AI Agents: Will Authenticity Beat Hype
Grant Lee, co-founder of Gamma, recently took to LinkedIn to profile Morris Chang, a founder who only a few years ago — according to the usual metrics — should have been contemplating retirement.
Instead, he changed the world.
As Grant explained, Chang, after being passed over for a promotion at age 55, decided to take his 30 years of semiconductor experience back to Taiwan and launch his own company. That company became TSMC, the microchip giant that Grants says is now valued at $700 billion and serves as “the invisible foundation of our entire digital world.”
I was one of several hundred people who commented on Grant’s LinkedIn post. I thanked him for highlighting an often-overlooked truth: innovation and success have little to do with age.
I wrote: “Morris Chang’s story is a powerful reminder that experience can be a superpower, not a liability. His story flips the script on the ‘young tech genius’ myth we’re so often sold.”
Chang’s bio also reminds us about the value of experience in today’s youth-obsessed culture, while speaking to the need to separate hype from authenticity.
One area where I now see the hype in action is the skyrocketing rise of AI agents.
As we know, AI is now all the rage. According to a recent Boston Consulting Group survey, more than 70 percent of Chief Marketing Officers use AI for content creation, personalization and segmentation. AI also dominates software development. My industry, financial services — which is highly regulated, data-dependent and reliant on workflows — also embraces AI to automate its compliance, risk management and trading needs.
Slick Demos and Bold Claims
With the world’s growing dependency on AI, it’s only natural to fast-track agents that quickly deploy tools that meet the immediate needs of an industry. But, for me, AI agents — artificial intelligence software designed to complete tasks with minimal human oversight — serve as the type of technology that could be at risk of being hijacked by the sort of flashy disruption Grant Lee addressed in his LinkedIn post.
AI agents are popping up everywhere, promising to revolutionize businesses with slick demos and bold claims, and venture capital is pouring in, chasing the next big thing. But it’s worth remembering that Morris Chang’s success came from decades of pattern recognition and deep industry context.
Think about TSMC: Chang’s expertise didn’t hinge on flash. It was honed by years of seeing what others missed. Similarly, the most useful AI agents, at least those deployed in financial services, must quickly comb through and draw on unglamorous but critical stuff — messy data, strict legal frameworks — while delivering results that don’t crash billion-dollar systems. These agents won’t succeed because of hype; they will succeed because of grit.
“And while venture capitalists chase the next big chatbots, it’s worth remembering that most successful founders are older than the average 30-year-old tech wunderkind. ”
Founders who understand financial services are building AI agents that can help reshape how money moves, automate auditing and detect fraud in real time. In other words, they won’t be sexy apps; they will be tools capable of reshaping the backbone of a multi-trillion-dollar industry. Like Chang, their real value will come from builders with hands-on experience who understand their industry’s pain points and how to solve them.
The most successful AI agents in finance will have to understand GDPR, SEC rules and AML laws even while they streamline workflows. That’s a much higher bar to clear than slapping together an AI chatbot. So, where will the best AI agents in financial services come from? Perhaps they will come from Silicon Valley’s startup garages, but it’s just as likely that they will emerge from the cubicles of Wall Street or London’s financial district.
Thankfully, the financial services industry has the cash to fund serious R&D, attracting talent that’s battle-tested, not just buzzword-savvy.
The parallel to Chang is striking: his “old age” proved to be an asset because he’d seen enough to spot gaps in the semiconductor industry. The AI agents that will best serve the financial sector similarly must bypass the hype and, instead, deliver substance that reflects decades of industry expertise.
While VCs fawn over the next 20-year-old wunderkind, the real game-changers are likely to emerge from the world of ledgers and regulations to help build AI agents that serve as the TSMCs of tomorrow.
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