. Over-production pressure (the constant pull towards short-term delivery) has measurable cascading effects: developers stop mentoring, stop surfacing problems to managers, and stop investing in long-term code quality. It can be measured and, with committed leadership, changed within weeks. AI is producing genuine identity threats, not just productivity disruption. Teams that lower the "threat temperature" — framing change as a shared technical challenge and affirming that new skills can always be learnt — unlock significantly more adaptive and curious behaviour. Metacognitive scaffolding — building structured strategies for thinking about your own thinking, not just raw output — is more trainable than cognitive capacity and is almost entirely absent from how agentic coding environments are currently designed. Superordinate goals (shared outcomes that transcend individual preferences) allow diverse teams, including those who prefer deep solo work, to collaborate productively without demanding that everyone care about the product in the same way. Chapters (00:00) Opening (01:06) Cat's background and the book (04:40) Defining a software team (07:02) Building the Developer Success Lab (10:26) The brains and jars model (13:14) What the model costs teams (17:54) Why communicating value is so hard (19:04) What change looks like in practice (23:01) Code review anxiety and cycle time research (27:55) AI's effect on developer identity (31:57) Agentic coding and cognitive fatigue (35:46) Threat, play, and psychological safety (38:19) Working across disciplines (43:04) What product managers can do (48:00) Wrap-up Referenced The Psychology of Software Teams by Dr Cat Hicks — Routledge The Programmer's Brain by Felienne Hermans The Psychology of Computer Programming by Gerald Weinberg Developer Success Lab (Pluralsight) DORA project Catharsis — Dr Cat Hicks's consultancy "Fight for the Human" — Dr Cat Hicks's newsletter Dr Cat Hicks on Bluesky and Mastodon: @grimina Learning Opportunities Claude skill — by Dr Cat Hicks Deliberate practice study (40,000 chess players)

Developers’ problem-solving, creativity, and collaboration is what grows and maintains functioning software systems–and all the technology that interacts with software. And because modern technology is constantly changing, how well developers keep solving problems, creating and collaborating is at the heart of maintaining any technology organization’s performance and capabilities. But designing for developers’ problem-solving simply hasn’t been at the forefront of how we put software teams together or how we run technology organizations. It’s showing up in their stories and in the data. Across decades of research on software teams, one thing is startlingly clear: developers do not feel understood. In this talk, we'll explore a mission to change that: how using large-scale empirical research rooted in the psychological sciences brings us new evidence about critical aspects of developer thriving, such as agency, belonging, and learning culture, and can help us build new models for understanding our software teams. Along the way we'll untangle how old misconceptions about developer productivity hold us back, and the alternatives that come from a science-backed model for collaborative and cumulative cultures in software that drive sustainable innovation. This talk was recorded at Craft Conference 2025. The event was organized by CraftHub. You can watch the rest of the conference talks on our channel. If you are interested in more speakers, tickets and details of the conference, check out our website: https://craft-conf.com/ If you are interested in more events from our company: https://crafthub.events/

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

Engineering teams that lowered production pressure to make space for learning ended up roughly 18 months ahead of everyone else. This week is different: no news, no clock. Shimin and Dan sit down with Dr. Cat Hicks — psychologist for the humans in tech, principal scientist at Catharsis, and author of The Psychology of Software Teams — on how organizations misunderstand developer cognition, how to learn deliberately with AI instead of letting your skills atrophy, and what a healthy AI-native team actually looks like. Hosts: Shimin Zhang and Dan Lasky. Guest: Dr. Cat Hicks. ▸ Brains in Jars — Cat's name for organizations that treat developers as fungible, disembodied cognition. Developers are highly valued — just stripped of their humanity. It isn't even an accurate model: real problem-solving is heavily social. Brains in jars never produced great software. ▸ The 10x Engineer Myth — The lone-genius stereotype sticks because it rewards grind-set self-belief; Cat argues its costs are far bigger than we like to see. Dan brings the McCarthy core-protocols check-in ritual (mad, sad, glad, or afraid), and Cat explains why a technically credible engineer showing feelings rewires a team's stereotypes. ▸ Effortful Learning & the learning-opportunities Skill — Cat's Claude/Codex skill generates 10-15 minute deliberate-practice exercises from the files you're already working in. Built against the deficit mindset ("our brains will melt"). Ten minutes does something to your mind. It doesn't have to be five hours. ▸ The Fluency Illusion & Metacognitive Decoupling — We are bad judges of our own learning: fluent-feeling output masks understanding that isn't there. Cat on the scary lab studies: do you ever remember what you copy-paste? What works: self-quizzing, sketching architecture before implementing, interrupting agentic sessions with a short learning op. Metacognition is one of the few tractable interventions — working memory is hard to change, metacognitive strategy isn't, and it predicts life success. ▸ Measuring Your Own Skills — No good instruments exist for working developers to track their own skills over time. Cat, a former assessment scientist, wants to build them — which might accidentally fix interviewing too. ▸ Healthy AI-Native Teams — Dumping unreviewed AI output on teammates is a cultural statement, not a technical decision: it says their problem-solving doesn't matter. The fix is a shared team mental model — decide explicitly how you'll use AI for the next month, then test whether it worked. Teams that lowered overproduction pressure ended up roughly 18 months ahead. Scale in production demands matching scale in testing and auditing — borrow probabilistic thinking from computational biology and robotics. ⏱ Chapters 00:00 Cold Open — No News, No Clock 00:35 Meet Dr. Cat Hicks 01:14 Is Software Engineering Abnormal Psychology? 03:27 Brains in Jars — Why Orgs Misread How Developers Think 06:43 The 10x Engineer Myth 09:30 The McCarthy Core-Protocols Check-In 12:45 Effortful Learning & the learning-opportunities Skill 18:50 The Fluency Illusion & Metacognitive Decoupling 22:51 Measuring Your Own Skills (and Fixing Interviews) 24:38 What Are We Actually Learning Right Now? 26:25 Informed Patient — the Same Problem Outside Tech 29:39 What a Healthy AI-Native Team Looks Like 33:54 The Book, the Podcast & the Newsletter 🔗 Links The book: • The Psychology of Software Teams — Routledge: https://www.routledge.com/The-Psychology-of-Software-Teams/Hicks/p/book/9781032963389 Cat's work: • Dr. Cat Hicks: https://www.drcathicks.com/ • Catharsis: https://www.catharsisinsight.com/ • Change, Technically (podcast): https://www.changetechnically.fyi/ • Fight for the Human (newsletter): https://www.fightforthehuman.com/ The skills: • learning-opportunities: https://github.com/DrCatHicks/learning-opportunities • learning-goal: https://github.com/DrCatHicks/learning-goal Follow Cat: • Bluesky: https://bsky.app/profile/grimalkina.bsky.social • LinkedIn: https://www.linkedin.com/in/drcathicks/ 🎓 About Dr. Cat Hicks Dr. Cat Hicks is a psychologist for the humans in tech and principal scientist at Catharsis. She wrote The Psychology of Software Teams (CRC Press, July 2026), co-hosts Change, Technically, writes the Fight for the Human newsletter, created the learning-opportunities and learning-goal skills, and authored the Developer Thriving and AI Skill Threat frameworks. 🎙 About ADI Pod ADI Pod (Artificial Developer Intelligence) is a weekly conversation show for working developers, sorting the hype around AI from what it actually delivers. New episodes Fridays. • https://www.adipod.ai • humans@adipod.ai If the fluency illusion hit a little too close to home, subscribe and tell us what you're doing about it. #CatHicks #PsychologyOfSoftwareTeams #Metacognition #10xEngineer #AICoding #AIPodcast #ADIPod

Ned and Kyler are joined by Dr. Cat Hicks to discuss her new book "The Psychology of Software Teams." They talk about software development from a psychological perspective, including how negative stereotypes of developers can lead to them being treated simply as “brains in jars” in toxic environments. They also point out the pitfalls of relying too heavily on one person, which can lead to burnout, and how “bands are more important than rock stars”. Links: The Psychology of Software Teams - Routledge - https://www.routledge.com/The-Psychology-of-Software-Teams/Hicks/p/book/9781032963389 The Psychology of Software Teams - Amazon - https://www.amazon.com/Psychology-Software-Teams-Cat-Hicks/dp/1032963387/ Fight for the Human Newsletter - https://www.fightforthehuman.com/ Dr. Cat Hicks on LinkedIn - https://www.linkedin.com/in/drcathicks/ Day Two DevOps is part of the Packet Pushers network. Visit our website to find more great networking and technology podcasts, along with tutorial videos, the Human Infrastructure newsletter, and loads more resources for building your IT career. https://packetpushers.net

The Psychology of Technologists 💬 Speaker(s): Cat Hicks 📝 Abstract: Technology teams are struggling to be heard. Technologists are grappling with high turnover, high burnout, and low resilience in the face of rapidly-accelerating technological change. Even though effective technical teams are an essential part of our world continuing to work, many organizations struggle to understand their technical teams, stuck in old stereotypes that treat technical people like isolated machines. To build a thriving future, we need a new way of working together and understanding our own minds as we build technology. In my empirical research across thousands of developers, technical managers and their teams, we've explored what a psychologically-rich environment looks like for modern technologists and found important signals that can guide teams toward greater resilience, innovation, and thriving. In this keynote we'll unlock access to the psychological sciences and evidence that you can use to make your every day more human. 🔗 Links: Dr. Cat Hicks - https://www.drcathicks.com/ Catharsis Consulting - https://www.catharsisinsight.com/ Center for Open Science (COS) - https://www.cos.io/ Fight for the Human Newsletter - https://www.fightforthehuman.com/ posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/

Dr. Cat Hicks, a psychologist studying software teams, joins RedMonk’s Kelly Fitzpatrick to discuss the role of psychology in technological innovation. Dr. Hicks emphasizes the importance of understanding the human aspects of software development and shares insights from her recent research projects, including a study on code review anxiety and the impact of what she calls “AI Skill Threat” on developers. Dr. Hicks also addresses the challenges faced by scientists today, the significance of cumulative cultures in software, and her upcoming book on the psychology of software teams. Show notes: https://redmonk.com/blog/2025/03/03/psychology-technical-innovation-and-why-we-need-science-with-dr-cat-hicks/

Are you writing enough code, keeping up with the latest technology, or driving product progress? Developer productivity is a top priority for developers, engineering leaders, and businesses. But attempts to measure developer productivity can be risky, damaging, and downright misleading. From the infamous lines of code to brutal code reviews, every developer has a horror story of a time their authentic effort and problem-solving was mismeasured, or worse, even punished. In this talk, I want to propose a different, science-backed approach to productivity using research evidence from a study with 1200+ developers: developer thriving. I’ll tackle why “thriving” remains a challenge, exploring three myths about productivity that I believe hold our industry back, and thinking through better and more scientific ways of understanding productivity for engineering organizations, leaders, and developers.

Cat is a research architect and psychologist for software teams. She leads high-velocity research agendas that provide new empirical evidence to answer pressing questions about tech innovation and developer thriving. She's the Principal at Catharsis Consulting and the author of a forthcoming book on the Psychology of Software Teams. Takeaways • Cycle time is a complex topic that requires careful definition. • Cycle time measures can provide insights into software development processes. • Organizations need to measure cycle time over a long period to understand trends. • Cycle time is highly variable and can be influenced by seasonality • It's important to consider the context in which cycle time is measured. • Developers often feel their work is invisible to management. • Cycle time can be used to improve communication with customers. • Organizations should create their own benchmarks for cycle time. • A thoughtful approach to metrics can empower teams and improve performance. Chapters 00:00 Introduction to Cycle Time and Research Background 06:03 Defining Cycle Time and Its Variations 10:32 Understanding the Audience for Cycle Time Metrics 15:03 The Importance of Measurement in Software Engineering 19:11 Insights from Cycle Time Research and Practical Applications 21:27 Understanding Cycle Time Measurement 27:07 Data Collection and Statistical Modeling 33:26 Benchmarking and Organizational Context 41:16 Creating a Cycle Time Playbook