Assani

@pipat9cat Absolutely true

ถ้าคุณไปสัมภาษณ์งาน แล้วบอกว่า “ใช้ AI เป็น” อาจไม่พอแล้วในยุคนี้ สิ่งที่ตลาดต้องการ ไม่ใช่แค่ AI Literacy (รู้จักหรือรู้ว่าใช้ AI ยังไง) แต่คือ AI Fluency = ใช้ AI จนมันกลายเป็น วิธีคิด และเอาไปใช้พัฒนางานจริง จาก research ล่าสุดของ Anthropic งานที่โดน AI กระทบหนักสุดตอนนี้คือ Programmer, Customer Service, Data Entry, Financial Analyst ส่วนมากจะเป็น งานหน้าจอ + มี pattern + ทำซ้ำได้ เกมมันเลยเปลี่ยนแล้ว คนที่ได้เปรียบไม่ใช่คนที่ใช้ AI พิมพ์งานแทน แต่คือคนที่มี AI Fluency ใช้ AI แล้ว → ทำงานเร็วกว่า → สร้าง value ได้มากกว่า และที่สำคัญกว่านั้นคือ Human Skills เพราะสิ่งที่ AI ยังแทนไม่ได้จริง ๆ คือ - ตัดสินใจในสถานการณ์เสี่ยง/คลุมเครือ - ความเข้าใจคน (empathy / communication) - การตั้งโจทย์ที่ “ใช่” ตั้งแต่แรก - ความคิดสร้างสรรค์ + judgment - ความรับผิดชอบ AI Literacy = entry ticket AI Fluency = leverage + add value Human Skill = differentiation AI ทำให้ output ดีขึ้น แต่ Human skill ทำให้ direction ถูกต้อง สุดท้ายแล้ว AI ไม่ได้แย่งงานคุณ แต่คนที่ “ใช้ AI เป็น + คิดเป็น + มีHuman skill” คือคนที่รอดแน่นอน

@SaniSalisu0 Noted

Most people think Web3 rewards the smartest. That’s not always true. Web3 rewards the most visible. The ones who Share what they learn Talk about projects Show up every day

@9CATGROUP AI is no longer just smart models it’s full-stack infrastructure powering real-world impact. From agentic AI and robotics to finance, healthcare, and AI-to-AI commerce, the next race is about ecosystems, not just models.

@pipat9cat Very insightful post

AI is no longer just behind the scenes. It's becoming the scene itself. DLSS 5 = another proof point that AI-native visuals will define the next era of gaming, content, and brand experience 🎮🔥

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@pipat9cat Excited to see how builders leverage the shift

I've been thinking a lot about Jensen Huang's GTC keynote and what it means for the next decade of building. We are moving past the era of passive software. The new unit of production isn't code anymore. It's intelligence. And that intelligence needs a way to transact. Thread below

@9CATGROUP A huge congrat to tge 9cat team for such achievement Lets keep pushing forward

9 CAT Group is proud to be part of the Claude Thailand Community Meetup As AI continues to grow rapidly, local communities play an important role in turning technology into practical knowledge through real conversations, shared experiences, and collaboration. It was great to see people from different backgrounds come together to exchange ideas, explore real AI use cases, and contribute to the growing momentum of Thailand’s AI ecosystem. For 9 CAT Group, being part of spaces like this reflects what we believe in "Real ecosystem growth starts from the community" We appreciate everyone involved in making this meetup happen and look forward to seeing Thailand’s AI community continue to grow 🇹🇭

@9CATGROUP 2025 was epic with 9CAT GROUP 100+ events, 10k+ participants, $1M+ delivered! 2026, let’s go even bigger

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@pipat9cat We used AI to model token flow and KOL incentives, testing vesting schedules and price stability. Then we ran a 12-month supply-demand and treasury model. AI doesn’t replace experts but helps founders make smarter decisions before paying big money.

Instead of paying a very expensive tokenomics consultant, we used Claude to help design the tokenomics for a project. The idea was simple: Feed it the business model, the user behavior we want, and the incentives we’re trying to create. Then ask it to simulate how the token would actually flow. Who ends up holding? Who dumps? What happens under different scenarios? One case we tested was around KOL incentives. The project wanted KOLs to hold long-term instead of dumping right after TGE (which happens a lot). So we modeled different vesting structures and asked Claude to compare them. For example: If the vesting schedule is Model A vs Model B, how would KOL behavior likely change? Which one creates more stable price dynamics in the first 6 months? Then we took the output and used Manus to build a deeper financial model: looking at supply vs demand sustainability, treasury burn rate, and LP sizing over a 12-month period. AI obviously doesn’t replace a great tokenomics expert. But it’s surprisingly good at helping founders think through the system more clearly and ask better questions before paying someone a lot of money to design it. And honestly, that step alone already improves decision quality a lot.

@pipat9cat Spot on. This isn’t crypto adoption it’s banking obsolescence. AI agents can’t open bank accounts, but they can own wallets. The next billion transactions won’t be human they’ll be machines born on-chain.

Everyone's excited that AI agents will "use crypto wallets." But that framing is wrong. AI agents aren't choosing crypto because it's cool. They're choosing it because the entire banking system was designed for humans — and software doesn't have a face, a passport, or a signature. The real shift isn't "AI meets crypto." It's that the financial system built over 500 years for human identity is about to become irrelevant for the fastest-growing class of economic actors on the planet. Brian Armstrong said it plainly: AI agents can't open bank accounts. But they can own wallets. Coinbase already shipped Agentic Wallets. 0G built ERC-7857 so agents can own, trade, and evolve on-chain. Stellar is integrating x402 for machine-to-machine payments. Here's the contrarian part most people miss: This isn't a crypto adoption story. This is a banking obsolescence story. Banks won't adapt fast enough. KYC frameworks assume a human behind every account. Compliance systems require beneficial owners. None of that maps to autonomous software. Crypto isn't winning because it's better money. It's winning because it's the only money that doesn't ask "who are you?" For builders: stop thinking about "AI + crypto" as a category. Start thinking about it as the default economic infrastructure for non-human actors. The next billion transactions won't come from people downloading wallets. They'll come from agents that were born with one.