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Favour Afolayan
Favour Afolayan

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AI isn't taking our jobs — It's taking our illusions

There’s a growing sentiment that software engineers shouldn’t tie their identity too closely to their work. On the surface, that sounds healthy. But in practice, it’s more complicated.

If most of your adult life has been spent learning, practicing, and becoming genuinely good at one thing, it’s only natural that it becomes part of how you see yourself. We see this shift all the time—people redefine themselves when they get married, have kids, or take on new responsibilities. Identity evolves with focus.

For a long time, software development rewarded deep attention to code: patterns, architecture, edge cases, and craftsmanship. That focus shaped not just our careers, but our sense of value.

Now we’re in a moment where generative AI can produce high-quality code, surface edge cases, and move at a speed that years of experience alone sometimes can’t match. That realization is unsettling. It feels similar to what elite athletes experience near retirement—when the skill they’ve spent their lives perfecting no longer guarantees relevance.

Some reflections from this shift

  • We were fortunate to get good at something

    Not everyone gets the opportunity to spend years honing a valuable skill and be rewarded for it. Many people never become particularly good at what they do. That perspective matters, especially now.

  • The learning didn’t lose value—it got leveraged

    The same discipline we once poured into mastering languages and frameworks should now go into mastering these tools. Concepts that used to take years to internalize can now be explored, tested, and understood in weeks.

  • Feeling behind is a normal response

    Things are moving fast. Not everyone will keep up at the same pace, and that’s okay. This is another moment of professional molting—uncomfortable, but necessary.

  • Coding was never the whole job

    Even before AI, writing code was only part of the role. Context, trade-offs, judgment, communication, and decision-making have always mattered more than raw syntax.

  • No role is immune

    Every job is being pressured to justify its value—even executive roles. Software engineering isn’t special in that regard; it’s just more visible right now.

  • AI is leverage, not replacement

    Giving an experienced engineer AI tools is like giving someone used to a Pentium 4 a modern MacBook Pro. The person didn’t change—their leverage did.

  • Tools still need orchestration

    AI decentralizes access to powerful capabilities, but tools don’t decide what to build, why it matters, or when it’s wrong. Humans still do that work.

A reminder about perspective

At moments of rapid change, pessimism can feel intellectually safer than optimism. But safety isn’t the same as progress.

As Elon Musk put it at Davos:

“For quality of life, it is actually better to err on the side of being an optimist and wrong rather than being a pessimist and right.”

That perspective matters here. The choice isn’t between naïve optimism and informed realism—it’s between freezing in fear and moving forward with intention.

A reframing worth considering

If you feel your relevance or job security being pried from your hands, you might actually be fortunate, that discomfort isn’t necessarily a warning—it may be an invitation, that tension is a signal that it’s time to molt—time to shed an identity built purely on execution and move toward higher-purpose work.

Not everyone gets a forced moment of reinvention. Some coast until they’re obsolete. Others evolve while the pressure is still survivable.

Moments like this strip away the parts of our identity that were overly attached to tools or speed and push us toward higher-leverage work: clearer thinking, better judgment, stronger context-setting, and real responsibility. It’s uncomfortable because growth usually is—but comfort was never where progress lived.

Closing thought

AI didn’t suddenly make our experience useless. It exposed which parts of our value were tied to execution speed—and which parts were tied to understanding.

The future isn’t about competing with tools. It’s about learning how to direct them well—and accepting the responsibility that comes with that.

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