🎟️ Surf × JE Labs: Lotto is Live To celebrate @Surfdeveloper latest milestones, including the launch of US Equities Analysis and its collaboration with @BithumbOfficial, Surf and JE Labs are kicking off "Surf Lotto" for the community. 💰Win up to $3,996 in Surf annual membership 💰Share a $3,000 cash prize pool 📅 Campaign: Sep 3 – Sep 17, 2026, 24:00 （UTC+8） 🎉 Draw: Sep 18, 2026 🎟️ Join the Lotto:

JE Labs is a partner of Open AGI Builder Day this autumn. Model labs, agent builders, and investors together in Shanghai on Sept 19. We'll be there to meet teams building the next wave of agent products. See you at S Creator Week.👇

Korean companies run the most developed student ambassador ecosystem in the world. About 273 new programs open applications every month, and 44.4% of university students joined at least one last year. Foreign brands entering Korea barely touch it. We turned our research into a 3-minute video, including the Google Gemini (@GeminiApp) campus program that's worth copying. What it covers: 1/ Students apply the way they apply for jobs. Written applications, interviews, acceptance letters, cohort numbers like "13th class." The popular programs draw so many applicants that alumni publish "how I got in" guides. 2/ The motivation is employment first, fandom second. 42% join because it helps with hiring, and two-thirds say they'd feel disadvantaged without one. One student called these programs "step zero of brand fandom." 3/ Companies now run these programs as content and insight engines. Lecture-style programs dropped 23.5 points in five years. Supporters-style programs, where students create and publish, grew 13. 4/ Design one moment to be filmed. Cosmax ran its kickoff as a princess party and the Reel hit nearly 100,000 views. SK Hynix (@SKhynix) gave every ambassador a lettering cake with their name on it. LG U+ (@LGUplus )put its supporters in pink varsity jackets, and the uniform became the media. 5/ Give real work. KT hands student teams a real budget to run public campaigns from scratch. Bubble pays 10% commission on sales through personal links. And Google compiled its Korean ambassadors' work into "12 best Gemini prompts for university students" and distributed it through official channels: a public portfolio credit for the students, product proof for Google. 6/ Respect the mechanics. Publish the full activity calendar upfront, because surprise missions read as free labor. Plan around exams in mid-April and mid-June. Give real feedback on submissions, then boost the best student content as paid ads. The reviews this cohort writes decide who applies next year. Full video below 👇

Korean companies run the most developed student ambassador ecosystem in the world. About 273 new programs open applications every month, and 44.4% of university students joined at least one last year. Foreign brands entering Korea barely touch it. We turned our research into a 3-minute video, including the Google Gemini (@GeminiApp) campus program that's worth copying. What it covers: 1/ Students apply the way they apply for jobs. Written applications, interviews, acceptance letters, cohort numbers like "13th class." The popular programs draw so many applicants that alumni publish "how I got in" guides. 2/ The motivation is employment first, fandom second. 42% join because it helps with hiring, and two-thirds say they'd feel disadvantaged without one. One student called these programs "step zero of brand fandom." 3/ Companies now run these programs as content and insight engines. Lecture-style programs dropped 23.5 points in five years. Supporters-style programs, where students create and publish, grew 13. 4/ Design one moment to be filmed. Cosmax ran its kickoff as a princess party and the Reel hit nearly 100,000 views. SK Hynix (@SKhynix) gave every ambassador a lettering cake with their name on it. LG U+ (@LGUplus )put its supporters in pink varsity jackets, and the uniform became the media. 5/ Give real work. KT hands student teams a real budget to run public campaigns from scratch. Bubble pays 10% commission on sales through personal links. And Google compiled its Korean ambassadors' work into "12 best Gemini prompts for university students" and distributed it through official channels: a public portfolio credit for the students, product proof for Google. 6/ Respect the mechanics. Publish the full activity calendar upfront, because surprise missions read as free labor. Plan around exams in mid-April and mid-June. Give real feedback on submissions, then boost the best student content as paid ads. The reviews this cohort writes decide who applies next year. Full video below 👇

Most ambassador programs die right after the first round of rewards. The ones that keep growing treat ambassadors differently: not as promoters, but as co-builders. We've turned our ambassador playbook into a 3-minute video, including the full breakdown of the program we ran for Creao ( @CreaoAI ). What it covers: 1/ Selection is 80% of the outcome. Run it as a funnel: open application, community observation, then a trial period before anyone gets the title. Choose resonators, not just influencers. 2/ Ambassadors close a gap money can't: local context. One team in one country can't speak the culture of ten markets. Ambassadors already live there. 3/ Every incentive layer has a job. Base rewards set the floor, growth rewards drive activity, identity rewards build pride, and a promotion path gives people a future. 4/ Give it a rhythm. A shared task board, a monthly sync, a monthly report, and a seat in the planning room for your best people. 5/ Two playbooks that work. Bluefin ( @bluefinapp ) runs three tiers, so users level up from task-doers to co-creators. UniversalX ( @UseUniversalX ) bet on mid-tier creators instead: smaller budget, more authentic content, reach beyond what they planned. 6/ The results compound. Four months with Creao: 20+ trained ambassadors, 300+ pieces of content, 3M+ impressions, 3,000+ sign-ups, and CPM down from $160 to $15. Full video below 👇

Most event write-ups are recaps: attendance, agenda, atmosphere. They prove an event happened. They don't explain why it was built that way. A while back we wrote about the design logic behind Creao's (@CreaoAI) Demo Day in Silicon Valley, an event for content creators with one simple ask: build your own Agent workflow, on-site. We've now turned that piece into a 90-second video. What it covers: 1/ Work backwards from goals. We set three objectives first (activation, distribution, relationships) and only then picked the format. A Demo Day was the format that could carry all three at once. 2/ Design participation intensity. We used the Yerkes-Dodson curve to keep the room in the useful zone: a clear build task and light public pressure from demos and voting, plus templates, credits and on-site support to lower anxiety. 3/ Behavior has to be designed. Creators don't lack motivation. They lack ability and a prompt, so the event was built to supply both. 4/ Distribution comes from participants, not the host. The most shareable material isn't your recap. It's what attendees made themselves, so those moments are planned in advance. 5/ "The energy was great" is not an evaluation. The signal that matters is whether the workflow traveled back into real work. Full Video below 👇

Most event write-ups are recaps: attendance, agenda, atmosphere. They prove an event happened. They don't explain why it was built that way. A while back we wrote about the design logic behind Creao's (@CreaoAI) Demo Day in Silicon Valley, an event for content creators with one simple ask: build your own Agent workflow, on-site. We've now turned that piece into a 90-second video. What it covers: 1/ Work backwards from goals. We set three objectives first (activation, distribution, relationships) and only then picked the format. A Demo Day was the format that could carry all three at once. 2/ Design participation intensity. We used the Yerkes-Dodson curve to keep the room in the useful zone: a clear build task and light public pressure from demos and voting, plus templates, credits and on-site support to lower anxiety. 3/ Behavior has to be designed. Creators don't lack motivation. They lack ability and a prompt, so the event was built to supply both. 4/ Distribution comes from participants, not the host. The most shareable material isn't your recap. It's what attendees made themselves, so those moments are planned in advance. 5/ "The energy was great" is not an evaluation. The signal that matters is whether the workflow traveled back into real work. Full Video below 👇

Big step for the agent economy. FAT Protocol makes AI agents verifiable, ownable, and tradable onchain, with an open standard behind it. Live across Arbitrum, BNB, Base, and Ethereum, built with 10+ ecosystem partners, and now in Ethereum's standardization process. Congrats to the @MossAI_Official team 💚

Introducing Fungible Agent Tokens (FAT) Protocol, an open standard that turns AI agents into onchain assets anyone can verify, own, and trade. Moss is a core contributor to the standard, joined by our ecosystem partners: @AlloraLabsHQ @AlphioAI @aiseerco @arpaofficial @AiCapitalMarket @BASCAN_io @BellaProtocol @ClusterProtocol @dgrid_ai @HeyElsaAI @LLMTUNE_IO @MerlinLayer2 @numbersprotocol @QuackAI_AI @RaveDAO @SvpChain Integrated chains: @arbitrum @BNBCHAIN @base @ethereum Here's how it works👇

JE Labs was proud to partner with @CreaoAI , @googlecloud , @PingCAP , @Tiny_Fish , and @kuseHQ for an evening built around one question: how do you take AI from demo to production? One theme kept coming back throughout the panel: enterprise AI success depends on far more than model quality. Understanding customer workflows, integrating with existing systems, and tying it all to real business outcomes are now the hardest problems in the room. That's why roles like AI Field Engineers, Customer Engineers, and technical GTM are quickly becoming essential. Thanks to @CreaoAI for hosting, to our speakers for being so generous with their experience, and to everyone who joined us. Looking forward to more conversations on building AI that works in the real world 🚀

We're live on Product Hunt 🍀 WeLike: free AI marketing tools for frontier tech builders. We kept seeing the same thing at JE Labs. Teams shipping serious AI, robotics, and Web3 products were still guessing at KOL rates and tracking sentiment by scrolling X all day. So we packaged what we learned from 100+ frontier tech launches: → KOL Pricer: a fair, CPM-based rate for any X creator in 30 seconds, formula fully public → Social Listening: trending topics, sentiment, and a suggested action per topic → AI Marketer News: a daily digest picked by marketers → Smart Alerts: sentiment shifts and mention spikes, straight to Telegram → Strategy Reports: your live market data turned into a prioritized action plan Free for AI builders. No credit card. Connect X and start. Support our launch 👇

Join us on July 30th for an evening with AI builders, Field Engineers, and enterprise practitioners in the South Bay. 🚀 From AI Demo to Production: The Rise of AI Field Engineers (FDEs) As AI moves from impressive demos to real enterprise deployment, success depends on more than model quality. Learn how leading teams bridge the gap between AI capabilities and real business outcomes. Expect: 🎙 Panel discussion with leaders from @googlecloud, @PingCAP, @Tiny_Fish & @kuseHQ 💡 Practical insights on deploying AI in production 🤝 Dinner & networking with Bay Area AI builders, founders, and engineers Hosted by @CreaoAI 📍 1250 Borregas Ave, Sunnyvale at 6:30–9:30 PM If you’re building AI products, deploying AI for customers, or exploring the future of Field Engineering, we’d love to see you there. Register below 👇

Creao is expanding to Taiwan! We are now recruiting official Taiwan Ambassadors to help us grow the local AI Agent community. Beyond community building and content creation, we also hope to work with our ambassadors to explore potential partnerships with local enterprises, AI teams, and other B2B ecosystem partners in Taiwan. If you are passionate about AI Agents, community building, or business development, we would love to hear from you. Join us and help build the next chapter of Taiwan’s AI Agent ecosystem 🚀 👇 Learn more and apply in the original post.

Model Watch #1#: GPT-5.6 (Sol), for marketers We moved our whole team to GPT-5.6 Sol this week. Here's the 7-day verdict, and why it matters more to marketers than to engineers. 🧵 What Sol is? The short version: GPT-5.6 Sol (@OpenAI) finishes exactly what you spec. Give it a narrow instruction and it does that much, no detours. It's also cheaper than Fable and burns fewer tokens. Predictable means easy to trust and delegate. The one catch: hand it open-ended work and it over-reviews. Verifies before fixing, verifies after, then finds something else to inspect. The thoroughness is real, but the loop stalls actual progress. The fix is a workflow, not a prompt: • Analysis-only session first: "don't touch code, just report." • Split problems into parallel sessions • Fix sequentially, using each report as the spec Now the part we actually care about as an agency. Same shift, four marketing reads 👇 1/ Conversion comes from hands-on reviews, not spec sheets. What moved GPT-5.6 was "I used it for days" content (Lenny's, Every's Vibe Check). In KOL briefs and PR, lead with how someone's workflow changed, and let the score table sit in the appendix. 2/"Humans frame, AI executes" is your content workflow too. You own strategy, angle, tone. AI does the reps: variations, research synthesis, first drafts. Don't pile it into one session. Separate research, drafting, and polishing so it can't wander off. 3/Cheap tokens mean volume is cheap. Sol runs ~1/3 to 1/2 of Fable, output tokens down ~54%. Anyone can now pump channel variations and multilingual versions. So the differentiator moves back to the human-owned part: the angle and the insight. 4/A user-growth surge is a timing signal. Codex's single-day user growth after launch beat the prior two weeks combined. When attention floods a category, ride it: hands-on content, ambassadors, comparison reviews. "The model got better" is your best window. And build a stack, not a hero tool. We split Opus for UI, Sol for bugs. Do the same with your marketing tools: right tool per stage, humans connecting the seams.

SEO in 2026 isn't about ranking. It's about getting cited by AI. 68% of Google searches now end without a click. When an AI Overview shows up, organic CTR drops around 60%. But brands cited inside the AI answer get +35% CTR. What works now: 🔹 Front-load your answers. 44.2% of ChatGPT citations come from the first 30% of a document. Put a direct answer within 40 to 60 words, right after a question-form heading. 🔹 Drop CSR-only sites. GPTBot, ClaudeBot, and Perplexity don't run JavaScript. If your content is client-side rendered, AI search can't see it. Use SSR. 🔹 Write self-contained paragraphs. AI search splits pages into passages, so each paragraph has to make sense on its own. Keyword density is dead. 🔹 Name your brand in third person. "[Brand] does X" beats "we do X." AI has to identify the subject to cite you. 🔹 Brand mentions beat backlinks. Web mentions correlate 3x stronger with AI visibility than backlinks. 82% of AI citations come from earned media. 🔹 Go long-tail. 94.74% of keywords get 10 or fewer monthly searches. A wide set of clear-intent long-tail terms beats chasing high-volume heads. 🔹 Use hub-and-spoke. One pillar page plus 8 to 20 interlinked supporting articles beats a single 5,000-word guide. The fight isn't for page 1 of Google anymore. It's for a spot inside the AI answer.

KOL Campaign Analysis tool is on live in Welike Ran a KOL campaign and now drowning in spreadsheets trying to figure out who actually delivered? We built Campaign Snapshot so the reporting does itself. One page that turns a finished campaign into: 📊 The full picture: views, engagement, ER across every KOL 🏆 KOL rankings by what they actually produced, with every post traceable to the real account 📈 A traffic timeline showing when it spread, and the exact tweets that made it spread 🤖 Two AI reports: a campaign summary, plus a next-round strategy covering who to prioritize, what format landed, where to expand The report doesn't just close out your campaign. It becomes the brief for your next one. Stop losing half a day to campaign reporting 👇

Most event write-ups are recaps: attendance, agenda, atmosphere. They prove an event happened. They don't explain why it was built that way. We wrote about the design logic behind Creao's Demo Day in Silicon Valley, an event for content creators with one simple ask: build your own Agent workflow, on-site. A few things we worked through: 1/ Work backwards from goals. We set three objectives first (activation, distribution, relationships) and only then picked the format. A Demo Day could carry all three at once. 2/ Design participation intensity. Most events are either too passive or too demanding. We used the Yerkes-Dodson curve to keep the room in the useful zone: a clear build task, light public pressure from demos and voting, plus templates and rewards to lower anxiety. 3/ Behavior has to be designed. Creators don't lack motivation. They lack ability and a prompt. 4/ Distribution comes from participants, not the host. The most shareable material isn't your recap. It's what attendees made themselves, so those moments have to be planned in advance. 5/ "The energy was great" is not an evaluation. What matters: how many finished a working workflow, and how many were still using it a week later. Full Article below 👇