tejaditya

fun enthusiast. chasing consistency. Product @Microsoft. Tweets are preposterous opinions. COYG

[Nikunj Kothari @nikunj]

the models have no moat (OpenAI, Anthropic, XAI)

the IDEs have no moat (Cursor, Windsurf)

the harnesses have no moat (Cognition, Factory, LangChain)

the app builders have no moat (Replit, Lovable, Bolt)

the wrappers have no moat (Harvey, Abridge, OpenEvidence)

the inference providers have no moat (Together, Fireworks, Groq)

the voice layer has no moat (Sierra, Decagon, ElevenLabs)

the data labeling companies have no moat (Scale, Surge, Mercor)

the AI infrastructure has no moat (Baseten, Modal, Railway)

the neoclouds have no moat (CoreWeave, Lambda, Crusoe)

the generative media companies have no moat (Runway, Higgsfield, Suno)

apparently nobody in AI has a moat

except the venture firm ☠️

[Jake @JustJake]

To have a high bar, be clear, and kind while holding it

There is no greater gift you can give to another

[Henry Shevlin @dioscuri]

My students sometimes ask why they should memorise things in the age of Google and LLMs. But internalised facts are your bullshit filters and your raw material for creative association. Facts outside your head are inert.

[Paras Chopra @paraschopra]

To develop deep intuitions in any domain, you have to go through the grind and the struggle of using your brain.

You really can’t outsource understanding as the whole point of it is to develop and evolve a highly *personal* web of belief about how a domain works.

[Paul Graham @paulg]

@charliermarsh Sometimes they're a good reason to work on something. When people say a market is "crowded," what that often means is that there's a real problem and none of the solutions are good enough yet.

[Matt Stockton @mstockton]

I’m obviously biased — but this 1000%.

We have an extreme AI capability overhang - which in simple terms means that if things were to just totally pause re: AI improvement, it would take a long time for companies to implement what’s possible right now. Even with this truth, there is adoption friction.

Why is this the case? because you still need specific people to do the implementing. AI is amazing but it is also a tool - and we still need skilled people to use the tool the ‘right way’ - and we need people who are specifically skilled at understanding what that means

My experience working with teams trying to ‘adopt AI’ can be summarized as follows:

- everyone is busy with their actual job, which doesn’t include adopting AI / understanding how to do so
- no one is tasked with considering how AI changes the shape of their specific job or how their job relates to other jobs
- no one is specifically tasked with understanding ‘how to do ai’ across functions.

Which is why Aaron’s point is so on point. There is an entirely new discipline emerging, which is still emerging / nascent. The shape of it isn’t fully defined, but the need for it is obvious.

There is an AI implementation gap to fill. And there is an amazing opportunity for folks who are willing to experiment and put in the reps to fill it

[Steven Strogatz @stevenstrogatz]

I really enjoyed Apoorva's essay. It's rare these days to hear what a *student* thinks about what's going on in AI and Math, and I highly recommend you take a look at her piece – it's thoughtful, curious, idealistic, and unmistakably human.

[Garry Tan @garrytan]

High agency high taste is the unlock these days

[Paul Graham @paulg]

A startup idea that only works if there are already a significant number of people using it is not a valid startup idea. There has to be some subset of users who need what you're making so desperately that they'll use it even if no one else is.

[John Collison @collision]

As you become an adult, you realize that things around you weren't just always there; people made them happen. But only recently have I started to internalize how much tenacity *everything* requires. That hotel, that park, that railway. The world is a museum of passion projects.

[signüll @signulll]

one of the most refreshing things on the planet is talking to someone who just *gets it*.

like you don’t need a preamble, & you don’t need to articulate the shape of the thought before you can share it cuz they just meet you where you already are. as if they skimmed your mind & married to the culture before you say a single word.

these people are rare, & conversations with them are incredible because you skip the surface layer entirely & land in the depth almost immediately. they’re the best ppl to riff with, ideate with, & think forward with.. the bandwidth is wide & already open.

this is true for any type of relationship.

[Sky Sports News @SkySportsNews]

"Pressure is a privilege"

Golden Globe winning actor Tom Hiddleston gives his thoughts on the huge clash between Manchester City and Arsenal 🎬

[Ryo Lu @ryolu_]

as agents make it easy to add features, design matters more, not less. the role is no longer just pushing pixels – it’s deciding what should exist, how it fits together, how humans stay in control, and how intelligence feels clear, trustworthy, and useful.

taste, craft, and judgment have always been the bottleneck. the game is not who ships fastest, but who makes the right thing for humans.

[tejaditya @_tjaysan]

@akoratana 100X

[Animesh Koratana @akoratana]

We're also giving away a curated collection of 200+ Claude Code Skills our team uses daily — the workflows that made us faster engineers while building PlayerZero.

Repost and comment "100X" to get access.

[Ryo Lu @ryolu_]

keep struggling

when things come too easy, you don’t exercise the brain nor the emotions. ease can feel like progress, but it often skips the reps that actually change you.

growth is usually a loop, not a straight line – you take passes. you try, you fail, you reframe. you come back with a slightly better model, a slightly calmer nervous system, a slightly wider range of what you can handle.

hardship isn’t the goal. but friction is gold. it shows you where your understanding is thin, where your habits are brittle, where your ego is doing the steering. the struggle is the curriculum.

agents are making things easier, and that’s good. but don’t confuse speed with depth. use AI to remove busywork, then spend the saved energy on the parts that still hurt a little: the unclear problem, the uncomfortable conversation, the hard tradeoffs, the things you can’t yet explain in words. instead of putting all your wishes into the black box, actually keep thinking, and seeing things fully.

keep the difficulty where it matters. outsource the tedious, keep the meaningful resistance. that’s how we keep learning – and how we stay human while your tools get superhuman.

[Karri Saarinen @karrisaarinen]

I think we have lost some sense of judgment and moderation when it comes to product building currently.

The moment you turn something into a universally celebrated metric, whether that is token burn, prototype count, or percentage of agent-written code, you start losing sight of what actually matters.

I have felt the same way for a long time about overusing data and A/B testing to build products. The moment you reduce product quality or productivity to a metric, you stop shipping value and start shipping numbers.

A lot of what people are doing with AI makes directional sense. The missing piece is counterbalance:

1. AI should help engineers build better products. Leaderboards and adoption metrics can be useful as directional signals. They do not tell you what is being built, whether it is good, or whether it should exist at all.

2. Users do not care what percentage of your code was written by agents. They care about the outcome. Faster output is useful. Like usually, faster doesn't seem to add to quality, clarity, or stability of products. Power to build should not become an excuse to lower quality bars.

3. LLM-generated prototypes can feel like late-night whiteboarding sessions. They look exciting in the moment and feel productive very quickly. Then a few days later you realize the idea was shallow, distracting, or simply wrong. The same trap shows up in jumping straight to code and solutions more broadly. You may just be building the wrong thing more efficiently. Prototyping has its place. So do clear thinking, good design, and a real understanding of the user’s problem. In terms of activities or momentum, the main quest and the side quest can both feel productive but only one actually moves the mission forward.

4. Adding more to products is still dangerous as ever even if time or effort to add it has gone down. Every addition creates complexity, maintenance cost, and user confusion. New features should be pushed back unless they clearly show it should exist and how it improves the product.

5. Not everything needs to be an agent shaped. A simple scheduled task does not need a full LLM sandbox. Making something agentic because it feels current or impressive does not make it right-sized, correct, or effective.

The core ideas are:
- even if you can, maybe you should not.
- more power we have to build should not reduce our need to think, it should increase it.

[Tanay Kothari @tankots]

We offered 5 people a Porsche 911 GT3 RS if they could get @WisprFlow to make a mistake

It's the fastest and most accurate AI voice dictation app that's 3x more accurate than ChatGPT, Claude, or Siri.

Today, we’re finally launching on Android. Download now: https://t.co/TJhnUhDSLv

As a part of the launch, we’re giving away 6 months of Wispr Flow Pro for free.

Like, retweet and comment ‘Wispr Flow’ to get it. Enjoy.

— Written with Wispr Flow

[Taijitu Observer @taijitu_sees]

Love this shape so much. Such a lifesaver.

When I have a higher dimensional perspective like this shape and someone from lower dimensional space tells me it's actually strictly square, triangle, or circle it becomes so much easier to identify their perspective limitations.

[Jaana Dogan ヤナ ドガン @rakyll]

Burnout happens when there is no progress. Burnout also happens when you have no visibility into how dots will connect in the future. Burnout is about not being able to close the loop after putting a ton of effort and not seeing enough results.