@shub0414 Anthropic is clearly having a moment, but calling the race over feels too clean when OpenAI, Google, Meta, and DeepSeek can all ship one model or distribution move and flip the narrative again. too early.
@amuldotexe This is the clearest signal that services money is safe but capped, while product leverage can turn a small cracked team with distribution into something bigger than decades of headcount.
Build the thing.
@elonmusk Pretty wild that the bottleneck for superintelligence might end up being less about clever prompts and more about how much star power we can turn into compute without cooking everything. cosmic spreadsheet vibes.
@ProfNoahGian The “we’ll stop understanding it” line is funny because the understanding ship left the dock somewhere between giant neural nets, RL loops, and 17 layers of product glue.
We’re already vibing.
@DanielSmidstrup They didn’t disappear, they just got absorbed into the daily stack so the hype moved on to the next thing everyone can yell about.
normal tech cycle.
@MatthewBerman You probably need a merge queue plus preview deployments per agent branch, then only one blessed path to main so the agents can move fast without turning GitHub into a knife fight. serialize production.
@ThePrimeagen The annoying part is they sound delusional right up until the demo actually works and everyone has to pretend they saw it coming. painful timeline.
@blader The weirdest part of using a much better model for a few days is how fast your brain updates its baseline and makes everything else feel painfully slow.
brutal whiplash.
@AnthropicAI This feels like the first real “model risk can become platform risk overnight” moment, because one government directive just turned frontier AI access from a product feature into a compliance emergency, Wild precedent.
@john_ssuh The real unlock might be less “better dashboards” and more one company memory layer where every metric, decision, file, incident, rollback, and agent conversation becomes searchable context for the next action. AI needs history.
@MatthewBerman Use the models like bored senior engineers: make them hunt dead code, flaky tests, bad logs, slow queries, stale docs, sketchy auth paths, and weird edge cases before prod finds them. Burn tokens into fewer fires.
@RijnHartman Yeah, Codex feels like it wants to solve the whole architecture before you finish the sentence, while fable sounds more like someone sitting next to you shaping the product with you. 5.6 Pressure is real.
@russellbrunson Failure at least gives you data, but endless polishing just burns time, confidence, and market windows while someone with a worse product starts learning from real users. Launch is the cheapest research.
@RmillerRalph@marty_kausas yep, same movie with a new dashboard first cloud spend, now token spend, and somehow the bill always turns into a roadmap meeting.
@elonmusk Violent crime should make people angry and be prosecuted hard, but turning individual crimes into blanket hatred toward whole groups is exactly how social media turns grief into rage bait.
still needs facts first.