Building Real-World AI Fluency
What’s the most important skill in entrepreneurship right now? Luciano Casale ’27 believes it’s AI literacy. Last fall, the psychology major and finance minor from Los Gatos, Calif., launched Start@AI: Build Your Toolkit—and it’s already making a major impact.
Casale conceived the series to help demystify AI. Held at the Shea Center for Entrepreneurship, the 75-minute workshops blend student-run dialogue with guest speakers from BC faculty, alumni groups, and private industry. Students in any major or year are invited. The only prerequisite: A deep curiosity about AI.
Start@AI helps build AI skills that create confidence and career advantages. Each session combines chats with industry experts, hands-on skill labs, and real-world projects that instill mastery of AI tools—and put BC students ahead of the curve.
We spoke with Casale about his inspiration for the program and how it’s preparing students campuswide for AI’s unstoppable influence on the global workforce.
You're a psychology major. Did your coursework inspire the concept for Start@AI, or was it something else?
Yes, some of the coursework that influenced the genesis of Start@AI came from classes about human nature and the psychology of change on a macro level. Psychology helped me think about how humans adapt to change and why we often resist it at first.
I started to realize why there is pushback against AI and how, generationally, the people who get ahead are the ones who can outpace the curve of change in society. I wanted to help BC students get ahead of that curve so my peers and I could benefit from this shift instead of being left behind by it.
AI is massive, and it changes every few weeks. Resistance to change can be a real psychological barrier, both individually and collectively. Starting something like this felt like a way to pace that change and create a space where we could push against humanity's natural fear of it. The idea was to do that on a small scale within a cohort of students who are willing to engage with it.
AI also feels like one of those major technological swings that happens every 40 years or so, and honestly this one might even be closer to a once-in-a-century shift. When swings like that happen, you see the biggest displacement, the biggest economic and societal change, but also the biggest breakthroughs and successes.
You led a session on AI and investing last fall. How was that experience?
That session was very interesting and a lot of fun. The goal was to talk about how jobs in investing are changing with AI and what it means to become AI-fluent or AI-literate.
We focused specifically on what it means to stay ahead of the curve in investing roles like venture capital, private equity, growth equity, and investment banking. We talked about the tools that are emerging, the way investment analysis is changing, and even questions like whether there might be an AI bubble forming in the market.
We also talked about things like Citibank hiring a head of AI, which is a brand-new role. That’s a signal that the industry itself is restructuring around this technology.
How is the program preparing students for a rapidly evolving job market?
The program itself evolves rapidly. With AI, every couple of weeks there are five new things you need to understand to stay current. The speed of change means that being “up to date” is not about memorizing tools. It’s about developing a mindset that adapts quickly as things change in real time.
That’s what we try to cultivate in Start@AI. After each session, we reflect on what changed since the previous week. Then the next session would begin with, “Here is what is new. Here is what changed. Here is what matters now.”
I sit here now as a second-semester junior and look back at how I would have prepared for entering the workforce just a few months ago, and it is completely different from what I would do today. What we are really trying to cultivate is the ability to recognize change as it happens and learn the new skills that come with it in real time.
Is AI literacy about to become a requirement for entrepreneurs in every field?
Absolutely. AI literacy is one of the most important skills in entrepreneurship right now.There is not a serious entrepreneur I have met in the past year who is not fluent in AI tools in some way. People are building workflows, using OpenAI, running agents, experimenting with coding using AI, and generally integrating these systems into their day-to-day operations.
What’s interesting is that founders who traditionally would have been considered non-technical are now coding their own products. They’re using AI to learn how to code, build prototypes, and automate pieces of their companies.
“If you are up to date with AI…a week of work can feel like three months of output.”
They’re also hiring people who are already AI literate to help push those systems further. If you go to startup hubs like San Francisco, this mindset is everywhere. The companies that really understand these tools are moving at a pace that honestly feels five or six times faster than startups were moving just a year ago. If you are up to date with AI and know how to use it properly, a week of work can feel like three months of output.
What makes the Start@AI program different?
Its ability to adapt to a technology that’s beginning to influence nearly every part of our lives. We’re living in a time where the rate of that change is exponential, and any program that teaches it needs to match that pace.
One thing that helped was our open discussion format. We talked about AI safety, its role in medicine, and how it could influence governments, banking systems, cities, and even space exploration. These were big conversations that forced us to think about what the next 10, 20, 30, or 40 years of human development could look like. Those discussions sparked insight and inspiration and pushed people to think about how they could contribute positively to that future.
Another important part of the program was how hands-on it was. Many sessions involved me opening my laptop, sharing my screen, and showing the actual workflows I use with AI. I would show exactly how I prompt systems, structure problems, and approach research. Then everyone would open their laptops and try it themselves.
“I would present a problem…then give everyone 15 minutes to solve it using AI.”
Sometimes I would give everyone a scenario like a business war room. I would present a problem, explain the outcome we needed, and then give everyone 15 minutes to solve it using AI. Often the task was something that traditionally might take a consulting team weeks or even months to figure out.
Afterward we would regroup, compare approaches, and I would walk through how I solved it as well. That structure made the sessions feel very real and very practical.
How are students applying AI—projects, workflows, internships—and what exactly is in an AI toolkit?
An AI toolkit can vary a lot depending on the individual. The best way to think about it today is that people build different AI systems or agents that each serve a specific role. For example, someone might have an organizational AI that helps manage their schedule, organize projects, and prioritize tasks. Someone else might have a more visionary AI that understands their goals and helps them think through larger ideas and long-term plans.
Those types of systems are fairly universal, but beyond that toolkits become very personal. If you are working in finance, one of your main tools might be AI integrated into Excel or financial modeling tools that make analysis dramatically faster. If you are an entrepreneur like I am, your toolkit might involve many different AI instances doing different things.
For me personally, I often run multiple coding agents at the same time that work within the same codebase. They reference a shared file that contains the vision of the product, safety protocols, and progress updates. When one finishes a task it reports back to that central file, so the others understand what has already been completed. Alongside those systems I also use AI as a strategic partner to help think through business ideas and product specifications.
Is participation in the program growing, and if so, what do you attribute that to?
Yes, participation grew a lot. In the first week there were about five people helping run the group and around 20 students attending the session. By the end of the semester, we had roughly 50 people attending talks and about 120 students in the group chat.
That kind of growth was pretty amazing, especially considering the meetings were every Wednesday night at 8 PM, which is not exactly the most convenient time for college students.
People kept showing up because they genuinely wanted to learn and participate. One of the sessions even ran about 40 minutes over because everyone was so engaged in the discussion about what the world might look like in 20 or 30 years with AI. Moments like that made it feel like we were doing something meaningful and helping students think about their future in a new way.
“Everyone knows AI is important, but many students do not know where to start.”
I think the growth came partly from the moment we are in right now. Everyone knows AI is important, but many students do not know where to start. We leaned directly into that. We framed the program as a resource that could help students become more valuable in whatever careers they wanted to pursue. Every week we were updating what we taught because AI itself was changing every week. That constant evolution made the program feel relevant.
I also want to give a lot of credit to the Shea Center for Entrepreneurship. Leaders like Kelsey Renda and Professor Doyle were extremely supportive when I first proposed the idea. They immediately understood that change was happening and that students should have a place to engage with it. That support made the program possible.
What’s in your AI toolkit?
The platforms I use most often include Claude, Cursor, Wispr Flow, Obsidian, Claude Desktop, Claude Code, Perplexity, and Gemini. Claude Desktop and Claude Code are probably the most central to my workflow right now.
I also use an open-source agentic system called OpenClaw that allows me to run autonomous agents that perform certain tasks. For example, I have an SDR agent that runs outreach and searches for sales leads automatically on a schedule. That allows me to automate parts of running a startup so I can focus more of my time on building the actual platform.
Another tool that has helped me recently is RevvTen. It helps upgrade prompts automatically. I found and created this tool myself, so I'm a tiny bit biased, but I also use it every day and notice the difference dramatically.
As an AI power user, I can speak to the workflow of being an AI power user. I often brain dump ideas using voice tools like Wispr Flow and then run that through RevvTen to structure the prompt before sending it to an AI model. RevvTen has saved 10–15 hours a week from my workflow and makes the output much stronger.
More broadly, I think the skillset around AI is shifting. Prompt engineering is still important, but the bigger skill now is learning how to coordinate multiple AI systems and build workflows where they work together effectively.
In a way it feels like a new leadership skill. These agents are powerful, but they need direction, coordination, and context to produce real value. Learning how to guide them properly is becoming an important skill in itself.