Glaze

Random thoughts after trying 3 amazing AI+consumer tools @a16z highlighted: @mindseraAI provides coaching to improve journaling and reflection. It uses guidelines and methodologies, aiding those who struggle with writing, like ChatGPT's recommended questions.

@DaiZeshi 谢谢 james 哥哥

.@glazecl looking really handsome

@yuta1922521 @IOSGVC @SurfAI Thanks Yuta, appreciate the support. Excited to see this integration moving forward.

@IOSGVC @SurfAI @glazecl Thank you @glazecl for leading this integration 😍

Why we built on @SurfAI, from our AI lead @glazecl. 🌊Best-in-class settlement, fundamentals, and fundraising data, flexible enough (MCP + API) to wire straight into the research tooling we'd already built. ▶️

@IOSGVC @SurfAI Shoutout to @ryanli and @DaiZeshi for all the support. They’ve been incredibly helpful in shaping our use case. @SurfAI provides high-quality datasets at an affordable price, making it easy to build and iterate. We have something big coming soon. Stay tuned. A "game" changer

Proud to partner with @SurfAI as their first design partner. 🌊 We've plugged @SurfAI into our internal research agent as the sole source for 5 data categories our stack couldn't cover: social mindshare, perp liquidations by exchange, VC fund data, prediction markets, and fundraising. One question in, cross-checked diligence out.

Which is why "just learn to code" is aging badly. The skill worth having is knowing what is worth building and what form actually solves it. AI makes that harder, not easier. Now everyone competes on it.

You feel it the second you hand an internal tool to a real user. It works fine. It also feels wrong, and half the time you can't say why. That "why" is exactly what good SaaS was quietly charging you for.

When anyone can build anything, taste is the moat. Everyone can build software now. Almost nobody knows what is the right product to build. After a year of watching my team vibe code everything, I'm pretty sure that gap is the whole game.

@wadefoster @zapier We built an internal agent to collaborate. Access control and interation are challenging. Would love to try it. We perfectly fit all the expectations here

Today we open early access to @Zapier's next product We've been using it internally for months (>1,000,000 actions executed so far) and it's completely changed how we work. We're letting a small group of AI-forward teams try it first and give feedback. Who we’re looking for: - 10-100 person teams using AI daily, but need to do so more collaboratively - teams ready to build and ship automations through agents, not just chat - teams that already work in the open (call recordings, shared docs, public channels, etc) - teams obsessed with optimizing every aspect of their work Join the waitlist: zapier.com/shared-brain

Features - Unified tool inventory. All skills, MCPs, plugins, commands, hooks across 34 agents in one table. - Cross agent install. Install once, enable on any agent via symlink. No copies, no drift. - Full CLI. Everything in GUI also works as shuttle command.

I built Shuttle. Mac app for managing skills across 34 AI agents. Claude Code, Codex, Cursor, Gemini CLI, OpenCode all in one place. Install a skill once. Enable on whichever agent you want. Symlinks, not copies. No version drift. github.com/glazec/shuttle…

3: CapEx/Revenue gap. ~$690B hyperscaler AI capex in 2026. ~$100B in direct AI software revenue. 7x gap. Sequoia's David Cahn called this the "$600B question" in June 2024. The gap has only widened since. Apps are the only path to converting infra spend into actual revenue.

2: commoditized infra the enterprise llm market flipped fast: openai went from ~90% share to anthropic taking ~70% of new spend in 18 months. with 5+ models within ~2% on benchmarks, models become a commodity. edge moves to workflows, data, and distribution: the app layer.

There's a reliable rotation between Infra and apps. 1/ Infra goes open source → value moves to apps 2/ Infra commoditizes, fierce competition → margin compresses, apps capture value 3/ CapEx explodes but revenue lags → apps become the only way to justify the spend

@DaiZeshi Institutions and pros gain advantage on betting.

Dub — Open-Source Link Attribution Platform Started as a URL shortener and evolved into an open-source link attribution platform covering the full pipeline of link management → conversion tracking → affiliate payouts. Used by 100,000+ companies including Twilio, Vercel.

Value Chain: Institution Accessing DeFi Web2 Investor → Fund → Vault → Vault Infra/Protocols → Custodian + Compliance → DeFi Protocols

The opportunity: whoever owns the policy layer owns the institutional DeFi stack. This is the boring, essential middleware that makes the next $1T in institutional DeFi possible.

The mental model shift: DeFi has been punitive. you break the rules, you get liquidated. Institutions need DeFi to be proactive. the rules are enforced before you can break them. That's a completely different architecture.

Institutions want DeFi exposure. Everyone knows this. But there's a missing piece almost no one is building: programmable policy enforcement. Without it, institutions can't touch DeFi. With it, the floodgates open. 🧵