subj
I'm biased and bullish on the goog
We're in the "what if Google does that" part of the AI cycle.
They can make
— cheaper models ($2/M in, $12/M out, just above GPT5.1, cheaper than Pro)
— better models (benchmarks)
— distribute products at no cost to billions of users (Gemini has >50% MAU of ChatGPT, Antigravity is free vs Cursor $20-40/mo)
— get good unit economics (own TPU, no reliance on Nvidia premiums), use it to retain premium talent cheaper
Of the BigTech giants, Amazon and Microsoft chose to be infra partners. Apple chose not to play. Meta shat the bed. Google is coming out on top.
They can make
— cheaper models ($2/M in, $12/M out, just above GPT5.1, cheaper than Pro)
— better models (benchmarks)
— distribute products at no cost to billions of users (Gemini has >50% MAU of ChatGPT, Antigravity is free vs Cursor $20-40/mo)
— get good unit economics (own TPU, no reliance on Nvidia premiums), use it to retain premium talent cheaper
Of the BigTech giants, Amazon and Microsoft chose to be infra partners. Apple chose not to play. Meta shat the bed. Google is coming out on top.
subj
surging stock portfolios
It’s hard to overstate the significance of the soaring stock prices of artificial intelligence companies to the economy. Spending by well-off Americans, driven by their surging stock portfolios, is the single most significant driver of growth. This so-called wealth effect is responsible for nearly half a percentage point of real GDP growth over the past year, accounting for one-fourth of the economy’s overall growth. The wealth effect has been a tailwind to growth, more or less, since recovering from the Global Financial Crisis. Of course, housing wealth is also up a lot, and the well-to-do are still holding onto a big pile of cash that they accumulated during the pandemic shutdowns. But given the outsize gains in wealth compared with the growth in incomes and the economy more broadly – household net worth is now eight times after-tax income, compared with an average of 5.5 times in the decades between WWII and the GFC – it is prudent to consider how sustainable this is. And if it isn’t, what does it mean for future growth?
subj
Prompt-apaloooza
What?!! Someone literally just leaked the hidden system prompts of 30+ top AI tools 🤯
These are the essential playbooks that control tone, safety, reasoning and creativity.
Lovable, Claude, Cursor, Devin, Gemini, Perplexity... all exposed.
The leak covers 30+ tools, here's the full list:
→ Devin, v0, Cursor, Windsurf, Replit
→ Claude Code, Manus, Lovable, Augment Code
→ Notion AI, Xcode, Gemini CLI, Orchids.app
→ Warp, Qoder, Bolt, Cline, RooCode
→ 20k+ lines of condensed prompts
Here's the repo (100% open source):
↳ https://lnkd.in/duUyf4Dz
These are the essential playbooks that control tone, safety, reasoning and creativity.
Lovable, Claude, Cursor, Devin, Gemini, Perplexity... all exposed.
The leak covers 30+ tools, here's the full list:
→ Devin, v0, Cursor, Windsurf, Replit
→ Claude Code, Manus, Lovable, Augment Code
→ Notion AI, Xcode, Gemini CLI, Orchids.app
→ Warp, Qoder, Bolt, Cline, RooCode
→ 20k+ lines of condensed prompts
Here's the repo (100% open source):
↳ https://lnkd.in/duUyf4Dz
subj
Reality of vibe coding at a FAANG
Here’s the reality:
• It all starts with a technical design document, almost like a PRD.
• That doc gets torn apart and rewritten multiple times by senior engineers.
• Once it’s solid, the build is broken into sprints so devs and AI assistants don’t get overwhelmed.
• Only then does coding begin... but with a twist. They write the tests first.
• AI generates the code. If it doesn’t pass the tests, it doesn’t ship.
• Everything still goes through manual code review and staging before production.
The result? About 30% faster shipping speed.
Not 90%. But here’s the thing: 30% saved at FAANG scale is enormous. And even more importantly — it prevents the classic trap of shipping spaghetti code 90% faster, only to debug it 90% slower.
• It all starts with a technical design document, almost like a PRD.
• That doc gets torn apart and rewritten multiple times by senior engineers.
• Once it’s solid, the build is broken into sprints so devs and AI assistants don’t get overwhelmed.
• Only then does coding begin... but with a twist. They write the tests first.
• AI generates the code. If it doesn’t pass the tests, it doesn’t ship.
• Everything still goes through manual code review and staging before production.
The result? About 30% faster shipping speed.
Not 90%. But here’s the thing: 30% saved at FAANG scale is enormous. And even more importantly — it prevents the classic trap of shipping spaghetti code 90% faster, only to debug it 90% slower.
subj
duuuuuude
body slams for 'merica!
express, not stress