Ankit Jain

Strategy & Finance @Swiftly, Formerly @BCG, @KelloggSchool, @IBM, @DukeU, @IMSA_

[Nabeel S. Qureshi @nabeelqu]

Medicine discovers the bitter lesson: frontier LLMs (here GPT 5.2, Opus 4.6, Gemini 3.1) outperform specialized "clinical AI" (e.g. OpenEvidence) in a blind test.

Even funnier that hospital IT are more likely to approve the *specialized* versions despite them being worse.

[JerryRigEverything @ZacksJerryRig]

You know the reason your Stanley or Hydroflask is so good at keeping your water cold is because there's a vacuum inside the walls of the thermos.

Heat can't conduct in a vaccum. And "radiated" heat is ineffective at the temperatures processors operate at.

This satellite will be like plugging in your gaming PC without a CPU cooler. It'll be dead in minutes.

[critter @BecomingCritter]

you build it in the order that it was actually erected during its 140+ years of construction. ngl that's dope af

[Ankit Jain @AyeJayTwo]

#9 on this list is probably the most articulate position on how AI will impact professions going forward. Those that are most at-risk are the ones that tend to "just" do tasks, not complete objectives. Being able to articulate the latter (not just the former) is key

[Lenny Rachitsky @lennysan]

My biggest takeaways from @benedictevans:

1. We’re in 1997 for AI—it’s as big a deal as the internet or mobile, and only as big a deal as the internet or mobile. We’re at the stage where most stuff kind of doesn’t work yet, most of what people will build hasn’t been built, and it’s not clear how any of it will work when it does. Some people in tech have bought clusters of Mac Minis, while even among 13-to-18-year-olds, only about 15% to 20% are daily active users of AI. The companies that win may not exist yet, and the use cases that matter most are probably invisible to us today.

2. Every technology wave brings ways to ruin people’s lives, deliberately or by accident, and we need to be conscious of that without panicking. Every wave of technology—databases in the 1970s, social media in the 2010s, AI today—creates new ways to harm people. We need to be conscious of these risks, build safeguards, and hold people accountable. But we also can’t let fear of potential harms stop us from capturing the benefits. The goal is thoughtful deployment, not paralysis.

3. Things will probably be okay—but “on average” hides a lot of individual pain. We’ve been automating jobs and creating new jobs since 1800. Each time, you can see the jobs that will disappear but not the new jobs, because they don’t exist yet. We go through frictional pain, dislocation, people lose jobs, towns get hollowed out, and it all sucks. But we come through richer, and we’re not worried about crops failing anymore.

4. If you’re worried about your job, the worst thing you can do is stick your head in the sand and declare AI evil. Yes, some professions face major questions, particularly if you’re an associate or would have been thinking about becoming one. The pyramid structure of professional services may fundamentally change. What helps is submerging yourself in AI, understanding what you can do with it, how it changes things, and how you can be a great hire in this new environment. That may still not be enough, but it’s the only path forward.

5. The history of accounting shows us how automation often increases employment rather than decreasing it. Despite adding machines, punch cards, mainframes, databases, ERP systems, cloud software, spreadsheets, and PCs, the number of accountants keeps going up. This is the Jevons paradox: when you make something cheaper or easier, you don’t do the same amount of work for less money. You often do vastly more because the ROI changes.

6. Distribution is becoming a more valuable moat as software gets easier to build, which favors incumbents. As AI makes building software cheaper and faster, the market gets noisier. More products launch, more companies compete for attention, and breaking through becomes harder. This means distribution—the ability to reach customers and get them to use your product—matters more than ever.

7. Foundation AI model companies won’t have lasting pricing power, and value will likely accrue up the stack. The models don’t seem to have network effects, so there’s no winner-takes-all dynamic. If you have indefinite competition between three to six foundation model providers, and the models look like undifferentiated commodities to users, why would anyone have pricing power? The current pricing chaos—people spending $1.5 million on inference in a month—is temporary disequilibrium, like someone getting a $50,000 mobile data bill in 2010. The steady state will look different.

8. OpenAI and Anthropic are buying consultancies and PE firms. This seems counterintuitive—aren’t these the companies that should need consultants least? But the reality is that companies don’t have people sitting around waiting to reimagine all their internal workflows and figure out which could be automated with AI. That’s a project requiring five to 10 people spending months working it out, then actually implementing it across vertical and horizontal systems.

9. The fundamental question isn’t whether AI automates your job—it’s whether your profession is a "task" or a job. Some jobs are just tasks, and when you automate the task, the job disappears (i.e. elevator attendants). But in most professions, the task you think you’re being paid for isn’t actually what you’re being paid for. McKinsey doesn’t get hired to produce a 75-slide deck—they get hired to walk through your enterprise, understand the politics, talk to customers, and figure out what you actually need to do. The deck is just the artifact.

10. The anti-AI backlash is real, and a fuzzy mass of different concerns, some real and some not—much like the social media backlash. There are tangible concerns: electricity bills went up in some places, though this applies to very few locations objectively. The water consumption issue is largely false; data centers use about 0.017% of U.S. water consumption. There are real questions about jobs, though economists can’t yet find clear consensus in the data about AI’s employment impact. There’s also the culture war over AI-generated content and “AI slop.” The challenge is that all of this creates political pressure even when the underlying facts are unclear or contested.

[Ethan Brooks @alt_w_v_g]

Kindergarten graduation

The teacher made a video of every kid saying what they want to be when they grow up

Proudest moment of my life

My wife looked at the ceiling

The teacher asked to speak to me after

She did not say what about

Probably to apologize for putting him last in the interview order

He's going places

Some may say that I am the world's best dad

Sent from my iPhone

[sophie @netcapgirl]

this is KD joining the warriors for people who know linear algebra

[Duke Men’s Basketball @DukeMBB]

PRIME TIME 💡💡💡💡👿

[Duke Digest @DukeDigest]

“Duke will fall off after Coach K leaves”

[Karter Baughan @karterb8]

Jon Scheyer: "Cayden Boozer put us on his back today... Cam and Isaiah were just okay."

Isaiah Evans: "So was your coaching" 😂

[Duke Digest @DukeDigest]

DDMF

[Timon Wong @t31kx]

Claude Code: "You've hit your limit · resets 7pm"

Me from 5-6.59pm

[Ankit Jain @AyeJayTwo]

USA! USA! USA!

[SportsCenter @SportsCenter]

THE MOMENT THAT SECURED GOLD FOR TEAM USA MEN'S HOCKEY 🇺🇸

(via @NBCOlympics)

[SportsCenter @SportsCenter]

THE MOMENT THAT SECURED GOLD FOR TEAM USA MEN'S HOCKEY 🇺🇸

(via @NBCOlympics)

[Colyn @colynelliott]

so this just ruined my day

[Ankit Jain @AyeJayTwo]

The point of hard work is to prove to yourself you can do hard work

[tian/天 @xtbot]

The point was never to be “the smartest.”

The medium doesn’t matter. What matters is whether kids regularly face difficulty they didn’t choose and learn to push through it.

Math, music, and hard problems were always character training in disguise.

It’s also naive to think Asian parents don’t know that.

[tian/天 @xtbot]

The point was never to be “the smartest.”

The medium doesn’t matter. What matters is whether kids regularly face difficulty they didn’t choose and learn to push through it.

Math, music, and hard problems were always character training in disguise.

It’s also naive to think Asian parents don’t know that.

[Duke Digest @DukeDigest]

#CarolinaHateWeek @thewendellmoore

[Ejaaz @cryptopunk7213]

so just to recap this week (so far)

- musk industries is real (spacex, tesla, xai merger)

- clawdbot explosion leading to a bankrun on mac minis but then anthropic released their own version

- tesla dropped the bomb they’re halting production on model s and x to scale 1M optimus humanoid robots this year instead

- china dropped the mother of all open source models kimi k2.5 that turn video into production-ready apps but then google dropped a gemini update ON THE SAME DAY that does the same thing gg

- google said fuck it and also launched the worlds greatest world model genie and switched on gemini for 3.8B chrome browser users AND released alpha genome model that one-shots 1M dna base pairs for 3000 researchers across 160 countries AND teased new veo model

- microsoft crushed earnings, launched a new ai chip but stock still tanked 10% because they *only* grew rev 39%

- anthropic round 2X oversubbed raised to 20B 🏌️

- openai raising another $100B, 750B val 🏌️

- intel leaked they’re gonna help produce nvidias next gen feynman gpus - hello americas tsmc

- a robot (built by figure) washed the dishes with zero human interaction

- apple acquired stealth startup for $2B that can lip read - integrating their tech for new ai consumer airpods with cameras and mics

- demis confirms google glass 2.0 coming this summer

fckin hell

[Ankit Jain @AyeJayTwo]

@homsiT @ReadwiseReader Me!

[Andrew Nadeau @TheAndrewNadeau]

It’s crazy how good babies are for excuses. You can be like, “Sorry we’re late, SOMEBODY pooped themselves!” and everyone just assumes it was her.