Five Young Tech Leaders on What AI Gets Right, Gets Wrong, and What Comes Next
Last night, Tech Runs Boston returned to Venture Café Cambridge for a candid conversation on one of the biggest questions facing tech professionals today:
Will AI create more opportunity than disruption?
The answer from our panelists was surprisingly consistent:
Probably yes. But only for people willing to adapt.
Hosted by MTLC’s Tech Runs Boston series, the discussion brought together perspectives from software engineering, AI strategy, product operations, marketing, and growth.
Speakers
- Emma Harney, Director, Digital Experience & AI Strategy, Rocket Software
- Anne-Sophie Kadjo, Senior Product Operations Specialist, Flywire
- Andrew Kelly, Associate Full-Stack Software Engineer, John Hancock
- Charlie Hobson, Full-Stack Software Engineer, Capital One
- Shamsi Mumtahina Momo, Growth Engineer, AI Powered Women
Hot Take #1: AI won’t replace people. It will replace people who refuse to learn.
While opinions differed on the scale of disruption ahead, the panel largely agreed that AI is creating new roles even as it changes existing ones.
The group pointed to the emergence of AI security, model validation, AI operations, GTM engineering, and AI-enabled product roles as examples of how the workforce is already evolving.
As Emma Harney noted, previous technological shifts created entirely new industries that were difficult to predict at the time. The bigger question isn’t whether jobs will change.
It’s whether people will.
Takeaway: The winners won’t be the people who know the most AI tools. They’ll be the people who continuously adapt.
Hot Take #2: The real danger isn’t AI. It’s skill atrophy.
One of the strongest themes of the evening was the importance of maintaining core skills.
Andrew Kelly explained that he regularly uses Copilot to review and assist with code, but draws a clear line at outsourcing critical thinking and core engineering decisions.
If you don’t understand the logic behind what AI generates, you’re eventually going to hit a wall when it’s time to debug, explain, improve, or defend it.
Several panelists made similar points:
- Don’t outsource judgment.
- Don’t outsource problem definition.
- Don’t outsource curiosity.
- Don’t stop learning because AI can produce an answer.
As one panelist put it:
Use AI as a copilot, not a replacement for learning.
Hot Take #3: Builder culture has never been more accessible
The panel highlighted one of AI’s most exciting developments:
The ability for almost anyone to build.
Whether creating internal tools, experiments, automations, research workflows, or personal productivity systems, the barrier to entry has never been lower.
Momo shared how building AI-powered tools for her own academic workflow eventually became valuable beyond herself.
Charlie’s observation resonated with many attendees:
Building something is easier than ever. Building something an enterprise can safely deploy? That’s still hard.
The gap increasingly isn’t technology. It’s governance, compliance, trust, and implementation.
Hot Take #4: Curiosity is becoming a career advantage
Throughout the discussion, panelists repeatedly came back to one trait:
Curiosity.
Emma described curiosity as one of the most important qualities she looks for when hiring.
Today’s professionals have unprecedented access to information, learning resources, and AI-powered guidance. The limiting factor is no longer access.
It’s initiative. The people who ask better questions, test ideas, and keep learning will continue to stand out.
Hot Take #5: Human judgment matters more, not less
Despite working directly with AI every day, none of the panelists advocated for removing humans from decision-making.
The group discussed:
- AI hallucinations
- Security risks
- Biased outputs
- Regulatory concerns
- Privacy implications
- Overreliance on automation
Several speakers emphasized that responsible AI requires more than technical capability.
It requires humans who can challenge outputs, apply context, and recognize when something doesn’t look right.
In other words:
The more powerful AI becomes, the more valuable human judgment becomes.
Lightning Round Highlights
Most Overhyped
- AI agents everywhere
- Slapping AI onto every product without clear value
Most Underrated Opportunity
- Machine learning
- Career switching through AI-assisted learning
- Individual leverage and experimentation
Skills They’re Doubling Down On
- Security
- Cybersecurity
- Accomplishment and execution
- Continuous learning
Skills People May Be Losing
- Reading and writing
- Communication
- Confidence in technical fundamentals
- Critical thinking
Work in 2030, In One Word
- Automated
- Augmented
- Orchestration
- Daunting
- Collaborative
One Final Piece of Advice
The panel closed with a simple but powerful message:
Stay curious. Build things. Learn how the technology actually works. And don’t let AI become a substitute for thinking.
Because the future likely doesn’t belong to the people who avoid AI. It belongs to the people who know how to use it wisely.
