For nearly a decade, that foundation served me well. I became the person on the team who could untangle merge conflicts, recover lost commits, and help engineers out of messy Git situations. It saved me countless hours over the years.

This week, I discovered git worktrees, and I had no idea what they were.

A Gap I Didn’t Know I Had

Lately, I’ve been following a handful of developers who are writing and experimenting in the open with Claude Code. They show up in my timeline not because I deliberately curated a list, but because I keep lingering on posts about AI-assisted development.

One day, I came across a thread of practical tips for getting more out of Claude Code from Boris Cherny, he is one of the creators of Claude code itself. One suggestion was about using “learning mode” to have Claude generate visual HTML explanations of concepts.

The other one mentioned using worktrees for programming in parallel.

I realised I’d never really encountered worktrees in practice. I tried to recall if they were covered in the Pro Git book. I couldn’t remember seeing them. A quick search confirmed why: git worktrees were added in Git 2.5, released in July 2015, just after the version of the book I had read.

No big mistake. Just a feature I’d never had a reason to reach for before.

Until now.

How I’ve Been Learning Lately

After reading that thread, I decided to combine two of Boris’s tips: learn about git worktrees using Claude Code’s learning mode.

Learning mode is one of Claude Code’s output styles. You enable it by typing /config and selecting “Learning” from the options. It changes how Claude responds: instead of just giving you answers, it explains the why, offers insights that connect to broader patterns, and sometimes asks you to write small pieces of code yourself so you’re not just passively reading.

I asked Claude to generate a visual HTML explanation of git worktrees. What came back was an interactive diagram showing how worktrees share the .git directory, how branches map to directories, and what happens when you add or remove worktrees.

I still believe in the deep-reading kind of learning. The Pro Git book was dense, comprehensive, and required long stretches of focus. Sitting with a well-written book, building a mental model slowly, establishing depth. Those things compound over time. Reading that book was a great help to my career and has saved me countless development hours, week after week.

But this was different. Immediate, visual, iterative. I could ask follow-up questions. Not better or worse. Just a different tool for a different moment.

I turned that exploration into a small Vercel app that explains worktrees visually. Because if I just learned this after 10 years with Git, maybe others will find it useful too.

The Pace of Now

There’s a strange mix of emotions that comes with being a software developer right now.

On one hand, I feel lucky. The tools available to us are extraordinary. I can talk to an AI that understands code, generate visual explanations on demand, and ship small interactive apps in an afternoon.

On the other hand, there’s a quiet unease. A sense that the ground is shifting. That I might not always be learning the right things. That the opportunity cost of choosing one path over another feels unusually high.

And yet, in evenings like this, when you stumble into something new using these tools ,it scratches that familiar itch. The simple satisfaction of learning something new, in deep detail, using AI tools of today.

So I’ll keep doing that. Notice something useful, learn about it, try it, and write it down.

For now, that’s enough.

My belief has previously been somewhat similar to Javed Akhtar. His argument: If God is all-powerful and all-merciful, why does evil exist in the world? The response that God created the possibility of evil but isn’t evil himself felt inadequate. Couldn’t an omnipotent being design free will without the bombing of innocent people?

I’m not an atheist. More agnostic, leaning toward “probably no god.” The universe feels too random, too brutal, too indifferent for someone to be running it who actually cares.

Then I watched a documentary about Demis Hassabis and DeepMind. I kept thinking more and more about the question, and got reminded of a third probability and how Google DeepMind is actually doing that.

What DeepMind is Building

DeepMind has built AIs called Genie. Given a single image, say, a photograph of a waterfall in California, it can generate a navigable, game like 3D environment.

Then they drop AI agents called SIMA into these worlds. The agents have goals: navigate this maze, climb that ladder, maximize your score. They fail. They learn. They improve. Endless trial and error.

From a SIMA agent’s perspective, that generated world is reality. They don’t know their creators exist. They don’t know they’re in a simulation. They simply exist, strive, fail, and try again.

The Third Option

The debate offered two familiar positions.

The Mufti argued that God must exist because existence itself cannot regress infinitely. There has to be a first cause, something which wasn’t created. Akhtar countered that even if such a being exists, it cannot be both all-powerful and all-merciful, because a just and caring god would not permit horrors like the suffering of children.

Watching DeepMind create worlds and populate them with goal-seeking agents, I began to think of a third possibility, one that neither side addressed.

Maybe there is a god. Maybe he just doesn’t care about us.

This wasn’t an entirely new idea for me. I remember reading something similar in Yuval Harrari’s book Homo Deus. But seeing DeepMind build worlds and release agents into them gave that intuition a concrete shape.

Do the researchers care about individual SIMA agents? Do they mourn when one fails? Do they intervene when an agent keeps hitting the same wall? No. They’re running experiments. They’re interested in the system, the emergent patterns. Individual agents are data points.

We might not be anyone’s children. We might just be agents.

This answers Akhtar’s Problem of Evil more cleanly than the Mufti’s defense. Why does God allow suffering? Because he’s not watching. He set up the world, dropped us in, and he’s waiting to see what emerges. War isn’t a theological puzzle if the creator is indifferent. It’s just what happens when you let a simulation run.

The Simulation Question

Philosopher Nick Bostrom made a famous argument: if advanced civilizations can create realistic simulations, and they have any interest in doing so, the number of simulated beings would vastly outnumber real ones. Statistically, we’re probably simulated.

Recent calculations put it at roughly 50-50 odds we’re in base reality. But if we ever create conscious simulations ourselves, those odds collapse. We would almost certainly not be real.

The Uncomfortable Parallels

DeepMind creates worlds. So does the god of every religion.

The system gives agents purpose—score points, navigate mazes. Religion says we’re created with purpose too.

The creators are invisible to their creations. The Mufti argued God is known through reason and signs, not physical detection. Same structure.

They allow failure and suffering—that’s how agents learn. The Mufti’s free will argument, essentially.

They can end the simulation whenever they want.

Where This Leaves Me

I’m not suddenly religious. I’m not convinced we’re in a simulation. But my leaning towards their being no creator has changed slightly.

This feels more honest than “mysterious ways.” It makes sense of the world’s cruelty without requiring deep theological thinking.

Somewhere on a DeepMind server, a SIMA agent just hit a wall for the thousandth time. It doesn’t know why. It can’t conceive of Demis Hassabis. It simply tries again. Tomorrow morning, I’ll brew my coffee for the ten thousandth time, commute the same route, solve the same kinds of problems.

Maybe that’s the point. Maybe it isn’t. We keep going anyway.

Author’s note: I used AI as a thinking and editing partner while writing this essay. The ideas, arguments, and conclusions are my own.

I found the video really insightful, some of the best reassurances one can get about why developers are not going anywhere. Humorous and thoughtful at the same time. The video is great in itself, it talks about many qualities that a developer in the age of AI should have to keep themselves relevant. Major points being

1. Being curious - leads to invention

2. Thinking in terms of systems - how your change impacts the overall ecosystem

3. Clear communication - communicating effectively

4. Ownership - YOU own the code, not the AI tool

5. Being a Polymath: Broaden your expertise
   

However, the word which really struck with me was “Renaissance”. I have been thinking recently about what the future is going to be like for developers in the coming years, but it has all been wild imagination, and I would like to marry the word Renaissance with my thoughts here.

Renaissance is a big word. It means ‘rebirth‘ in French. However, the period in history which is signifies carries even more weight. For those unaware, the European Renaissance was a period from roughly 1300s to 1600s where Europe came out of the middle ages or the dark ages. It was a dark age because religion dominated, scientific discoveries were minimal, art was not widespread and knowledge was centralised to a few. The renaissance helped humans understand the human potential, broke the intellectual monopoly of institutions, and unleashed creativity, science, and art at a scale never seen before. It included the birth of humanism - focus on human potential rather than solely on religion, invention of the printing press which democratised information, artistic masterpieces like The Last Supper, The Mona Lisa, carving of David, and scientific breakthroughs like discovery of telescope which proved the concept of heliocentrism.

It changed the common man too - albeit slowly, over decades to come. The common man began challenging the church, the feudal heirarchies, became traders, earned better wages and had access to information like never before.

Now coming back to developers and AI. If we are truly at the renaissance point for developers, over the next few years, the renaissance developer will :

1. Realise his expanded potential. With information available at an unprecedented level, the renaissance developer will push boundaries in terms of his creation. The barrier to satisfying curiosity will be lower than ever, and will result in some truly great products.

2. Questioning outdated constraints and processes. The Renaissance developer will have leverage which large teams used to have before him. He will be empowered to question existing broken processes and break out of them with much less effort than before.

3. Shift from employment to ownership mindset. The Renaissance redefined who could own ideas, art, businesses, political power. AI allows the developer to own products, audiences, intellectual property, and distribution if they wish to.

4. Be a true Polymath. The renaissance led people like Da Vinci to become a philosopher, a scientist, an artist all at the same time. the polymath developer can increasingly operate across product, design, strategy, and even business roles. AI enhances this, not replaces it.

The renaissance is the single greatest period which changed the psychology of the human mind like never before, so if we’re on the brink of a similar transformation for developers, I find that incredibly exciting.

Would love to hear your thoughts on this!

Disclaimer: The use of “he/his” in this post is not intended to imply gender specificity. My thoughts around this post are entirely gender-neutral. Please excuse any imprecise pronoun usage.

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