The Playing Field Is Level Again

Here’s something that doesn’t happen often: nobody knows the best way to build software right now.

Not the big tech companies. Not the consulting firms. Not the senior architects with 20 years of experience. Everyone is figuring it out. The rules change by the week.

Your average enterprise engineer knows about as much about building with AI as some motivated teenager with a laptop. Maybe less. The institutional knowledge that used to take years to accumulate? It’s being rewritten in real time.

This is chaos. It’s also an enormous opportunity.

Why Fundamentals Still Win

AI doesn’t replace good engineers. It multiplies them.

The people worried about AI taking engineering jobs are missing something fundamental: the job was never about writing code. It was about designing solutions. Understanding problems. Making tradeoffs. Knowing what to build and what to skip.

Anyone who’s worked for more than a year knows this. The hard part isn’t typing. It’s thinking.

Claude Code lets you build faster than ever before. But “faster” only matters if you’re building the right thing. That judgment—what to build, how to structure it, when to stop—that’s still human. That’s still the job.

Good engineers become great with AI tools. Mediocre engineers become faster at producing mediocre output. The sorting is more visible now, not less.

The $200k Coasting Era Is Over

Let’s be honest: there’s been a class of engineer collecting $200k to do not much.

Meetings. Code reviews that don’t catch anything. Tickets that take a week when they should take a day. The kind of presence that looks like work without producing work.

That’s not a viable position anymore. When AI makes it obvious who ships and who doesn’t, the gap becomes impossible to ignore.

But here’s the thing: this is actually good.

There are so many talented, enthusiastic, deserving people who couldn’t break into tech because the doors were closed. People who would actually build things if given the chance. The coasting jobs disappearing means those spots open up for people who want them.

The industry was carrying dead weight. Now it’s not.

The Demand Is Enormous

Look around. Everything needs software. Everything needs automation.

Small businesses running on spreadsheets that should be apps. Manual processes that waste hours daily. Integrations that would take an afternoon to build but nobody’s built them. Data sitting in silos because the connection doesn’t exist.

The demand for software has never been higher. We’ve barely scratched the surface of what should be automated.

Yes, some skills and moats and businesses aren’t viable anymore. Yes, some work needs fewer humans than it used to. But the total amount of software that needs to exist is growing faster than AI is reducing the human effort per project.

There’s more to build than ever. The tools to build it are better than ever. The barriers to entry are lower than ever.

What Actually Changes

Here’s what AI changes about software engineering:

Speed — Projects that took months can take weeks. Features that took weeks can take days. The iteration cycle compresses dramatically.

Scope — A single person can build what used to require a team. Solo projects can reach production quality that previously needed multiple specialists.

Skill focus — Writing boilerplate becomes trivial. Understanding architecture, making design decisions, debugging complex systems—these matter more than ever.

Entry barriers — You can learn faster, get feedback faster, build real things faster. The gap between “learning to code” and “building something useful” shrinks.

What doesn’t change:

Judgment — Knowing what to build. Knowing when to stop. Knowing which tradeoffs matter for your specific situation.

Taste — Recognizing good design. Understanding what users actually need versus what they say they want.

Debugging — AI helps here too, but understanding why something breaks still requires human reasoning about systems.

Communication — Explaining technical decisions. Collaborating with non-engineers. Translating business needs into technical solutions.

The Enthusiasm Gap

Something interesting is happening: enthusiasm is becoming a competitive advantage.

When established engineers are confused and defensive about AI, the people who lean in gain ground fast. The 18-year-old who’s excited to learn can outpace the 10-year veteran who’s resistant to change.

This doesn’t mean experience is worthless. It means experience plus enthusiasm beats experience minus enthusiasm. And fresh enthusiasm beats stale experience.

If you’re excited about this moment—if you want to figure out new ways to build things—you’re in a better position than you realize.

It’s an Exciting Time

I’ll say what the cynical takes won’t: this is an exciting time to be a software engineer.

The tools are incredible. The problems are real. The opportunities are wide open. Nobody has all the answers, which means there’s room for anyone who wants to find them.

Yes, things are uncertain. Yes, the landscape is shifting. Yes, some paths that used to work don’t work anymore.

But the core thing—building software that solves problems for people—that’s more accessible and more valuable than ever.

If you’ve been waiting for the right time to start, this is it.

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