The internet has made information readily accessible to almost anyone. Access to various methods of learning has become equally accessible; anyone can open a browser and find dozens of tutorials, courses, YouTube Videos, and Reddit threads on any subject. But as American culture becomes increasingly online and attention spans are only as long as the next 30-second clip, opportunities for deep study have become scarce.
According to Gagan Biyani, co-founder of Udemy, one of the largest online learning marketplaces, the real issue is motivation. True learning requires dedicating time to studying a subject consistently over a long period of time, which is almost the opposite of what most algorithms are optimized for.
"Learning is something that doesn't happen by scrolling TikTok,” Gagan said. “You have to sit down for an hour, two hours, four hours over many weeks to really learn something. The internet has both improved access and dramatically increased the amount of distraction that prevents you from learning."
Gagan built Udemy, stepped away to travel for several years, then came back to create Maven, a platform for live, cohort-based, expert-led learning. He and GC AI founder Cecilia Ziniti met when she launched her AI courses for legal professionals on the Maven platform. She saw firsthand how Maven’s live learning format increased AI adoption for lawyers in ways that pre-recorded video sessions never quite managed.
In this conversation, CZ and Gagan explore what it takes to build two successful online education platforms, how curiosity and continued learning pay off longterm, and how a tech CEO in 2026 handles legal questions.
What Udemy Got Right, and How it Led to Maven
Gagan’s journey to build Udemy taught him a critical lesson about tech: the product-market fit almost never looks how you expect it to. Udemy's original idea was live online learning: a Zoom-like interface for instructors and students. Gagan initially had the idea in 2009 when YouTube was barely two years old and online education was still a novel concept. Gagan tried to sell his vision to potential instructors, and it did not go well.
"Our original idea was live learning online. Most people did not want to teach online at all,” Gagan recalls. “About a year in, I told my co-founder: I don't think this is going to work. We ended up switching to recorded online learning. That was probably one of the biggest decisions we made."
That pivot would also shape the next generation of ed-tech companies, and live online learning wouldn’t become a serious reality until the COVID-19 pandemic. When Gagan decided to build Maven a decade later, he started from scratch. None of the research they’d done for Udemy applied; the world had changed in almost every way that mattered.
"In 2020, I could look someone up. Every single person who is a successful professional basically has a LinkedIn presence,” Gagan said. “There are thousands of people who have built online followings via podcasting, Substack, LinkedIn, who are now deemed to be experts. That's completely new."
While Udemy was aiming to provide greater access to education, Maven’s focus was depth of knowledge. Live, cohort-based learning with a genuine expert solves the motivation problem: it puts the learning on your calendar, creates accountability to peers, and produces the kind of depth that passive consumption never will.
Note from CZ: I started teaching on Maven because I was running classes on how to use ChatGPT and realized almost immediately that it was completely inadequate for what lawyers needed. Teaching the course itself was what helped me understand GC AI’s ideal persona more deeply. The students teach you as much as you teach them. That feedback loop simply does not exist in pre-recorded formats.
The Business Case for Continuing Employee Education
Gagan argues that the business case for investing in employee AI training is clear, even if that employee won’t be around longterm. Training an existing employee to be AI-enabled can dramatically increase their productivity, and the increased value generated over the following year will justify the company’s investment many times over.
"Taking an existing employee and making them AI enabled will double or triple their productivity,” he said. “Even if you stopped that employee's work for a month, it would still be worth it."
Gagan’s actual recommendation for employee AI enablement is less intensive than you might think: two to four hour training sessions once a week for six weeks, done two or three times a year. Most executives are wary of L&D initiatives due to a lack of measurable results. Gagan argues that this isn’t a reason not to invest in AI training.
"This is the moment for L&D to step up and show that it's valuable,” he said. “You might have been burned by training that didn't work before. This is not that moment. If you adopt AI and learn it, it'll change your life for the better. If you don't, it'll change your life for the worse."
A lawyer who completes a serious AI training program does not need to wait for an annual review to show the impact of that investment; the productivity gains will be evidence enough. Gagan argues the business leaders who treat AI L&D as a meaningful investment will find their organizations much further ahead in the coming years.
Building Big: A New Way to Think About Ambition
Gagan’s advice for ambitious lawyers is a little counterintuitive: most people underestimate how big things can get, instead of how risky the attempt might be. Before he makes any big career or business decision, Gagan asks, if this works, how big can it possibly be? Once you have a sense of the idea’s ceiling, then move on to whether it has a chance of working.
“You want to be shooting for top decile outcomes at least,” Gagan said. “And that should be a binary question, not a percent question, because if you try to create an expected value, you will get the math wrong because of the exponential curve."
Note from CZ: My law school friend Brian Israel was the first lawyer at Anthropic. That was a career bet that required the kind of framing Gagan is describing: if this works, how big can it possibly be? He saw the answer clearly and acted on it. Asking ‘how big this could be’ should be a critical part of every career decision you make, not just the ones that feel risky.
And for in-house attorneys who find themselves struggling with the chaos of early startup life, Gagan recommends riding the wave. You do not have to create the wave to benefit from it. Becoming an early GC at a company that with real trajectory can produce outcomes that exceed what most founders achieve. The bet is picking the wave, not building it.
"Startups are really not that risky anymore. Most of my friends who started companies in 2008 failed,” Gagan recalls. “As far as I know, they all had amazing careers and are financially quite successful. That says everything."
How a Tech CEO Handles Legal Questions in 2026
Gagan keeps dozens of lawyers on retainer, and he still consults AI for every legal question that lands on his desk. Whether it’s a trademark dispute, a contact question, or an employment issue, he asks ChatGPT before calling his lawyer as a way to prepare for the conversation.
"Every time we have a legal or HR or trademark or tax issue, I will first ChatGPT it,” Gagan said. “But I still have a lawyer in every single one of those fields. I come into those meetings far more informed, but I still need the advice and partnership of a lawyer."
Maven’s in-house lawyers provide what an AI tool cannot: creative options, judgment about what to do, and the strategic conversation that turns information into a decision. Legal AI will never replace Maven’s lawyers, it’s simply a way for everyone to work more efficiently together. The lawyers who understand this distinction and build their legal advice around the judgment layer are the ones Gagan keeps calling.
GC AI was built to help in-house lawyers surface the knowledge quickly so they can get to the judgement calls faster. Let legal AI handle the research, drafting, and first-pass analysis so you can show up to every conversation more prepared and confident. Try GC AI for free today.
