The first time I used GitHub Copilot, I expected a toy. A smarter autocomplete, maybe. But after a few sessions, something clicked. It wasn’t perfect, but it made me noticeably faster, especially with boilerplate and repetitive tasks. That was the moment I knew that this wasn’t just hype. It was the start of a shift.
Since then, the question has evolved. It’s no longer “Can AI code?”. That’s been answered. Now we’re asking better questions:
- How should we work with it?
- What should still be done by humans?
- Where’s the edge between speed and understanding?
This is the AI moment for me.
The early hype
Back in late 2022, ChatGPT became a headline in every news outlet. In just a few months, it became the fastest-growing app in history. The buzz was everywhere:
- “AI will replace programmers.”
- “You can build an app just by prompting.”
- “Design, content, testing, engineering, all automated by AI!”
People dreamed big, and startups popped up overnight offering AI tools for everything: slides, UIs, marketing copy, legal docs, code generation. We saw the promise everywhere: “faster software, smaller teams, better automation”.
And to be fair, some of that was real. Engineers, including myself, saw immediate boosts in productivity. We could ship things faster, explain ideas more clearly, or get problems solved with a good prompt.
But at the same time, something felt off. Many outputs were “almost right”, not right. Code that ran, but wasn’t elegant. Docs that sounded smart, but missed the nuance. Designs that looked okay, but weren’t usable. We started to realize that AI could do stuff. But building something great? That still needed us.
The shift from excitement to baseline job expectation
What’s happening now is a transition from excitement to expectation. AI is no longer a new thing; it’s a baseline job expectation.
In many companies, using AI tools is becoming part of the job. Shopify’s CEO started this by saying publicly that they expect every employee to use AI in their workflow. Not using AI now feels like not using Google decades ago.
And this shift isn’t just about speed. It’s about how we work.
- Engineers are rethinking their workflows: What parts of coding should I keep? What can I automate?
- Product teams are exploring new collaboration styles: Can PMs write specs in ways AI can understand and use?
- Leaders are revisiting team structure: Do I still need the same ratio of juniors to seniors?
The story is no longer about AI replacing engineers. It’s about engineers who know how to work with AI outperforming those who don’t.
How to ride the shift
If you’re leading a team, building products, or writing code, here are some practical ways to move from hype to real impact:
Treat AI like a teammate, not a tool.
AI is your junior engineer, who is fast, tireless, and need explicit instruction. Don’t expect it to read your mind. Give it clear instructions. Check its work. Teach it your standards.
Make AI part of your workflow, not a separate task.
The biggest gains come when AI is embedded in your daily flow. Use it to:
- Draft your merge request descriptions.
- Refactor repetitive code.
- Generate test cases from API specs.
- Summarize messy meeting notes.
Expect more, not less, from engineers.
Now, AI can write a lot of code. The real value of engineers is shifting upstream. Understanding the problem. Making trade-offs. Guiding the system design. Holding the line on quality.
Update your team’s definition of “done”.
If your timeline doesn’t shift with AI in the loop, you should ask: “Why not?”. With the right integration, many tasks should move 30 to 50% faster. If that’s not happening, either the workflow is broken, or AI isn’t being used effectively.
Don’t overcorrect.
Don’t overcorrect. AI won’t triple your delivery speed. It might give you 20 to 30% gains. That’s still a huge win, but don’t fall into the trap of overpromising. Sustainable change takes new habits, not just new tools.
This moment is real. Let’s use it well!
AI won’t replace you, but engineers who use AI well will replace those who don’t.
The hype was loud, but the real opportunity is quiet: better workflows, clearer thinking, faster feedback.
Don’t just try AI. Integrate it. Make it part of how you think, build, and collaborate.
This is the shift. The AI moment is here. Now it’s your move.