Ling Qing Meng

You may have never heard of MoPub. Or MAX. But they built the invisible rails of mobile advertising. @jimpayne did both. MoPub was the mobile ad exchange that wired up the smartphone internet — sold to Twitter in one of the defining ad tech exits of its era. MAX became the mediation layer that every major app publisher depends on today. Two companies. Two categories defined. And now Jim is back for a third time with @cloudx, leveraging the largest computing shift of our lifetimes -- AI. Most founders never get one of these right. Jim has done it twice — and he's not done. On Episode 31 of the @humanunicornpod, we get into the full arc: what he learned building at scale during the mobile boom, why he kept coming back, what founders consistently get wrong about timing and distribution, and what he's seeing now that makes CloudX the bet of his career. Three-time founders are a different species. This one will show you why. 🎧 Link in comments

the cheapest growth marketing strategy right now: 1. vibecode an internal AI tool 2: let it get decently good 3. give it a cool girl name (not siri, alexa, akai, river...those are taken) 4. make your org use 5. act like you weren't going to share it 6. share it anyway 7. founder x article debuting the AI tool 8. "we've been running this on 1B+ ARR" 9. act surprised by the interest 10. "fine, we'll open it up" 11. waitlist 12. early access page 13. pipeline with qualified leads 14. you replaced your entire launch gtm strategy 15. you are now an AI company let it fuckin rip

We're announcing our $50M Series B led by Benchmark. Founders Fund and Human Capital are tripling down in the round. We gave Benchmark a sneak preview of our upcoming GA release. They saw the future of sales. We had a term sheet 2 hours later. The future of sales is Monaco.

@themoe u in bkk?

@LingqingM We got a momentum Now we get to execution

Bangkok Hacker House Who's in?

Good conference looking forward 10/10 #EchelonSG2026 #EchelonSingapore

@juliusonchain sure dm me

If you’re a founder based in S/E Asia, let’s connect

@suni_code Openlucia.com

Drop your project URL 👇🏻 Let’s drive some traffic...

@askOkara Openlucia.com

drop your website and i'll ask our ai cmo how to grow it

time to finally grow my x, rabbits out of the hat boys

My general mental model is this: Agents will use cards to consume human-focused goods (retail,SaaS,etc.) and stables to consume agent focused goods (inference, data, compute,etc.) This is because stablecoins tend to be more optimized for micropayments (5 credits of niche compute) than cards.

@youfadedwealth @a16z ragebait

A very famous crypto founder told me they recently closed a $10M+ private round with @a16z I saw them spend $200K+ at E11even last night… Your series A is sponsoring BBLs, not the next Kalshi / Polymarket

@guywuolletjr 🤣

you can’t vibe code usdc you can’t openclaw hyperliquid you can’t prompt engineer morpho network effects are the moat

@quxiaoyin me

Starting a community for one person company founders who can manage at least 10 agents now and can make agents work while they sleep. Only comment “me” if you can do that. We will quiz you.

@andyyy crypto doesnt have utility. the time spent learning monad you would have advanced your career 6x faster if you just studied how to make your claude setup better

It’s crazy how so many teams in this industry who raised multiple 8-figures and had absolutely zero presence at Consensus. Sad tbh

@businessbarista AI-native

I want to start an AI community for executives. This will be a space for people to share killer use cases, agentic workflows/agents, post-AI org structure, AI governance, AI training/enablement, change management, and more. Comment “AI-native” if you want to join.

In February 2026, Atlassian raised Loom prices by up to 100x. One team's bill went from $240 a year to $24,000 a year. Overnight. No opt-in. No warning. Loom Business now costs $12.50 per user per month. Loom Business + AI is $20. A 50-person team pays up to $12,000 a year to send screen recordings. A 100-person team pays up to $24,000 a year. A 500-person team pays up to $120,000 a year. For screen recordings. Then a developer in Liverpool shipped Cap. His name is Richie McIlroy. Solo founder. Built and sold four micro-SaaS products before this one. Started Cap in November 2023, six weeks after Atlassian announced the Loom acquisition. Cap is the open source alternative to Loom. Built in Rust and Tauri. Native macOS and Windows app. AGPL-3.0 licensed. Free forever for local recording. No usage limits. No watermark. No login wall. Here is what it does: → Instant Mode: record and upload at once, shareable link the moment you stop → Studio Mode: 4K, separate screen and camera tracks, no compression, no upload → AI-generated titles, summaries, chapters, transcripts — automatic → Custom S3 storage: AWS, Cloudflare R2, Backblaze, MinIO, Wasabi → Custom domains: share from cap.yourdomain.com, not loom.com → Import your existing Loom videos in one click → Self-host everything with one Docker command Here is the wildest part: Loom hosts your videos on their servers. If Loom goes down, your links go down. If Atlassian raises prices again, you pay or your library disappears. Atlassian has killed products before. Stride. HipChat. Both were buried. Loom could be next. Cap puts your videos on YOUR storage. If Cap disappears tomorrow, your recordings still sit in your S3 bucket. Every link still works. Every video still plays. The numbers, today: 18,506 stars. 1,454 forks. 56 contributors. 1,762 commits in 2026 alone. Latest release v0.4.84, three weeks ago. Used by 30,000 teams. A $63 billion public company raised the price of screen recording 100x in February. A solo founder in Liverpool made it free the same year. Your recordings. Your storage. Your links. No surprise invoice. Free forever. AGPL-3.0 open source. (Link in the comments)

@anirudhbv_ce @OpenAI @GeminiApp @sentra_app meh rag is outdated

We finally know why LLMs hallucinate. It's not the model. It's the geometry. @OpenAI text-embedding-3-large: 91/3072 dimensions do real work. @GeminiApp gemini-embedding-001: 80/3072 dimensions do real work. ~97% of your vector database is mathematically empty. Your RAG system is retrieving from noise. @ashwingop and I present "The Geometry of Consolidation" - a proof that RAG compression has a hard floor no algorithm can beat, set by a single spectral number your embedding model cannot escape. Every hallucination your RAG pipeline produces? This is why. Paper + results: github.com/niashwin/geome…

No one goes to Vegas anymore, so many better options, ads arent going to help you here buddy