How Developers Can Leverage AI Today
Let’s draw a parallel between today’s software engineers and Renaissance painters.
For centuries, painters thrived because society depended on their ability to capture reality. But when a better tool arrived – the camera – the ground beneath them shifted. The craft didn’t disappear, but the meaning of value changed forever.
“We’re facing something similar,” said Tejas Kumar (Developer Advocate, IBM) at the Shift conference in Kuala Lumpur. Citing tools like Cursor, Lovable, Bolt.new, Vero, and Windsor, he reminded developers that coding agents are already writing software faster (and often more reliably) than humans.
Developers must rely on first-principles reasoning
The data backs this up. Job openings across S&P 500 companies dropped sharply after ChatGPT’s release. Yes, market cycles and the zero-interest-rate hiring bubble played their part, but the trend points to something bigger: the profession is being reshaped, and developers need to understand how to stay relevant in the years ahead.
To navigate this landscape, Kumar argued, developers need to lean on first-principles reasoning. The term gets tossed around often in tech circles, but it’s rarely defined clearly. He offered a straightforward explanation:
First-principles reasoning means starting from what is invariant – the parts that never change – and building your understanding from there.
Invariants are the fundamental laws of reality – things like gravity, light, or the rising and setting of the sun. They remain constant, no matter what tools we create.
Returning to the Renaissance analogy, Kumar explained that both painters and cameras are simply different ways of capturing the same invariant: light. The tools change, but the underlying truth stays the same.
This approach, he argued, helps us understand the deep value of AI.
The goal isn’t to cling to the tools we’ve always used but to identify the underlying invariant that AI supports. In this case, it is reclaiming time and human agency – giving developers the freedom to focus on meaning while delegating repetitive work to machines.
The invariant in AI? It gives us back lost time
The point became unmistakable when Tejas demonstrated a multi-step AI agent in real time. Without typing a single keystroke, he watched as the agent opened Chrome, searched for the event schedule, parsed the results, and added the correct session to his calendar.
While my hands were off, what could I have been doing? I could’ve been at the gym. Out on a run. Playing with children I don’t have yet – but pray for every day. I could have been doing something meaningful. Instead, I’ve outsourced this tedious work to my agent- and in return, I get back life.
AI does not simply automate tasks. It returns lost hours and makes room for creativity, rest, curiosity, and focus. That, he argued, is the true invariant AI addresses.

Breakthroughs don’t need new toys – they need new tricks
As the keynote wrapped, Kumar recounted the telescope’s origins. In 1608, Dutch glassmakers used clear spyglasses horizontally to scan the horizon. A year later, Galileo pointed the same tool upward, unlocking new worlds.
“He literally saw Jupiter. He saw Saturn,” Tejas said. “A tool used differently became the telescope we know today.”
This story illustrates a timeless lesson: transformative breakthroughs often come not from inventing new tools, but from using existing ones in unexpected ways. In today’s era of open-source models, MCP servers, frameworks like LangFlow, and an unprecedented supply of freely accessible AI technologies, Kumar posed a question to developers that was simple, but profound:
How are we using these tools and how might we use them differently to achieve more, or even discover entirely new possibilities?
In the age of AI you need to be CREATIVE
Tejas invited developers to embrace the moment rather than fear it. Never before have engineers had access to such a vast array of powerful open-source tools. LangFlow itself, he reminded the audience, is fully MIT-licensed and easy to self-host, letting anyone build scalable agents through a visual interface.
But his message went beyond tools or licenses. It was a call to creativity, a call to agency – a reminder for developers to lift their gaze, imagine new possibilities, and see where these tools can take us when used in unexpected ways.



