@milesdeutscher the morning routine and the amazon pick were never the reps keeping you sharp. offload the busywork, the real question is whether you redeploy the freed cycles or just scroll. the tool isnt making you dumber, the defaults are
@marty_kausas this is where the seat-based saas model quietly breaks. once usage bills past a seat cap your ai line item behaves like cogs, not software. the companies that survive this build a margin model around tokens from day one instead of bolting it on at seat 150
@RaoulGMI the vague-directions part is the actual shift. you stopped writing specs and started writing intent and it fills the gap. for scenario work thats where it earns its keep, it surfaces the branch you didnt think to ask for. macro desks are going to live in chat mode
Recently, we purchased one of each Anthropic/OpenAI subscription plan and randomly ran long horizon coding tasks until we exhausted the weekly limit. It's widely believed that a $200/month plan maxes out at ~$2000/month worth of tokens (assuming API pricing). However, we found that the subscriptions are actually far more generous. (2/4)
spacex prices at a 1.8t tag tomorrow, 30 percent carved out for retail, book 3.5x oversubscribed. largest ipo ever and the float trades like a scarcity asset before it even opens. the part nobody is modeling is whether the xai merger turns a launch-cadence story into an ai one
@filipsamardzicc the trd data is what makes the rest even thinkable. short-duration dosing is the real near-term unlock because it fixes clinic throughput. the upgrade-the-human-system framing is a decade of trials away, one indication at a time. exciting but the order matters
@aleximm vertical ai crossing 200m arr at 100 percent growth is the proof the wrapper fear was always backwards. the risk was never the model, it was whether you own the system of record. the ones that just automate a task get ripped out. the ones that become the books stay
@BIOTECHSCANNER macro is the headwind, not the story. amtagvi just cleared australia and the next gen til pipeline keeps moving while the tape only prices the melanoma launch. manufacturing already down to a 32 day turnaround. thats the part patience pays for
openai cutting prices to win back share while anthropic grows off never-adopters, same week. the frontier is commoditizing in real time and the whole game already moved to who owns the workflow
@arakharazian the never-adopter line is the whole story. growth pulled from firms already on ai is just share shuffling. growth from people who never touched it is the market actually getting bigger. codex flat in its launch month is the tell that distribution beats feature parity
@WSJ price is the tell that the model itself stopped being the moat. once the frontier commoditizes you compete on distribution and switching cost. cutting price to win share back means the workflow already migrated. you dont discount from the front
@joinautopilot the 30 percent retail allocation is the unusual part. most mega ipos hand retail the scraps. with orders at 3.5x the float is the constraint not demand, so this is priced into scarcity before it even trades. year one tape is where the real test lives
now that models like fable aren't subsidized anymore
its very bullish for companies building their own harness (devin, cursor, opencode, factory etc)
claude code becomes significantly less once useful since you're not "unlimited usage"
and these companies are highly incentivized to give you the best performance/ token (and have been trying to solve this for a while)
very good situation for companies all around (minus the users, cuz your ai bills are boutta 5x)
Most people can't actually explain what AI is to a friend/coworker.
Take a page from Dr. Seuss (trust me) & you'll be set.
When someone asks me "how does ChatGPT actually work?" I used to reach for words like "pre-training," "back propagation" and "transformers." And I'd watch their eyes glaze over (understandably) in real time.
So now I just say this:
If I say the words, "the cat in the ___," what comes next?
Your brain automatically fills in "hat," right? Mazel tov, you're an LLM.
An LLM is a machine that has read basically the entire internet, and all it does is predict the next word.
Over and over. "The cat in the" → "hat." Then it looks at "the cat in the hat," predicts the next word, and the next one, and the next one.
It's not thinking. It's not reasoning the way you do. It's the most powerful autocomplete ever built, so good at guessing the next word that the sentences it strings together can write your email, debug your code, or explain quantum physics.
That one reframe does two things for your team:
1) It kills the fear. "AI is coming for my job and I don't even understand it" turns into "oh… it's fancy autocomplete." Way less scary. Way more usable.
It builds the right instincts. Once people get that AI is just predicting the most likely next word, they suddenly understand why it makes things up (it's guessing), why specific prompts get better answers (you're shaping the guess), and why it sounds so confident even when it's wrong (it's always just predicting).
2) You don't need your colleagues to understand the math. You need them to understand "the cat in the ___." There's no downside to going down the rabbit hole & understanding AI at a mathematical/technical level, but it's not necessary if a professional simply wants to understand it well enough to work well enough with it.
Steal the analogy. It's the fastest way I know to take someone from "AI scares me" to "ok, I get it."
ataibeckley at the oppenheimer cns summit today talking bpl-003 phase 3 reconnection. the 100 minute session vs a 6 to 8 hour psilocybin chair is the throughput math the category keeps underpricing