blynn

Building | Past: @Google, @X, @Digits (valued $560M+), @Crashlytics (acq $100M+) | Investor @xAI @Apptronik @1x_tech @reflection_ai @UseReasoner

[Digits @digits]

Digits is now an official app in @ChatGPTapp from @OpenAI.

You can now connect ChatGPT directly to your real-time financial data in Digits.

That means:
📊 Live books — not exports or stale snapshots
🧩 Clean, structured financial data AI can reliably understand
🔎 Answers grounded in your actual ledger

Ask about burn, cash position, vendor spend, runway, or anomalies. Build real-time FP&A workflows, create investor updates, compare budget vs. actuals, and analyze what’s changing in the business as it happens.

𝐘𝐨𝐮𝐫 𝐀𝐈 𝐢𝐬 𝐨𝐧𝐥𝐲 𝐚𝐬 𝐠𝐨𝐨𝐝 𝐚𝐬 𝐭𝐡𝐞 𝐥𝐞𝐝𝐠𝐞𝐫 𝐮𝐧𝐝𝐞𝐫𝐧𝐞𝐚𝐭𝐡 𝐢𝐭. 💪

Try Digits in ChatGPT today 👉
https://t.co/G4S1imTxOr

[Siddhartha Saxena @siddsax]

Anthropic onboarding day: Michael Scott introducing Karpathy like he just signed Wemby in free agency.

[GREG ISENBERG @gregisenberg]

More AI agent observations below (I keep adding to the list):

1. Hermes agents write to their own memory after every task. Which means starting today versus starting in 6 months is an unfair advantage for you.

2. We're maybe 12 months from an agent that can watch you work for a week and then do your job without any instructions. The screen recording plus agent memory plus local model combination makes this possible right now

3. The real reason local models matter for founders: you can ship a product where the AI runs entirely on the customer's device and you never touch their data. Zero privacy concerns. Zero server costs. Zero compliance headaches.

That changes which industries you can sell to overnight. Healthcare, legal, finance, all the regulated verticals that won't send data to the cloud just opened up.

4. Every company needs to be rebuilt as a "second brain" before agents can be useful. That means every process, every decision, every piece of institutional knowledge has to exist in a format an agent can read. Most companies have none of this.

5. Agent costs are the new headcount. Won't be crazy for companies to spend 50%+ of their total headcount cost on tokens.

6. Agents are accidentally creating internal competition at companies. The marketing agent and the sales agent are optimizing for different metrics and working against each other without anyone realizing it. It took humans decades to develop cross-functional alignment. Nobody thought about it for agents.

7. The YAML config file is becoming the new org chart. Who reports to who, what permissions they have, what tools they access, all defined in a config file. The company's structure is literally a file you can version control, fork, and deploy. That's new.

8. The first agents that can smell a scam are going to be worth billions. Right now agents will happily wire money to a fake invoice because it matched the format. The trust layer is completely missing.

9. We're about to find out that most "expertise" was actually just memory. Knowing the tax code. Knowing the case law. Knowing which supplier charges what. When an agent holds all of that in context, the expert's value shifts from "I know things" to "I know which things matter." Much smaller group of people.

10. We're all running the same models. The differentiation is in what you feed them. Two founders with the same agent, same model, same tools will get wildly different results based purely on the quality of their knowledge base. Garbage context in, garbage output out. Forever.

11. The most underbuilt category in AI right now: agents for old people. 70 million boomers who need help with medical forms, insurance claims, and appointment scheduling.

12. Agent latency is the new page load speed. If your agent takes 45 seconds to respond, your customer already switched to one that takes

13. Skills files are the new apps. A SKILL.md that tells an agent how to do one thing well is more valuable than a SaaS subscription that does the same thing behind a login screen.

14. AI hardware... how do you create devices that are good businesses that people want? It'll be a $30 dongle you plug into existing dumb devices to give them an agent brain. Smart toaster doesn't need to be built from scratch. It needs a $30 brain attached to a $15 toaster.

15. Your agent can read faster than you can think. The bottleneck in every agent workflow is now the human approval step. We're the slow part. That's a strange thing to sit with.

16. Agents made the 80/20 rule violent. The 20% of work that matters is now the only work humans do. The 80% just disappeared. Entire job descriptions were hiding inside that 80%.

17. The thing I keep coming back to: the best businesses right now are being built by people who are just slightly ahead of their customers. Not 10 years ahead. 6 months ahead. That's the sweet spot. Far enough to lead. Close enough to be understood.

[blynn @blynn]

@ahmad_a_wahabb Took

[blynn @blynn]

The one constant here is that quality differs in an “idea guy” - there’re those who truly understood their customers, hustles, and would’ve likely been able to recruit a technical cofounder (though quality also varies here). And then there’re still those who think the idea is everything, have minimal skills and expect to have cofounders do everything for 1%.

[Mustufa Khan @mustufa4socials]

https://t.co/m5leqLx6zj

[Aakash Gupta @aakashgupta]

Brian Chesky personally photographed every Airbnb listing in New York in 2009. He flew out with a camera, knocked on doors, watched hosts greet strangers, took notes on what felt awkward.

Airbnb is now worth $78 billion.

His framework was the 11-star experience. A 5-star stay: someone meets you at the door. 6 stars: champagne on arrival. 7 stars: the host pre-stocked your favorite groceries. Keep going. 11 stars: Elon picks you up at the airport in a SpaceX rocket. The exercise sounds ridiculous on purpose. You design the version no one would ever build, then walk it back to what's actually deliverable. The version you ship at the end is a 7. Every competitor ships a 5.

Most founders skip this entirely because it doesn't show up in a board deck. There's no metric for "the host left a handwritten welcome note." There's no A/B test for "the apartment smelled clean." Those details compound into something investors call brand and customers call the only company I trust with my kids.

Chesky's rule: you don't move to the second user until the first one loves it. You don't move to the millionth until the second one loves it. The hand-crafted phase looks like wasted time on a quarterly review. It's the only phase that creates a real moat.

Now look at 2026. The model layer is commoditizing. Every consumer AI app is wrapping the same three labs. Compute is a line item. The thing that decides who survives is whether someone obsessed over what the perfect experience looks like for one specific user before they tried to scale to a million. Cursor did that. Linear did that. Most VC-funded AI products did not.

Reverse-engineering an experience to scale takes weeks. Hand-crafting it for one person takes years and looks unproductive the entire time. Most founders refuse to sit in that phase. The few who do end up on the Stanford stage worth $78 billion.

[MATT GRAY @matt_gray_]

https://t.co/onr2ZcmgLC

[Aakash Gupta @aakashgupta]

Paul Graham spent 20 years watching founders and found the visionary model was backwards.

Bill Gates built a BASIC interpreter for a machine with a few thousand users. Mark Zuckerberg built a website so Harvard undergrads could stalk each other. Neither one knew what they were going to become.

That is the opposite of how every startup school, pitch deck, and vision statement tells you to operate. You're supposed to walk in with a 10-year roadmap. TAM charts. A precise picture of the future you're building.

The people who built the biggest companies didn't have a precise vision. They had a direction. Gates had "microcomputers are interesting." Zuckerberg had "Harvard undergrads will use this." That was the entire thesis.

The math explains why. If your target is 10 years out and 100x bigger than anything that exists, every assumption in your model compounds error. Interest rates move. Hardware costs collapse. A competitor pivots. By year three the roadmap is a museum piece and you're optimizing for a world that never arrived.

Graham's analogy is Columbus. Columbus didn't have a map of the New World. He had "there's something to the west" and a boat. The destination was wrong, the continent was wrong, the math on how far was wrong. The direction was right, and the direction was enough.

The inversion every founder gets wrong: the popular image of the visionary is someone who sees the future precisely. Empirically, it's someone who sees it blurry and walks toward the blur while everyone else is drawing detailed maps of imaginary places.

Gates didn't set out to dominate microcomputer software for four decades. Zuckerberg didn't set out to build a universal vacuum for human time. They started with something small that worked, and the opportunity to move came later.

The VCs who fund vision decks and the founders who write them are playing the same game. The founders who actually built those companies weren't in the room.

[GEOFF WOO @geoffreywoo]

announcement:

silicon valley spent 15 years worshipping polished founders with elite resumes and perfect narrative control.

that meta is dead.

the next decade belongs to founders with 3 things:
1) pain tolerance high enough to rebuild the company every 6 months
2) technical taste strong enough to know when model progress changes the product
3) cultural distribution so they can recruit, sell, and survive the chaos

most VCs still optimize for the old archetype because their entire social graph is built around credentialism.

they want safe weird, not real weird.

the cultural shift happening right now is that the internet no longer respects institutional permission.
people follow raw competence, speed, and proof of work.

if youre still building your company to impress a partnership meeting, youre already behind.
build it to dominate the feed, dominate the product, and dominate the labor market that agents are rewriting in real time.

thats the new founder stack.
not pedigree.
not polish.
not sandboxed ambition.

[Dustin @r0ck3t23]

Jeff Bezos just told you exactly how to price AI.

Nobody listened.

Bezos: “AI is real and it is going to change every industry. In fact it’s a very unusual technology in that regard in that it’s a horizontal enabling layer.”

Horizontal enabling layer.

Three words that reprice the entire technology sector.

The iPhone was a vertical. One product. One new market.

Electricity was a horizontal. One substrate that rewired every market on Earth.

Wall Street is pricing AI like it is the next iPhone. Bezos is telling you it is the next electrical grid.

Right now, thousands of companies are trying to sell AI as a product.

A feature. A tool. A subscription tier.

Every single one of them will be priced to zero.

You do not sell a horizontal layer. You do not compete with it. You build on top of it or you disappear beneath it.

For a century, entire industries survived on one thing. Complexity.

The friction of navigating law, medicine, logistics, finance. That was the moat. If you could not memorize the maze, you could not compete.

A horizontal layer does not navigate the maze. It dissolves the walls.

Electricity did not compete with the candle industry. It erased the need for one.

The most dangerous part of a horizontal shift is how quiet it is. It moves underneath the economy. The surface looks normal. Revenue still holds.

Every day you operate on the old substrate, you accumulate a debt you cannot see and cannot repay.

The internet repriced distribution. AI is repricing cognition itself.

When intelligence becomes a utility that runs through the walls of every company on Earth, the premium on human expertise does not erode. It evaporates.

This is not a disruption. Disruptions replace products.

This replaces the ground you are standing on.

[Big Brain Business @BigBrainBizness]

Steve Jobs gives a counterintuitive take on leadership:

"a CEO should be at the bottom of the hierarchy"

Most people think power flows downward in an organisation from the CEO to everyone else.

But Steve Jobs believed the opposite.

In the clip below, he explains what happens when you build a company around genuinely exceptional people (whether in technology or in creative work like Pixar):

"Incredibly talented people that are also rare and in demand — if you don't treat them right, they can go get another job in 10 minutes."

Because of that, something counterintuitive happens. The hierarchy of power inverts.

Jobs puts it plainly:

"The CEO is actually at the bottom. I sort of feel like I work for most of these people, because they're the ones doing all the brilliant work."

This isn't Jobs's modesty shining through. It's a structural insight about where value is actually created.

Whether in software, hardware, or creative production... the best people are extraordinarily hard to find. And they know it. Their leverage is real.

So what does management's job become?

"It's management's job to support them. Because they're on the front lines doing the work."

The leaders who build the most extraordinary things aren't the ones who command from the top — they're the ones who clear the path for the people doing the real work.

[Oren John @orenmeetsworld]

if you create good video content the ceiling for where that takes you is multiplying exponentially as we speak

go harder

[DAN KOE @thedankoe]

You as a single person have more power today than a 20 person company of the past. That's insane. The internet gave you the ability to learn anything. Social media gave you the leverage to reach anyone. AI is giving you the ability to create almost anything. Please don't waste it

[andrew chen @andrewchen]

the "AI wrapper" critique assumes the wrapper is the easy part

But being the wrapper also includes figuring out:
- getting distribution without paying infinite CAC
- creating an amazing UX that's AI native, not derivative
- building a brand, trust in a very noisy landscape
- creating an ecosystem/community
- generating network effects
- making customer service great
- ... plus pricing, hiring, raising money, and everything else

these are not easy!

[Gary Vaynerchuk @garyvee]

https://t.co/f8pT7OVN0O

[Harry Stebbings @HarryStebbings]

The Secret Formula to $144M ARR in 5 Years: @giliraanan

4x, 4x, 3x, 3x.

Net new ARR.

First year: $1M.

Second Year: $4M.

Third Year: $12M

Fourth Year: $36M

Fifth Year: $144M

How have growth rate expectations on companies changed in the last 12 months and is the above even growing fast enough @kirbyman01 @chetanp @mmurph @jasonlk

[Startup Archive @StartupArchive_]

Tobi Lutke explains what the VCs who passed on Shopify got wrong

Tobi recounts pitching Shopify to VCs on Sand Hill Road a few years after founding Shopify.

Investors passed because they thought the addressable market was too small. At the time, there were about 40,000-50,000 online stores, and even if Shopify captured 50% of the market, that still wouldn’t be a venture-scale business.

When Tobi ran into the VC partner a few years ago, the partner asked Tobi what he missed (Shopify is valued at almost $100 billion today).

Tobi explained:

“You were actually correct, but what you didn’t realize was that Shopify was the solution to the very problem you identified. The reason there was only 40,000 online stores was because it was hard, expensive, and everyone who tried ran into all these brick walls of complexity, which Shopify, one after another, smoothed over and made simple to do.”

Tobi believes this is a common mistake:

“What a lot of free-market thinkers don’t understand is that between the demand and eventual supply lies friction. And I actually think that friction is probably the most potent force for shaping the planet that people just generally do not acknowledge… That was my theory when I turned my snowboard store into Shopify: there was a lot more people like me except there was too much friction which we needed to solve. And Shopify has proven out that every time we make the process simpler, there’s more consumption. At this point, we have a million merchants on Shopify, which is a mind-blowing number. So friction is a major component, and it’s something that software is uniquely good at reducing.”

Video source: @danmartell (2019)

[blynn @blynn]

@katibmoe One

[blynn @blynn]

@MitcheIl Agent