Developer Tea

You're tired of hearing that you need to pick up AI, so today I'm not going to add to that pile. Instead, we'll look back at two moments in history that look a lot like this one: the arrival of Fortran in the 1950s, and the spread of autopilot in commercial aviation. Both show how new abstractions change the shape of our work without being purely good or purely bad.

Fundamentals get talked about constantly, but rarely defined. In this episode I dig into what a fundamental actually is — the building blocks, heuristics, and core characteristics that don't change — and why they matter more than ever in a profession where abstraction moves faster than almost anywhere else. If you feel like you can't keep up with every new framework, model, or tool release, the answer isn't to read faster. It's to step up a level.

A 1967 study gave us the concept of learned helplessness — but the same researchers later reversed it. Passivity is our default state; control is what we learn. In this episode, I unpack what that neuroscience means for how you face hard things in your career, and why the action you take doesn't have to match the size of your problem.

As you grow as an engineer, something counterintuitive happens: the systems you build get simpler, not more complex. In this episode, I explore why senior engineers tend to collapse abstractions, accept certain risks, and reduce the surface area they're responsible for — and what drives that shift underneath the surface. Understanding the reasons behind the trend is what lets you get there on purpose instead of waiting a decade to arrive there accidentally.

Accountability is one of the most important concepts in your career—and one of the most frequently weaponized. In this episode, I unpack why so many of us have a visceral reaction to the word, and offer a pragmatic, functional definition that reframes accountability as something a good engineer actually invites. Drawing a parallel to software bug reports and root-cause analysis, I explain how healthy accountability creates clarity of expectation rather than surprise punishment.

The skills you've built for reading people, reviewing code, and making calls under uncertainty all rely on the same brain shortcut: substituting an easier question for a hard one. In this episode, Jonathan explores how to take that automatic mental trick and use it on purpose — shrinking weighty, paralysis-inducing decisions down to the small, low-stakes actions they're actually made of.

The skills you build and the tools you master matter, but they aren't your most important asset when things go wrong — and something eventually will. In this episode, I work through why our careers and lives are governed more by avoiding catastrophic downside than by chasing upside, and why the single best tool for surviving a bad event isn't testing, insurance, or money — it's genuine trust with the people around you.

The skills you spent years building are getting cheaper to replicate—but that's not where the friction lives. In this throwback episode, I unpack why agentic coding hasn't made your team faster, and why the answer is the oldest model in the book: the theory of constraints. If you're a manager or a senior engineer being asked "why can't this go faster," this one's for you.

The skills problem isn't going anywhere — it's just wearing new clothes. In this episode, I unpack how the lessons we learned decades ago (limiting work in progress, the theory of constraints, test-driven development) are coming roaring back as the fundamentals that will carry you through the agentic shift. The bottleneck has moved, and knowing where it went changes how you should work.

The skills that survive every industry shakeup aren't the ones you can Google — they're softer, harder to name, and far more durable. In this episode, Jonathan explores principle-oriented thinking: the practice of stripping away the labels we attach to tools, roles, and even ourselves to see what something actually does at its core. It's the difference between handing your coding off to an agent and rethinking your entire workflow around what these new materials are truly capable of.

Feedback is one of the hardest skills in any career, and most of us have only experienced a handful of moments where it actually drove positive change. In this episode, Jonathan explores how to give and receive feedback that leads to real growth — starting with setting your ego aside, getting clear on your goal, and using behavior-based models like SBI and Netflix's Four A's. It's a durable skill that turns a contentious, dreaded conversation into a genuine pathway to career development.

If you're a software engineer right now, the questions you're asking about your career probably feel existential. We've been spending a lot of time on this show preparing for the changing industry—what skills matter, what mindset works—and one answer keeps surfacing: your ability to update your mental models is itself the critical skill. In today's episode, I push on that idea directly. Some of the thinking models that defined good software engineering for the last decade deserve real scrutiny now, and a few of them may deserve to be thrown out entirely. This is an uncomfortable ask, especially for those of you who earned your wisdom the hard way—but the engineers who can hold their hard-won models loosely are the ones who won't hit a ceiling.

If you're a software engineer right now, you likely feel like your world is changing overnight. We are writing half or less the amount of code that we wrote even a year ago, which represents a seismic, groundbreaking shift in our industry. For many of us, this career has always been engaging for deeply creative and intellectual reasons—and that excitement is still here. But our mental models of what it means to be a good engineer, and what it means to keep improving, have gone a little stale. In today's episode, I want to talk about a distinction that I believe will become the cornerstone mistake for seasoned engineers: confusing _practice_ with _adaptation_, and leaning on the wrong one at the worst possible moment.

If you've heard that your job in the agentic coding era is to "become a manager of agents," you may have noticed something doesn't quite fit. Most of us never trained to be managers, and frankly, that's not the role most engineers want. In today's episode, I unpack what that shift _actually_ means — it's closer to a tech lead or architect mindset — and zoom in on a specific interviewing and on-the-job skill that will help you stay employable: how you think about, talk about, and take ownership of failure.

What happens when you discover that a book that fundamentally changed how you think is built on a shaky foundation? In today's episode, I share my own struggle with the replication crisis surrounding Daniel Kahneman's *Thinking Fast and Slow*, and I use it as a springboard to talk about a much bigger skill: knowing how to update your beliefs when reality shifts underneath you. This isn't about throwing out science or losing trust in your heroes. It's about developing the muscle to replace old explanations with better ones — a skill that has never been more important for software engineers.

If you've felt like the show has leaned hard into agentic coding lately, today's episode opens with why: the realistic future of software engineering includes these tools, and pretending otherwise makes this show less useful to you. From there, I want to give you something practical — a transferable skill that will compound in value as LLMs get more capable, and that also makes you a stronger communicator with humans. The skill is learning to speak in **meaning-rich, high-specificity abstractions**.

Many engineers have built their careers on the belief that coding is their primary value — the flagship skill, the gate opener, the reason they get paid. But if AI can do a large slice of that implementation work, then coding-as-your-core-value leaves you in a very narrow place. In today's episode, I want to reframe how you think about your skills, and give you a simple three-part framework for deciding which skills are actually worth investing in as the industry shifts.

Your job is changing faster than ever, and it might be tempting to believe that chaos is simply the new norm. In today's episode, I want to push back on that idea. Part of your role as a senior engineer or leader is to make sure chaos doesn't win — not just to rein it in reactively, but to go on the offense and create order. We'll talk about one important way to do this: protecting the ceremonies on your team.

Your tool set isn't just a collection of utilities — it's the environment you live in every day, and it's shaping you whether you realize it or not. In today's episode, I explore two principles that senior engineers consistently apply to their workflows, regardless of which specific tools they're using. As our industry goes through one of the most rapid periods of change in the last 20 years, the engineers who thrive won't be the ones chasing every new tool — they'll be the ones who obsess over reducing friction in the work they do most often.

Most software engineers believe that having the best thinking — the most complete, most nuanced analysis — is what drives career success. Early on, that belief probably helped you invest in yourself and improve. But at some point, the habit of overanalyzing starts to work against you. In today's episode, I explore why the most useful beliefs in your career aren't necessarily the most accurate ones, and how deliberately leaning into "useful illusions" — heuristics that are technically incomplete but directionally correct — can make you more decisive, more action-oriented, and less likely to burn energy on arguments that don't matter.

As coding becomes cheaper and faster through agentic tools, the bottleneck in software development is shifting upstream — away from writing code and toward the decisions that determine what gets built and why. In today's episode, I explore why decision-making is rapidly becoming the central activity of your job as a software engineer, and I walk through two common traps that even senior engineers fall into when they start participating more in collaborative, organizational decisions.

If you're a software engineer right now, your feeds are probably overloaded with AI hot takes, tool announcements, and advice about how far behind you are. In today's episode, I take a different approach. Instead of prescribing what you should be doing, I open up about what I'm actually doing — from physical checklists and label makers to agentic workflows and 3D modeling with AI. This is a snapshot of one engineering manager's life in the spring of 2026, covering the small personal interventions, the books, the media, and the AI tooling that's shaping how I work and think right now.

If you're a software engineer right now, you likely feel like your world is changing overnight. We are writing half or less the amount of code that we wrote even a year ago, which represents a seismic, groundbreaking shift in our industry. However, the rapid introduction of new tools can slide quickly from exciting to purely chaotic, leaving you feeling like you are falling behind. In today's episode, I explore how this changes the nature of our day-to-day work, and why the key to surviving this transition is shifting your mindset from a traditional "Software Engineer" to an "Agent Manager".

AI is bringing massive changes to our industry, but it's not just about how fast you can write code or use agentic flows. In this episode, I explore how AI is fundamentally shifting the economic bottleneck of software development, and how you can use your systems-thinking engineering mindset to adapt and thrive in this new era.

Today, we are tackling the natural tension between the desire to make more money—getting a raise, finding financial stability—and the desire to have meaningful, purpose-driven work.

I've been delaying this episode for a long time because the topic is genuinely difficult and, for many of us, scary. AI is threatening not just to our livelihood, but to our sense of self-worth as creators. In this episode, I don't offer false guarantees about job security. Instead, I frame the problem through the lens of microeconomics and rational incentives to help you understand how to remain employable. We discuss why you must separate your ego from your current skill set and how to position yourself not as a competitor to AI, but as a force multiplier.

Do you remember the early days of your career? You likely spent hours coding late into the night, fueled not by a paycheck, but by the sheer joy of building. But somewhere along the way, that intrinsic fire faded, replaced by the extrinsic motivators of Jira tickets, performance reviews, and salary negotiations.

In today's episode, we are discussing one of the most common habits I see in high-performing managers and senior engineers. It isn't a single trick, a morning routine, or a specific productivity hack—it is a meta-habit. It is a specific way of thinking about how you spend your energy and time to avoid the burnout that comes from working hard without seeing commensurate gains,.

It is review season, and you might be finding yourself confused: you received high ratings and "exceeded expectations," yet the promotion you expected didn't happen. In this episode of the Career Growth Accelerator, I break down exactly why high performance doesn't always lead to promotion, helping you identify the structural roadblocks and strategic shifts necessary to move from senior individual contributor to staff, principal, or leadership roles,.

Are your career choices truly yours, or are they being held hostage by hidden vulnerabilities? In this episode you'll perform a "career pre-mortem" to identify the people, situations, and financial burdens that currently exert leverage over your decision-making. We explore how to gain autonomy by de-risking these areas—like eliminating debt or shifting how you relate to job misalignments—so you can reclaim the agency needed to make principled moves that align with your true purpose.

Evaluating what you are uniquely good at is more than just making a list of your current skills; it requires looking at your past, your future potential, and what actually energises you. In this episode, I introduce a practical tool called the Nine-block to help you map out your skills across performance and potential, while adding critical dimensions of energy and risk to help you break through career stagnation.

This episode marks the 11th anniversary of the show, and I want to celebrate by continuing our Career Growth Accelerator series. Today, we’re moving beyond the "autopilot" mode that many engineers find themselves in and learning how to define goals that are uniquely yours so you can find the specific challenges that will actually move the needle.

This episode kicks off the Career Growth Accelerator series, focused on the specific hurdles faced by mid-to-senior level engineers, managers, and leaders who are looking to move to the next level. Before diving into specific strategies, I’m addressing the fundamental prerequisite for real growth: getting out of your own way. We often block our own progress because our ego conflates our self-worth with our career position, making it impossible to see the real problems or lessons we need to learn. In this episode, I share a vital mental exercise to help you disconnect your identity from your job title and begin diagnosing your career challenges honestly.

Are you a mid-to-senior level engineer or leader who has hit a career roadblock or found yourself stagnated? I'm launching the new Career Growth Accelerator series, focused on the difficult, non-obvious hurdles that prevent you from moving to the next level. In this foundational Episode Zero, I cover the critical prerequisite for growth: Getting Out of Your Own Way. Our ego often protects our self-worth by blaming external factors for failures, making honest diagnosis impossible,. • Learn why protecting your ego is the most dangerous way to control your career. • Discover the fundamental shift: disconnecting your self-worth from your career aspirations to gain clarity. • I introduce a distancing thought experiment to help you diagnose the real problems blocking your path. • Start focusing on the diagnostic aspect—What happened and why?—to build real momentum. Subscribe now so you don't miss out on this series!

When you hit a career roadblock, the methods that worked for you before often stop working. Today, I’m diving into why that happens, and why the first and most critical step in progressing past stagnation isn't doubling down on skills, but clearly defining the problem standing in your way.

We often look for ways to reduce the load on our brains, seeking shortcuts and optimizations to get ahead. Sometimes this works, reinforcing the belief that we can hack our way around every problem. However, this episode addresses the truth that many fundamental aspects of your career require something difficult, messy, slow, or inefficient, demanding deep thought and repeated failure.

If you're looking to accelerate your career growth, this episode gives you what may feel like hard truths about the path forward. So many engineers fall into traps of overthinking, chasing minor optimizations (like 5% or 10% productivity boosts), or playing the games of politics and networking. While these sideline activities aren't necessarily useless, I want to help you focus on the "big engines" and "primary considerations"—the things that will make the monumental difference in your career building strategy.

If you're an engineer looking to move into a senior role, you have likely heard that you need to demonstrate "ownership". Unfortunately, this crucial term is often poorly defined and leads to a major misconception: that ownership means being assigned a full project or a Tech Lead role. I want to dispel that myth and explain why ownership is actually a necessary behavior and mindset shift, applicable in almost every action you take, regardless of whether you’re leading a project.

Hey everyone, welcome to today's episode of Developer Tea. This is the second part of my interview with Bryan McCann, the CTO at you.com. If you haven't listened to Part One, I'd encourage you to go back, as it provides crucial context for our continued discussion. In this episode, we dive into how you can think about relating to and integrating the massive changes that AI is bringing to your job, whether you are a software engineer, manager, director, or product professional. Bryan and I discuss his interests beyond research, including art and organizational design.

Hey everyone and welcome to today's episode of Developer Tea. It's been quite a while since I've had a guest on the show. Today, I'm joined by Bryan McCann, CTO at you.com. We dive into a wide-ranging discussion, exploring the philosophical origins of his career—from studying meaning and language to working in very early AI research. This discussion is less advice-heavy and more focused on kind of theory and discussion. I hope this is insightful for you and helpful as you crystallize your own philosophies on these subjects.

I'm tackling a massive challenge today: burnout. While the standard advice usually involves working less, I want to show you a practical dimension of burnout you have more control over, focusing on increasing your agency and autonomy to manage chronic workplace stress more effectively. Burnout is classified by the ICD-11 as a syndrome resulting from chronic workplace stress that has not been successfully managed.

In this episode, I dive into the management mantra that "what is measured is managed" and explain why this simple assertion often leads to a complex trap. We discuss why the act of measuring team productivity is never neutral—it's an intervention that immediately changes behavior, often resulting in unintended consequences like gaming the metrics. We'll explore how to collaborate with your team to find measurements that truly drive desired behaviors.

I want to dive into the concept of Deliberate Practice, which sets the greatest apart in fields ranging from sports to writing to engineering. I’ll explain why it’s much more than just repetition or experience, and why applying it to your career can lead to rapid improvement. Most importantly, I will provide concrete ways you can apply deliberate practice to level up your engineering and leadership skills, especially in areas that are traditionally difficult to practice, such as communication and strategic decision-making.

This episode explores the concept of Locus of Control and why developing a more internal locus of control is beneficial for your career and life. You'll learn the difference between internal and external perspectives, why one is more useful than the other, and practical exercises to shift your mindset to believe you have more influence over the outcomes you care about.

In this episode we'll discuss why "Résumé Driven Development" is a powerful mental model for building a thriving career. Instead of seeing your résumé as just a job-hunting tool, you'll learn to use it as a guide for setting measurable, impactful goals that benefit you, your manager, and your company.

In this episode, we introduce a simple yet powerful mental model from the world of sports: forced vs. unforced errors. By understanding this concept, you can shift your focus from things outside your control to the simple, foundational behaviours that truly define a successful career.

In this episode, we introduce two fundamental thought experiments to help you uncover your true priorities and core values. By exploring scenarios of scarcity and abundance, you'll learn to align your daily actions with what truly matters, leading to a more satisfied career and life.

This episode explains what is arguably the best career advice you'll hear this week: the one skill that signifies seniority in software engineers is the ability to synthesise and optimise for multiple factors at once. Instead of focusing on a single factor, such as performance or maintainability, senior engineers identify and weigh the various trade-offs involved in any decision.

This episode focuses on the critical importance of having a backup plan, not just for technical redundancies but especially for situations involving human error, which are highly prevalent in one's career. The core argument hinges on understanding risk and reward curves, highlighting the disproportionate impact of failures compared to incremental successes.

Todays episode delves into understanding and leveraging second and third-order consequences – the ripple effects that occur after an initial action – and introduces forcing functions, which are an inverted way of thinking about these consequences, designed to drive desired outcomes by first determining "what must be true" for them to occur. The episode also connects these concepts to the importance of effective goal setting, explaining how well-defined goals provide clarity, focus, and a strategic framework for decision-making and career advancement.