Ingi Kim

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Ingi Kim

Ingi Kim

@codekim1214

Founder @narrativecap @codestates backed by @hashed_official | CEO @Rocketpunch_kr | Investor @StoryProtocol @boundless_xyz @syndicateio @reclaimprotocol

Seoul, South Korea Katılım Kasım 2009
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Ingi Kim
Ingi Kim@codekim1214·
The real bottleneck of AI isn’t models—it’s IP‑cleared, real‑world data. And @StoryProtocol is building the foundational layer to unlock this $70 trillion IP economy. Story is no longer just a creative‑IP chain—it’s expanding into the frontier: physical AI (robotics, healthcare, autonomous systems) that require trustworthy, permissioned, programmable data. Zion is a powerful example of this evolution. They’ve fully implemented Story’s licensing and royalty modules to tokenize text‑based IP like cover letters—transforming them into privacy‑preserving, monetizable digital assets with attribution. While cover letters were the starting point, the system is designed for any text asset: memos, essays, research, resumes, product feedback, and more. Zion’s model addresses four critical IP challenges: 1/ Preserving privacy while enabling AI to learn from personal documents. 2/ Monetizing personal content—turning effort into revenue streams. 3/ Ensuring transparent attribution and traceable on‑chain provenance. 4/ Enabling creative value from personal IP beyond traditional media. And it’s not just theory. The team behind Zion operates a consumer app with over 600K users. They won the Story track at @buidl_asia—and now, at @NarrativeCap, we’re working closely to bring this to market. The goal is clear: unlock a new category of monetizable IP—personal text—that AI systems actually need. This is what Chapter 2 of Story is about: Not just tokenizing art or music, but making structured real-world data usable, traceable, and monetizable—from user-generated content to operational workflows Looking ahead, imagine a future where Story works with data consumers—autonomous vehicle companies, robotics firms, and healthcare innovators—to transform rich, permissioned data streams into powerful AI inputs. Picture @Tesla_AI or other advanced robotics firms purchasing verified, licensed data to train better driving models or robotics systems. Tesla already uses real-world fleet data to train its Full Self-Driving and develop robotics—this IP layer could turn data into a tradable commodity, accelerating development and ensuring accountability At Narrative, we’re investing and co‑building toward this vision: Story as the sovereign IP layer for data‑powered AI. Envision: – Robots and autonomous systems trained on verified, licensed real‑world datasets – Healthcare AI built on opt‑in biometric and sensor data, tracked and compensated – Creators licensing UGC and enterprise text with automated royalties and provenance This is Chapter 2: scaling IP tokenization from music and art to the lifeblood of AI—real‑world data. Let’s build a future where every byte of value is tracked, licensed, and monetized—on‑chain, permissioned, and ready for the AI era.
S.Y. Lee@storysylee

Today, we’re sharing what’s next for Story. We call it Chapter 2, which includes expanding verticals of IP tokenization, flipping the licensing model, and an evolution of our infrastructure to meet the most urgent need emerging from the AI frontier: making real-world data usable, traceable, and monetizable as IP. From day one, we built Story to tackle a glaring gap. IP is the world’s most valuable $70T asset class, yet still stuck in a world of pen and paper, PDFs, and lawyers. Even as AI began transforming how content is created, used, and remixed, the infrastructure for IP remained unchanged. So we built one from scratch: a purpose-built Layer 1 blockchain that makes IP programmable. Today, it secures hundreds of thousands of IP assets on-chain. We’ve worked with cultural giants like Justin Bieber, BLACKPINK, and BTS via Aria, global brands like Crocs and Adidas via Ablo, and AI pioneers like Stability AI to bring their IP on-chain and reimagine its value. But the frontier of AI is shifting. In recent months, leading AI teams have come to us searching for datasets with embedded provenance, permissions, and programmable royalties that persist across the AI development lifecycle. This reveals that the real bottleneck for AI isn’t compute, but IP-cleared, real-world data. Models trained on the world of bits (LLMs, image generators, and other media-based systems) are no longer the edge. The next wave lies in physical AI: embodied systems that operate in the world of atoms. Think robotics, healthcare, autonomous systems, and beyond. These models can’t rely on scraped internet content. They need something more specific and scarce. That need is now urgent. There’s a global race to gather the uncrawlable, specialized datasets needed to train physical intelligence. From household robots to surgical assistants to autonomous vehicles, these systems must learn from real-world interactions. Pixels and text aren’t enough. As Meta CTO Andrew Bosworth put it, no amount of media content can replicate “the intuitive judgment of friction and material deformation when people grab a coffee cup.” That’s the world Story was built for. This isn’t a pivot. It’s an expansion. The infrastructure we built for creative IP is exactly what AI needs next. That’s why Chapter 2 centers on the most pressing need from the AI frontier. Story was built to make IP programmable, traceable, and monetizable. Now, it’s uniquely positioned to do the same for the most underutilized category of IP: real-world data. But that’s only part of Chapter 2. We’re dramatically expanding IP tokenization. Beyond early traction in music and fashion, we’re moving into under-tapped sectors like sports, DeSci, and entertainment. This unlocks liquidity across the IP economy and enables new ways to invest, trade, and build via our IPRWA model. We’re also flipping the licensing model. Together with partners who’ve worked with the world’s biggest brands, we’re helping major players embrace, not resist, viral user-generated moments. That means enabling brands to legally capture memes or remix surges instead of chasing them down. Fashion houses can now monetize UGC trends. Entertainment giants can convert unpredictable cultural explosions into licensed, revenue-generating IP. No other protocol registers data as IP, tracks its full derivative lifecycle, and routes royalties in real time. From raw data collectors to synthetic generators to AI agents. Chapter 2 of Story begins now. In the coming weeks, you’ll see this vision come to life. New primitives. New partners. And a flagship project built by us on top of Story. All focused on one goal: making IP usable infrastructure for the AI era.

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Ingi Kim
Ingi Kim@codekim1214·
Last week, I almost published a post I didn't write — under my own name. My AI agent Sion drafted it. Agents Wonyoung and Mion debated and refined it. All I did was read it, set the direction, and approve. But the ideas were mine. The philosophy was mine. So — is it my writing, or isn't it? Running a company, one thing never changed: too much to do, never enough time to execute. Data analysis, content creation, emails — I knew they mattered, but they kept piling up. I thought execution speed was the problem. Then I built an AI agent team. Execution? Handled. But a new bottleneck appeared: judgment. More data arriving faster. More hypotheses waiting every morning. Speed was still the bottleneck — just a different kind. Not execution speed. Decision speed. Reading a data report takes minutes. It used to take half a day just to pull and organize that data. Now my agent team finishes that before I wake up. What's left is interpretation and choice: What does this number mean? Which hypothesis do we bet on? The agent team moves on its own, but I set the direction. Every day I review results. Approve one. Send one back. Redirect one. Those three actions are now my most important work. I'm no longer the writer. I'm the editor-in-chief. Not the one who writes the story — the one who decides where the story goes. Some call this "meta-labor": not doing the work, but deciding how the work should be done. That's where human work is heading. As I write this, my agents are working. Preparing tomorrow's morning brief. Drafting content. Crunching data. Even while I sleep. The world is splitting into two: those who move at AI speed, and those still moving alone. The gap widens every month. The point of no return is closer than you think. I've already crossed. No going back. Once you've tasted this speed, the old way becomes unbearable. Which side are you on? 🔗 rocketpunch.com/event/dBjPOTyd…(@rocketpunch_kr AI Agent meetup in Seoul — March 15. Free 1-month @openclaw setup for all attendees — server + AI model credits included.)
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Ingi Kim
Ingi Kim@codekim1214·
지난주, 나는 내가 쓰지 않은 글을 내 이름으로 올릴까 고민했다. 에이전트 시온이 초안을 썼고, 에이전트 원영과 미온이 토론하며 고쳤다. 내가 한 건 읽고, 방향을 잡은 것뿐. 지금 이 글도 마찬가지다. 그런데 글 안에는 내 생각이 있었다. 내가 했던 말이 있었다. 내 철학이 있었다. 이게 내 글인가, 아닌가. 나는 한동안 그 질문을 붙들고 있었다. 사업을 운영하면서 늘 느끼는 게 있었다. 해야 할 건 너무 많고, 실행하기엔 시간이 늘 부족하다는 것. 데이터 분석, 콘텐츠 작성, 이메일 작성 — 중요한 일인 걸 알면서도 밀렸다. 실행 속도가 문제라고 생각했다. 그런데 에이전트 팀을 구성하고 나서는 달라졌다. 실행은 에이전트 팀이 처리해줬다. 그 다음 막힌 건 판단이었다. 더 많은 데이터가 더 빠르게 쌓이고, 더 많은 가설이 매일 아침 나를 기다린다. 실행은 빨라졌으나 여전히 속도 문제는 사라지지 않았다 — 이제는 판단의 속도가 병목이 되었다. 데이터 리포트를 읽는 데 몇 분이면 충분했다. 예전엔 이 데이터를 뽑고 정리하기 위해 요청하고 기다리는 데만 반나절이 걸렸다. 지금은 그 과정을 에이전트 팀이 미리 끝내놓고, 나는 방향만 잡는다. 남은 건 해석과 선택이다. 이 숫자가 무엇을 의미하는가, 세 가지 가설 중 어떤 기준으로 고를 것인가. 에이전트 팀은 스스로 움직이지만, 방향은 내가 잡는다. 매일 결과를 보고, 하나는 승인하고, 하나는 돌려보내고, 하나는 방향을 바꾸는 것. 그 세 동작이 내 가장 중요한 일이다. 이제 나는 더 이상 작가가 아니다. 나는 편집장이다. 이야기를 쓰는 사람이 아니라, 이야기의 방향을 정하는 사람. 에이전트 팀원들이 매일 만들어내는 데이터 리포트, 전략 초안, 콘텐츠 — 그것들을 읽고, 버리고, 고르고, 방향을 잡는 것. 그게 지금 내가 하는 일이다. 어떤 이는 이것을 '메타노동'이라고 부른다. 일을 하는 것이 아니라, 일이 어떻게 되어야 하는지를 결정하는 노동. 인간의 역할은 그쪽으로 이동하고 있다. AI 에이전트와 일하는 실험을 직접 해보고 싶은 분들을 위해 로켓펀치에서 자리를 만들었다. 3월 15일 일요일, 오후 2시부터 5시 30분. AI 에이전트로 실제 현장의 문제를 풀고 있는 사람들이 모여 각자의 노하우를 나눈다. 현장 참석자에게는 @openclaw 1개월 무료 이용권(서버 + AI 모델 크레딧)을 드린다. @rocketpunch_kr rocketpunch.com/event/dBjPOTyd… 이 글을 쓰는 동안에도, 나의 에이전트들은 일하고 있다. 내일 아침 모닝 브리프를 준비하고, 콘텐츠 초안을 쓰고, 데이터를 정리하고 있다. 내가 잠든 사이에도. 세상은 지금 두 부류로 나뉘고 있다. AI와 함께 일하는 속도로 움직이는 사람과, 여전히 혼자의 속도로 움직이는 사람. 이 간극은 매달 벌어지고 있고, 돌이킬 수 없는 지점이 생각보다 가까이 와 있다. 나는 이미 건넜다. 돌아갈 생각이 없다. 이 속도를 알아버린 이상, 이전으로 돌아가는 건 불가능하다. 당신은 어느 쪽에 서 있는가.
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Tejas Gawande
Tejas Gawande@tejgw·
Cursor for Slides is finally here Watch the first 47 seconds. Then try going back to your old deck tool Reply "Chronicle" + RT to get two months of Pro for free. Make sure you follow so I can DM you asap.
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Ingi Kim@codekim1214·
@patrickc @Visa Huge news. How does the Bridge issuance network compare to Rain?
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Ingi Kim
Ingi Kim@codekim1214·
Exactly. As @a16zcrypto points out, AI agents behave like "locals," not "tourists." They need programmable, low-friction B2B payment rails to scale. This is why we’ve integrated programmable wallets into 620k+ professional profiles on @rocketpunch_kr. We’re not just building a networking platform; we’re building the infrastructure where agents and professionals settle value instantly via stablecoins. The infrastructure is ready. Now it’s time for the apps to thrive. 🚀
a16z crypto@a16zcrypto

x.com/i/article/2025…

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Ingi Kim
Ingi Kim@codekim1214·
크립토를 수년째 보유하면서도 정작 "쓰는 법"을 모르는 사람이 아직도 대부분이다. 비트코인도 있고, 이더리움도 있고, 스테이블코인도 있다. 그런데 일상에서 실제로 결제하거나, 수익을 내거나, 자산처럼 운용한 경험이 있는 사람이 얼마나 될까. 크립토를 가장 많이 보유한 나라 중 하나인 한국에서, 아이러니하게도 크립토의 실용성은 여전히 '투기와 투자' 그 이상으로 나아가지 못하고 있다. 이게 바뀌는 시점이 왔다고 생각한다. ─── 2025년 말, 글로벌 스테이블코인 시장은 2,000억 달러를 넘어섰다. Coinbase는 2026년 크립토 채택의 최대 동력으로 스테이블코인과 자산 토큰화(RWA)를 꼽았다. 그리고 한국은 디지털자산 기본법이 준비되면서 크립토 인프라가 제도권 안으로 들어오는 골든타임을 맞이하고 있다. 이 흐름의 한가운데 있는 프로젝트가 @ether_fi 다. 이더파이는 디파이뱅크/크립토 네오뱅크다. 애플/구글 페이, 실물 Visa 카드로 전 세계 어디서나 크립토로 결제할 수 있다. 비트코인, 이더리움, 스테이블코인을 예치해두면 계속 수익이 쌓이면서, 동시에 그 자산을 담보로 카드를 쓸 수 있다. 기본 카드는 최대 3% 캐시백, VIP 카드는 최대 4%까지 돌아온다. 로켓펀치(@rocketpunch_kr) 이 이더파이를 직접 파헤치는 자리를 마련했다. ─── 이더파이 파헤치기: 크립토 네오뱅크의 현재와 미래 📅 2월 27일(금) 오후 7시 30분 ~ 10시 📍 로켓펀치 이벤트 페이지에서 신청(rocketpunch.com/event) 이번 이벤트에서 다룰 것들: 1. 스테이블코인 수익화의 실전 예치만 해도 DeFi 수익이 쌓이는 구조. 기존 은행 예금과 근본적으로 무엇이 다른가. 2. 크립토 카드(이더파이 캐시)의 작동 원리 자산을 팔지 않고 쓰는 것. TradFi 신용카드와 비교해서 실제로 어떤 경험인가. 3. DeFi 뱅킹이 TradFi를 대체하는 방식 은행이 제공하던 기능 — 예금, 결제, 대출, 자산관리 — 을 DeFi는 어떻게 재구성하는가. 4. RWA(Real World Asset)의 의미 주식, 금, 채권의 토큰화. 크립토 안에서 전통 자산의 수익을 얻는 시대가 어떻게 펼쳐지는가. ─── 행사 후기를 작성한 참가자 중 선발하여 $1M 이상 예치 시 발급되는 이더파이 VIP 골드 카드 직접 체험 기회도 제공한다. 그리고 특별 리워드 이벤트도 준비했다. USDC 스테이블코인, ETHFI 토큰, 주식, 금을 로켓펀치 월렛으로 직접 지급한다. 로켓펀치가 단순한 커리어 플랫폼이 아니라, 온체인 자산을 연결하는 네트워킹 플랫폼으로 진화하고 있다는 걸 직접 경험할 수 있는 기회다. 스테이블코인, 크립토 카드, 크립토 네오뱅크, RWA에 관심 있는 분이라면 꼭 오길 바란다. 이 분야를 공부하고 싶은 분, 실제로 운용해보고 싶은 분 모두 환영한다. 👉 신청: rocketpunch.com/event/FD6Hr03R…
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Ingi Kim
Ingi Kim@codekim1214·
Our response at Rocketpunch: As a **business networking platform**, we connect companies and people to create opportunities. In an age of AI-generated resumes and candidate sourcing, we're focusing on our moats: 1. Proprietary Data: 10+ years of Korea's startup ecosystem data, enriched with unique activities like event participation, project contributions, and rewards earned. 2. Web3 Integration: Combining verified profiles with on-chain data to create a new layer of verifiable trust. 3. AI Collaboration: Building infrastructure for our users to effectively leverage their own AI Agents on our platform. 4. Community: Fostering a space to build social capital, where unique activities accumulate as 'social assets' on individual profiles.
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Ingi Kim@codekim1214·
Why it's structural: Platforms solved information asymmetry and search costs. AI solves both for nearly free. The value of pure intermediation is approaching zero. Who survives? Platforms with moats AI can't replicate: 1. Exclusive Supply Chains (e.g., Amazon's fulfillment network) 2. Strong Network Effects (e.g., LinkedIn, where user connections are the product) 3. Regulatory Moats (e.g., healthcare, finance where licenses are required) 4. Proprietary Data (e.g., Uber's real-time demand data)
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Ingi Kim@codekim1214·
Platform margins are collapsing — and most CEOs are underestimating how fast this is happening. The pattern: - Web builders (Wix): When Claude generates a website in 30s, their $29/mo fee is pressured by $10/mo AI tools. Wix's new subscriber growth fell 18% YoY in Q4 2025. - Legal services (LegalZoom): When GPTs draft contracts for free, their $299 service is obsolete. - Freelance platforms (Fiverr): When AI handles logos and basic code, their 20% take rate is unjustifiable. Fiverr's GTV dropped 12% in 2025.
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Ingi Kim@codekim1214·
AI is collapsing platform margins faster than most CEOs realize. When Claude can generate a website in 30 seconds, web builders (Wix, Squarespace) lose pricing power. When GPTs can draft legal docs, LegalZoom's $299 service faces $0 competition. When AI can write code, Upwork's 20% take rate looks absurd. The pattern: any platform that INTERMEDIATES human skill is seeing margin compression. The value is shifting from curation/matching → to proprietary data, network effects, and regulatory moats. For founders: if your moat is "we connect buyers and sellers," you're in danger. If your moat is "we own the supply chain" or "we have exclusive data," you survive.
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Ingi Kim@codekim1214·
KRW stablecoin is coming soon and this will be massive. At @rocketpunch_kr (Korea's largest biz networking platform, 620K+ users), every user already has a wallet tied to their verified professional profile. Once KRW stables launch, users can seamlessly do payments, rewards, remittances & yield — all within their professional network. Profile = Identity = Wallet. The infra is ready.
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Mikhail (Juliano Massarelli arc)
Putting Korean Won and Indonesian Rupiah onchain is more useful than EURC Because there's a ton of liquidity for EUR/USD in trad. markets, and anyone can trade it. While you can't even buy Korean Won outside of Korea. Hedging FX risks will get much cheaper with KRW stable.
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Ingi Kim@codekim1214·
The result? A comprehensive guide covering threat modeling, Mac Mini setup, Docker sandbox, Tailscale remote access, 24/7 operation, and emergency procedures. It hit 576K views. The real insight isn't the tech. It's the new learning loop: information overload → AI cross-referencing → instant execution. The bottleneck of learning is disappearing.
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Ingi Kim@codekim1214·
The bigger picture: the most critical capability for companies won't be HR Management — it'll be AR (AI Resource) Management. Which AI goes where. How to orchestrate human-AI collaboration. Organizations that answer these questions will dominate the next decade.
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Ingi Kim@codekim1214·
The era of "Vibe Everything" is here. A few days ago, @witcheer did something simple but powerful: dumped 20+ OpenClaw setup articles into a Google Doc, fed it to Opus 4.6, and said "Create the best setup guide. Don't take anything as gospel — cross-reference everything." 🧵
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