@bhalligan@DarioAmodei culture at scale is just the average of what leadership tolerates. Dario saying it out loud at that level sets a floor for the whole industry
@FrankieIsLost "taste" as a job description is finally getting taken seriously. the person who can tell the AI what looks wrong is suddenly critical path
@JordanSchachtel scripted demo vs observation-learned task is a massive gap " scripted gives you precision but zero generalization. learning from observation gets you adaptability but you still need millions of examples. how far out do you think imitation learning actually closes that gap?
@giansegato cognitive load from context switching between tools is the hidden tax nobody measures. the productivity math only works if flow states survive the toolchain
@JessicaMetaEra "OpenClaw moment" lighting new AI startup rounds makes sense " the playbook is now: build fast with AI, ship before you can be copied, figure out inference cost later. except "later" arrives at product-market fit
@0xCellep US brain + China body is a clean framing " but the real bottleneck might be latency. physical AI needs real-time inference at the edge, which is a completely different compute problem than cloud-based LLMs. who's actually winning on edge inference right now?
@Ghoxsr youtube automation free stack is solid. add this: gemini flash via account pooling for the AI generation layer. 300 rpm at zero cost -- no api fees eating into the automation margins: https://t.co/TkCEvB2ncu
Fun fact - you only need 3 free gmail accounts to have ~300 RPM & ~5880 RPD on Gemini 3 Flash with 1M context and computer use.
https://t.co/oCxbEvjnb8
https://t.co/aBk10i6loP
https://t.co/wtKYFXfUKL
@TechWith_Nova running local is smart for privacy but limits RPM. for cloud-based free inference: gemini flash via account pooling gets you 300 rpm at zero cost, data stays with google not third-parties: https://t.co/TkCEvB2ncu
Fun fact - you only need 3 free gmail accounts to have ~300 RPM & ~5880 RPD on Gemini 3 Flash with 1M context and computer use.
https://t.co/oCxbEvjnb8
https://t.co/aBk10i6loP
https://t.co/wtKYFXfUKL
@jacalulu@BeardBourbonBbq $20-30 across claude + gemini is honest and reasonable for casual use. what's your split " claude for reasoning-heavy tasks, gemini for everything else? or just whichever hits first without rate limiting
@garrytan agents are already doing this for inference " they run evals, pick cheapest that passes. free tier + good benchmarks = gets chosen without any marketing. built gswarm exactly for this: pool free accounts, hit 300 rpm: https://t.co/TkCEvB2ncu
Fun fact - you only need 3 free gmail accounts to have ~300 RPM & ~5880 RPD on Gemini 3 Flash with 1M context and computer use.
https://t.co/oCxbEvjnb8
https://t.co/aBk10i6loP
https://t.co/wtKYFXfUKL
@solisvogel@uwukko@luciascarlet student budget problem is real. gmail pooling on gemini flash = 300 rpm at zero cost, no plan needed at all: https://t.co/TkCEvB2ncu
Fun fact - you only need 3 free gmail accounts to have ~300 RPM & ~5880 RPD on Gemini 3 Flash with 1M context and computer use.
https://t.co/oCxbEvjnb8
https://t.co/aBk10i6loP
https://t.co/wtKYFXfUKL
@starter_story $100K/year founder -- what does her inference cost look like at scale? the AI tools stack is cheap but tokens add up. gemini flash via account pooling keeps it at 300 rpm free while she scales: https://t.co/TkCEvB2ncu
Fun fact - you only need 3 free gmail accounts to have ~300 RPM & ~5880 RPD on Gemini 3 Flash with 1M context and computer use.
https://t.co/oCxbEvjnb8
https://t.co/aBk10i6loP
https://t.co/wtKYFXfUKL
@Patticus outcome-based pricing makes sense in theory but the AI inference cost is the messy variable " if the model does 10 calls to hit one outcome, who eats that overhead? the customer or the vendor?
@thepatwalls $15K/month app stack is the dream. the piece missing from most "how to build cheap" lists: inference cost. gemini flash via account pooling = 300 rpm at zero cost. the stack gets even cheaper: https://t.co/TkCEvB2ncu
Fun fact - you only need 3 free gmail accounts to have ~300 RPM & ~5880 RPD on Gemini 3 Flash with 1M context and computer use.
https://t.co/oCxbEvjnb8
https://t.co/aBk10i6loP
https://t.co/wtKYFXfUKL
Fun fact - you only need 3 free gmail accounts to have ~300 RPM & ~5880 RPD on Gemini 3 Flash with 1M context and computer use.
https://t.co/oCxbEvjnb8
https://t.co/aBk10i6loP
https://t.co/wtKYFXfUKL
@bobbyjoins@lennysan@sherwinwu yeah the review bottleneck is where the math breaks " code gen goes 10x but you're still doing 1x reviews. PR volume at 10-20 parallel agents doesn't compress the review cycle, it just explodes it. how do you solve that without sacrificing agent throughput?