This video provides deep insights into the true meaning of "AI-native" and the present and future of enterprise AI through an interview with Wonjun Jang, co-founder of Man Of and a hands-on VC. AI-native goes beyond simply building good AI products -- it refers to a philosophical difference where AI is treated as a foundational premise in the organization's DNA and decision-making processes, which he emphasizes will significantly impact a company's growth velocity. He analyzes that in the Korean market specifically, AI-native startups have a higher chance of capturing markets faster than existing incumbents, and presents concrete methodologies for maximizing team productivity through the practical use of meeting transcripts and context data.

1. Introduction to Co-founder Wonjun Jang and His Investment Focus

Co-founder Wonjun Jang introduces himself as a venture capitalist who runs the Romantic Investment Partners blog. He originally graduated with a degree in industrial engineering and developed a deep interest in productivity while working as a planner at IT startups. Based on this background, he has primarily invested in B2B SaaS, particularly enterprise solutions that help companies improve their sales operations. He explains that this category hasn't been fully activated in the Korean market yet, so he's focused on discovering and investing in companies that are pioneering new markets or taking on bigger challenges. He notes that while the Korean B2B SaaS market is logically sound, the cycle hadn't arrived for various reasons, while acknowledging that individual companies had succeeded on their own.

2. The Start of an AI-Native Company: Why They Adopted Fireflies

Co-founder Jang shares his experience adopting Fireflies, which received significant attention through a recent LinkedIn post. When building a new team, he set the goal of "actively using AI without any legacy," and the first decision in that process was "don't build it in-house -- just pay someone else," leading to the adoption of Fireflies. He explains that while he initially thought this was just a team-level issue, he eventually realized it was a decision-making flow that all teams with similar goals would eventually go through, which is why he shared it publicly.

3. The Fireflies Service and Reasons for Choosing It

3.1. What Is Fireflies?

Fireflies is an AI notetaker service that records Zoom meetings and conversations via app, transcribes the content, and then summarizes it -- functioning like a secretary or intern. He describes it as working like a YouTube summary service such as Lilys AI, but across all voice-related meetings.

3.2. Competitive Services and What Sets Fireflies Apart

The AI notetaker market includes various competitors like Naver Clova Note, Tiro, TLDL, and Granola. Co-founder Jang identifies openness and extensibility as the key reasons for choosing Fireflies. He says everyone interested in AI works with the mindset that "big changes are expected, but this change isn't the end. What we have now isn't the fixed state." In the past, there was a belief that choosing a good product like Slack and using it diligently would pay off long-term, but now the standards for what makes a good product keep shifting and breaking new ground.

He describes the uncertainty: "I want to solve this problem right now, but I'm not sure I'll always solve it this way." In this context, he emphasizes the importance of data sovereignty and flexibility in information utilization. He chose Fireflies because its API-centric, open design provides an infrastructure for retrieving, reusing, and tuning data. In other words, it was extensible beyond simple consumption into an infrastructure for retrieving, reusing, and tuning data.

3.3. The Importance of Open Operations

Co-founder Jang says he has a vision that this open operational approach could become a superior tool in the AI era. While he frames this primarily as a user-side need rather than an investor's perspective, extending it to an investor viewpoint reveals that light users prefer tailored products while heavy users worry about extensibility, which inevitably leads to open services. He adds, "To see whether a company is trying to work productively, you'll likely look at whether they're using open services or not," suggesting that open service adoption could become an indicator of a company's productivity orientation.

4. Defining and Characterizing AI-Native Companies

4.1. The Difference Between AI-Native and AI Products

Co-founder Jang defines AI-native on a different dimension from "having good AI products." For him, AI-native is about "what the company's DNA is like" -- a philosophical difference in how the company operates internally. He believes this philosophical difference will create different growth velocities for future companies. In contrast, AI products from companies like Adobe or Figma are a question of "how you think about them as AI products" -- something to be evaluated on a product-by-product basis. He adds that while Adobe is not an AI-native product, Figma could be considered one.

4.2. How AI-Native Companies Work

An AI-native company is a team where people who believe problems can be solved through AI congregate in succession. Co-founder Jang explains that the underlying confidence of people who are immersed in AI technology and believe in its potential is so radical that they think, "Even when we hire someone to solve a problem, if we give them the right inputs, the output is my fault. I can control it." The difference between someone who tries to solve problems through people and someone who constantly considers whether problems can be solved through AI is what makes a company AI-native. He emphasizes that the more you research and learn about AI, the more immersive and captivating it becomes, with more upside becoming visible.

5. Vertical Winners vs. AI-Native Challengers: Opportunities in the Korean Market

Co-founder Jang addresses the question of whether established vertical winners with deep moats can transition to AI, or whether AI-native startups starting from scratch can capture those verticals. While he admits it gets confusing with big tech companies, he asserts that for Korean companies at least, the latter (AI-native startups) is overwhelmingly obvious.

He points out that in the US, structures around workplace productivity challenges and the freedom to hire and fire create an environment where people can work hard, but Korea has long lacked such corporate intensity. Because employment carries a different meaning in Korean society, existing players face significant difficulties when disruptive technology arrives.

For example, if AI shopping agents become the default in e-commerce, unless you're an overwhelming player like Coupang, the positions of existing retail giants like E-Mart, Homeplus, and Lotte Mart would likely be significantly taken over by AI-native apps. He explains this is because AI technology fundamentally disrupts a company's cost structure. AI completely changes the game of capital and personnel needed to run a business -- he compares it to being the only person using a calculator while everyone else is using an abacus.

6. Practical Use of Meeting Transcripts and Context Data

Co-founder Jang shares use cases of Fireflies, which records all meetings. While his team hasn't yet reached the stage of fully leveraging it, he's discovered two important benefits:

1. Sense of security about the future: He says they gained the reassurance that "no matter what the future brings, we've captured a lot of our conversation context, so we've built the infrastructure to use new technologies."
2. Tangible productivity improvement: When answers aren't clear or points are confusing after a meeting, he feeds the meeting transcript directly into ChatGPT or Claude for discussion. He sometimes asks "Give me a fair, third-party perspective," or "Challenge me," or "Help me strengthen my logic," and describes the effect as feeling like having an additional team member.

When asked whether there's more data to collect beyond voice and meeting data, he responds, "I think the question is more about what data we should NOT collect," emphasizing the importance of data collection for an AI-native approach. He predicts that between Fireflies' approach of actively pressing record to select, and another company's approach of recording all audio by default and excluding later, the ultimate direction will be the latter -- AI-controlled exclusion. However, he adds that for current usability, selective recording is much more convenient.

7. The Present and Future of Enterprise AI

Co-founder Jang sees the current enterprise AI market as a period of "unsorted opportunity." He says there's no clear answer about what kind of AI startup will succeed right now. Some are building agents, some are building SaaS, some are building outsourcing firms -- various approaches exist.

But he emphasizes that this is precisely what makes it a tremendous opportunity. "Once there's a dominant consensus that 'this is what you should do with AI,' the moment you learn about it, you're already a latecomer." Therefore, he believes now is an excellent time to be a first mover, as long as your thesis is clear. He believes that becoming a company that uses AI well means you can do anything better, and that's where he's focusing most.

He acknowledges that this perspective might seem like an early adopter discussing Bitcoin's credibility in the early days of blockchain, but emphasizes that it's based on his genuine conviction as he wraps up the interview.

Conclusion

The interview with co-founder Jang clearly demonstrated that AI-native companies go beyond simply adopting technology -- they fundamentally reorganize their organizational philosophy and ways of working around AI. In the Korean market especially, there are structural opportunities for AI-native startups to leapfrog existing incumbents. Active data collection and AI-powered problem-solving approaches were highlighted as the core factors that will determine a company's productivity and growth. Since this is a period of "unsorted opportunity" without clear right answers, the message was that rapidly executing your own theories and approaches is crucial for becoming a first mover. The interview concluded with a strong conviction that organizations that use AI well will lead the future.