The Computomatix Times

billiondollarpdf.com/

Great collection of exceptional writing online

this is everything you should know before building an app.

i’m not even joking, save this.

How to find a validated $10k MRR startup idea:

> setup TrustMRR MCP
> ask it “give me 10 startups making $50k+ MRR that aren’t built for agents yet”
> copy and build it for agents

Tag me when you’re rich.

Jack, who built a $30K/month Shopify app with AI (and can't code), says most of his growth came from word of mouth he hasn't even hard launched yet:

"We have 43 uninstalled and 47 installed. We've made $147,000 to date. We have 122 users of the app right now."

"Most of our growth came from like word of mouth. We haven't hard launched in marketing yet at all, but soon we're going to do a big launch."

"Paid plan used to be $5,000 a month, but we only had a couple of takers… so we dropped it down to $800 a month."

There is a process that I have used, and still use, to reignite life...

Create two timelines—6 months and 12 months—and list up to five things you dream of having (including, but not limited to, material wants: house, car, clothing, etc.), being (be a great cook, be fluent in Chinese, etc.), and doing (visiting Thailand, tracing your roots overseas, racing ostriches, etc.) in that order.

If you have difficulty identifying what you want in some categories, as most will, consider what you hate or fear in each and write down the opposite.

Do not limit yourself, and do not concern yourself with how these things will be accomplished. For now, it’s unimportant. This is an exercise in reversing repression.

Be sure not to judge or fool yourself. If you really want a Ferrari, don’t put down solving world hunger out of guilt. For some, the dream will be fame, for others fortune or prestige. All people have their vices and insecurities. If something will improve your feeling of self-worth, put it down.

Drawing a blank? In that case, consider these questions:

1) What would you do, day to day, if you had $100 million in the bank?
2) What would make you most excited to wake up in the morning to another day?

Don’t rush—think about it for a few minutes.

If still blocked, fill in the five “doing” spots with the following:

— one place to visit
— one thing to do before you die (a memory of a lifetime)
— one thing to do daily
— one thing to do weekly
— one thing you’ve always wanted to learn

What does “being” entail doing?

Convert each “being” into a “doing” to make it actionable. Identify an action that would characterize this state of being or a task that would mean you had achieved it. People find it easier to brainstorm “being” first, but this column is just a temporary holding spot for “doing” actions.

Here are a few examples:

1) Great cook —> make Christmas dinner without help

2) Fluent in Chinese —> have a five-minute conversation with a Chinese co-worker

Determine three steps for each of the dreams in just the 6-month timeline and take the first step now.

Define three steps for each dream that will get you closer to its actualization.

Set actions—simple, well-defined actions—for now, tomorrow (complete before 11 A.M.) and the day after (again completed before 11 A.M.). Once you have three steps for each of the four goals, complete the three actions in the “now” column.

Do it now. Each should be simple enough to do in five minutes or less. If not, rachet it down. If it’s the middle of the night and you can’t call someone, do something else now, such as send an e-mail, and set the call for first thing tomorrow.

If the next stage is some form of research, get in touch with someone who knows the answer instead of spending too much time in books or online, which can turn into paralysis by analysis.

The best first step, the one I recommend, is finding someone who’s done it and ask for advice on how to do the same.

The approach here is exactly right. Pairing builders with domain experts, and grounding the work in the company’s real knowledge, systems, and workflow context.

Most AI initiatives don't stall for a lack of ambition or model capability, but because the people building the tools or workflows are too far removed from the friction of the actual work.

The breakthrough happens when you combine technical builders, domain experts, and the scattered knowledge, workarounds, context behind the workflow itself.

You can’t redesign the future if you’re too far removed from the friction of the present.

Agentic AI adoption is on fire at @Uber, and it's changing the way we build, not just in engineering, but across the entire company.

Today, 99% of our engineers use AI tools. More than 70% of pull requests are attributed to local or cloud agents. And our engineers have built 2,500+ agent skills across the software development lifecycle.
Those numbers are exciting, but they led us to a much bigger question:

How do we bring agentic AI beyond engineering?

Finance. Legal. Operations. Marketing. Customer Support. HR. Procurement.

These functions run on complex workflows that are often manual, highly nuanced, and spread across dozens of systems. You can't automate them effectively by looking at process diagrams or documentation. You have to understand how the work actually gets done.

So we created something called Agentic Pods.

The idea is simple.

We handpicked ~30 of our most AI-proficient engineers (people with deep knowledge of Uber's systems) and paired each of them with a domain expert from a business function.

Then we gave every pod just two weeks.
• Days 1 – 2: Shadow the expert. Observe every step. Document workflows. Ask questions. Build intuition.
• Day 3: Prioritize opportunities based on scale, repetition, business impact, and data availability.
• Days 4 – 5: Build a working agent alongside the person doing the job.
• Days 6 – 9: Validate with several others performing the same work. Does it generalize? Does it actually make their job better?
• Day 10: Ship.

In just the past two months, we've run 16 Agentic Pods across 16 different business functions.
• Capital allocation across 150 cities: 15 hours → 30 minutes.
• Financial pacing reports: 2 days → 10 minutes.
• Marketing web quality assurance: 2 weeks → 50 minutes.
• Support workflow creation: 9,000 manual workflows → self-service automation.

The productivity gains are impressive, but what surprised us most wasn't the speed.
• It was how quickly engineers embedded in unfamiliar domains uncovered opportunities that had been hiding in plain sight.
• The biggest wins rarely come from automating one task. They come from rethinking an entire workflow. Once you redesign the workflow around AI, you often eliminate handoffs, remove unnecessary approvals, replace legacy tooling, reduce vendor spend, and dramatically accelerate decision-making.
• The workflow becomes the unit of automation - not the individual task.
• The most impactful agent skills cut across teams, orgs, functions, tools, and systems.

The biggest lesson? The best AI opportunities are rarely visible from the outside.

You discover them by sitting next to the people doing the work, understanding every friction point, and building with them, not for them.

We're now forming a dedicated team to scale this further and go deeper. They'll deeply understand the work, redesign it from the ground up, and use AI to fundamentally change how the business operates.

It's exciting times!

Clearest explanations of loops I've read so far

I will make 12% rent without owning any stocks. Here is how:-

1) I own 0 stocks of AVGO (Broadcom). The stock trades at 370.
2) Fundamentally, this is one of the best businesses in the world to own.
3) Now, I will sell a PUT option at around 280. This is 20%+ Out of the Money.
4) For this, I will be paid roughly 6% yield over 6 months. So 12%+ in 1 year.
5) Now: some of you would say: that cash secured put is a risky strategy. What if the price hits 280$. And, you are forced to buy?
6) I am okay with this. AVGO falling to 280 means, it is down 40%+ from its peak. I am happy to buy 100 stocks here. Therefore, I picked a firm like AVGO to begin with.

If the stock does not fall to this point, cool, I will collect my 12% rent in $ terms.

Most people make losses on options because they don't make it part of their core portfolio. And, neither understand how to manage risks.

If you use it sensibly (especially in good markets like the US), you can make decent cash flows.

Explains beautifully in plain language the core concept of #AI and how it works.

news.mit.edu/2026/agentic-ai-and-what-do-we-wa…

Conor Neill spent years studying why 19 out of 20 speakers lose their audience in the first sentence.

3 best ways to start a speech (worst to unforgettable):

1. 19 out of 20 speakers open the exact same forgettable way. They say their name, where they are from, and what the talk is about. But all of that is already printed on the paper in front of the audience. By repeating what people already know, you send a signal that now is a safe time to check their phone. The opening that feels safest is the one that loses the room.

2. The worst possible start is fumbling with the equipment. How much time do I have? Is this plugged in? Is the mic working? Neill says this happens constantly at conferences, and it is painful because it is often the first time the audience meets this person. They came expecting a leader in the industry, and a kid presenting on giraffes at school would have done a better job.

3. There are only three real ways to start a speech, and Neill ranks them. The same logic applies to walking into a group at a networking event. If you approach three strangers and announce your name, age, and hobbies, they walk away. The opening has to earn attention, not just deliver information.

4. The third best way is a question that matters to the audience. Not a question about you, but one that frames a problem the audience actually faces. It pulls them in because the answer is something they need, which makes them lean in to hear where you go with it.

5. The second best way is a factoid that shocks. Neill's examples: there are more people alive today than have ever died, or the energy reaching Earth from the sun every two minutes equals the entire annual energy usage of humanity, every car, every light, every air conditioner, for a whole year. A fact that forces the audience to rethink something buys you their full attention.

6. Shock facts work even better now because anyone can verify them. Given two or three minutes, the audience can Google whether what you said is true. Neill points out they trust him partly because he looks the part and has the credentials, but the facts hold up under checking. The credibility of a surprising, verifiable claim is what makes it land.

7. The best way to start is the same way you start a story for a child. Once upon a time. When Neill says those words, his daughter leans forward and engages, because we were all trained as kids to recognize when a story is coming. We also learned to recognize when a teacher is about to deliver 40 minutes that will not matter to our lives.

8. There is a grown-up way to say once upon a time. Jack Welch and Steve Jobs do not literally open with a fairytale line, but they signal a story is coming. Listen to the interesting people at a dinner table or the person holding a group of eight at a networking event, and you will hear it. Neill's own version: the last time I was in this room, someone said something to me that changed how I think about speaking. The audience immediately wants to know what was said.

9. The pause is part of the technique. After teasing that someone said something that changed his thinking, Neill can pause for 30 seconds, even two or three minutes, and the audience sits there wanting to know what it was. Creating that gap, and then holding it, is what pulls people to the edge of their seats. The tension does the work.

10. Stories are about people, never about things. If you want to tell a good story about your product, do not talk about the software. Talk about the people who built it, what they sacrificed, what matters to them. All the features and benefits are already in the document and the PowerPoint. What the audience needs is to trust you and care about you as a person, because that is what makes them decide to act.

11. Connect the topic to your own life, because in speaking we assume self-interest. Tell the story of why you joined the company, or the first time you saw someone's life changed by what you do. When you show what quality of life means to you and how your work affects a customer's quality of life, that is where the stories that connect you to the audience come from.

Codex now has more of the iOS app development loop built directly inside the app.

The Build iOS Apps plugin lets Codex view and test an iOS app in the in-app browser, open SwiftUI previews, and hot reload edits without forcing the developer to leave Codex.

I hope everyone had a great 4th of July. I know @realDonaldTrump and family did.

250 years ago we declared independence from a king who ran the colonies as a family business. In just 18 months the Trumps have made King George look like an amateur.

A $620 million Pentagon loan, the largest in the program’s history, to a company Don Jr.’s firm bought into three months before.

An Air Force drone contract to a startup the princelings took public through a golf course company they own a piece of.

The Army’s largest drone motor order ever, to a company where Don Jr. sits on the board and holds millions in stock.

A $24 million Pentagon robotics contract to the company that employs Eric as Chief Strategy Advisor.

A stake in the largest undeveloped tungsten deposit on earth, in Kazakhstan, backed by $1.6 billion in US government support.

Jared’s fund seeded with $2 billion from the Saudi crown prince, now $6.2 billion, 99% of it foreign money from Gulf governments. Over $110 million in fees collected from the Saudis alone. He negotiates American foreign policy with the governments that pay him.

$2.3 billion from crypto ventures their father regulates. More than a million people bought in and lost $2.3 billion. The money didn’t grow. It simply moved from the subjects pockets to the crown’s coffers.

And the next one is already drafted. A proposed ATF rule that will allow guns to be shipped straight to your front door. The government’s own estimate is 3.3 million home gun deliveries a year. Don Jr. sits on the board of the online gun megastore built to cash in. He holds 300,000 shares.

And that’s only the fraction they’ve allowed us to see. Not one subpoena served. Not one search executed. Why hide anything when you own the investigators?

Me? They searched a laptop for six years. Federal prosecutors. Grand juries. Subpoena power. Congressional hearings. They found nothing. I made about $200k a year selling paintings when my Dad was President, and they made my paintings part of an impeachment inquiry.

For six years they’ve asked Where’s Hunter? What about the laptop?

Wrong questions. The right one is 250 years old. Does America belong to a family?

They’ve given their answer. Long live the King.

Btw, this guide was written in workbench.md/, which is crazy powerful Fable accelerant.

I share more in the guide, but it’s basically a superpowered agent-first workspace that allows multiple agents to chat, collaborate, keep you updated, etc.

Huge thanks to this Croatian supporter for giving me the opportunity to create a GIF that I will use on here almost daily.

Nebius will be a TRILLION dollar company and here is exactly why (Save this).

Brad Gerstner's Altimeter said on camera that they are invested in ClickHouse, and explained exactly why in one sentence: "If you're in the data infrastructure layer, then token consumption is driving a lot more consumption of your basic services."

The flip side of that point is equally important.

Gerstner added that the closer you are to a point solution, a single use app built on top of AI, "that feels like you're on the front of the conveyor belt heading toward the guillotine."

Models get better, apps get commoditized and the companies that own the foundational infrastructure that every AI application must run through keep compounding.

ClickHouse is exactly that foundational layer.

It is a real time analytical database engine originally built inside Yandex, optimized for the exact query patterns that AI agents, LLM observability pipelines, and machine learning infrastructure generate, massive write volumes, complex aggregations, and sub-second response at scale.

It processes hundreds of billions of rows per second, serves over 2,000 enterprise customers including Cloudflare, Uber and ByteDance, and grew 300% in a single year.

In January 2026, a $400 million Series D valued ClickHouse at $15 billion more than double its $6 billion valuation just eight months prior.

Here is where Nebius comes in.

Nebius holds a 28% stake in ClickHouse, an asset that traces back to its Yandex origins.

At ClickHouse's current $15 billion valuation, that stake is worth approximately $4.2 billion, sitting largely unrecognized on Nebius's balance sheet while most market coverage focuses entirely on the AI cloud business.

A ClickHouse IPO, which the company is actively positioning toward, would force the market to mark that position to full public market value for the first time and could alone reprice Nebius meaningfully.

But that hidden asset is just one layer of the bull case.

The core AI cloud business just printed 684% year over year revenue growth, $399 million in Q1 2026 against $50 million a year prior.

AI specific revenue grew 841% and now represents 98% of total revenue.

The moat underneath those numbers is 3.5 gigawatts of secured power capacity, a $27 billion five year contract with Meta, a $2 billion strategic investment from Nvidia, and a Microsoft partnership ramping to full run rate in 2027, all stacked on top of a ClickHouse stake that the market is still not fully pricing in.

Long Nebius and make sure to follow me @MelvinInvests for more underlooked AI oppurtunities.

ANTHROPIC HAS AN OFFICIAL PROMPT LIBRARY FOR CLAUDE CODE

Most people have never opened it.
So they write every prompt from scratch.

It is copy-paste, tagged by task and by role,
across the whole lifecycle:

discover → design → build → ship → operate

Straight from the page:

> what would break if I deleted this helper?
> plan this refactor, list the files, do not touch code yet
> write tests for this, run them, fix what fails
> the test is failing, find out why and fix it

This is not a cheat sheet.
It is a map of what Claude Code already does for you.

Bookmark it before you forget it exists.

The Invisible Metric in Startup Building: "Founder Form"

When Messi goes five matches without scoring a goal, or Virat Kohli goes through a dry spell, the sporting world doesn’t assume they’ve suddenly forgotten how to play. We don't demand they be permanently benched or declare their career over.

Instead, we use a very specific word: Form.

We recognise that sports require immense psychological, emotional, and physical intensity. "Form" fluctuates. It has peaks, valleys, slumps, and flow states.

Yet, in the hyper-rational, metric-driven world of startups, we treat founders like machines. We expect them to ingest capital and seamlessly produce flawless strategic execution 365 days a year. If a quarter misses expectations, a product launch bombs, or a key hire walks out, the immediate reaction from boards, markets, and sometimes even fellow co-founders is panic, blame, or a sudden loss of faith.

Over the last 19 years as an entrepreneur and through supporting hundreds of founders in their journeys, I’ve realised one undeniable truth: Founder Form is real. And ignoring it can destroy perfectly good startups.

The Anatomy of the Two States: The Slump vs. The Flow
Building a company demands an elite athlete's intensity. Because it relies heavily on human judgment under extreme uncertainty, founders inevitably move through distinct cycles of form:

When you are in "Bad Form" (The Slump): Every strategic bet feels slightly off. You make a hiring mistake, a key client churns, your pitches don’t quite click, and your decision-making feels sluggish or over-analyzed. You are working just as hard - often harder, out of sheer desperation - but your timing is gone.

When you are in "Good Form" (The Flow State): Everything you touch turns to gold. You make a gut-call on a product pivot and it works flawlessly. A casual coffee meeting scales into a massive strategic partnership. Investor meetings go super smoothly. Your energy is infectious, and the team rallies without effort.

When you are in a slump, it feels like nothing will ever work again. When you are in flow, it feels like you can never fail. Both illusions are dangerous, but the slump is where companies break.

The Danger of Asymmetry in Co-Founder Pairs
The ultimate test of a co-founder relationship isn't how you celebrate wins together; it’s how you handle a divergence in form.

In a multi-founder setup, it is incredibly rare for all partners to be in peak form simultaneously. The danger arises when Co-Founder A is in a legendary flow state, while Co-Founder B is grinding through a deep slump.
If they don't understand the concept of "form," this asymmetry breeds deep resentment. Co-Founder A starts thinking, “I’m carrying the entire weight of this company.” Co-Founder B, already drowning in self-doubt, feels isolated, judged, and increasingly anxious - which only prolongs the slump.

Great co-founder relationships survive because they view performance through the lens of a team sport. When your partner’s timing is off, you don't call them incompetent. You step up, cover the field, take the heavy shots, and give them the breathing room to find their rhythm again. You do it gladly, knowing that next quarter, the roles might be reversed.

A Message to Investors: Stop Managing to the Daily Scorecard
To the investor community: when a founder is in a slump, adding institutional pressure or questioning their fundamental capability is the equivalent of a manager screaming at a struggling athlete from the sidelines. It doesn't fix their footwork; it merely tightens their grip on the bat.

Seasoned investors back the person, understanding that form is temporary, class is permanent.

If a founder who has previously delivered high-quality execution hits a wall, the goal shouldn't be to micro-manage the metrics. The goal should be to help them remove the noise so they can find their baseline.

The Founder’s Playbook for Regaining Your Form
If you are a builder currently grinding through a slump, remember how elite athletes get back into the runs:

Go Back to Basics: When a batsman loses form, they spend hours in the nets focusing on basic footwork, not hitting sixes. Stop trying to solve the entire macro crisis today. Focus on small, undeniable execution wins. Go talk to three customers. Fix one internal bottleneck. Rebuild your momentum incrementally. Confidence will grow with action, shrink further with idleness.

Manage the Fatigue: Founders tend to respond to a slump by doubling down on work, leading straight to burnout. But a chaotic mind cannot produce elite execution. Step back, rest, and disconnect briefly to regain perspective.

Trust the System: Accept that market forces and luck play a massive role in early-stage startups. If the core capability is there and you keep showing up to the crease with clean mechanics, the flow state will return.

Startups are a game of endurance. We can’t expect builders to be flawless algorithms, and we must support them like the elite psychological athletes they are.

Give your co-founders and yourself the grace to find form again. It’s just a matter of time before they find it.

🚨 Luka Modrić on Croatia’s controversial last-minute disallowed goal against Portugal:

🗣️ “This is football. Not a courtroom, not a lab where we freeze every frame and argue over centimetres.
Tonight we gave everything against a very good Portugal team. We were still fighting deep into stoppage time. The boys kept believing, kept pushing, and when that ball went in through Josko we thought we had it — equaliser, extra time, everything still possible.
Then VAR comes in and takes it away because of a touch earlier in the move. I respect the officials, I really do. But the rule is clear and obvious error. Was this one? These little things, these marginal calls where players are fighting for every inch… that’s football. That’s what defenders and attackers do every single day.
If we start ruling out goals like that in the last seconds because of a split-second touch or a shoulder or a toe, then what are we left with? The game loses its soul. The emotion, the chaos, the moments that make people fall in love with football — they get taken away by technology that was only supposed to fix the obvious mistakes.
We accept that sometimes the ball doesn’t go your way. We’ve done it our whole careers. But when the decision feels like it rewrites the last chapter of the match instead of just correcting something clear, it hurts. Not just us in the dressing room, but everyone who was watching and living every second with us.
Portugal deserved to go through, they’re a strong side and they showed it. But nights like this make you wonder where the game is heading. We play with our hearts, we fight until the whistle, and then one review decides everything.
That’s not protecting football anymore. That’s changing it into something else.”

I have met no one in Silicon Valley whose thesis work was more similar to my own academic work than Dario amodei

So color me surprised when I learned Anthropic sincerely stated that fable yapping about biology is dangerous

Their CEO is capable of understanding exactly why that’s BULLSHIT without better biological data.

Literally more capable of understanding what I am saying than anyone else I’ve met in his position.

I don’t buy that it’s a genuine error and it speaks volumes about this man.

UPDATE: President Trump filed a March 2nd purchase of Moderna stock.

On June 18th, the FDA voted to recommend Moderna's mRNA flu vaccine.

$MRNA has now risen 46% since March 2nd.

Sergey Brin rarely speaks publicly. He sat down for an unscripted Q&A on Frontier AI.

He admits even the people building these models do not fully understand what they have created:

1. All the specialized AI models are converging into one. Google used to need separate models for different scientific problems. Now the main Gemini models are becoming state-of-the-art for math and other scientific questions at the same time. Brin says he would not have predicted this convergence at the outset, and watching it happen has been incredible.

2. Training an AI on one skill mysteriously improves unrelated skills. This is the concept of transfer. Train a model on coding, and its math reasoning gets better, and vice versa. Teaching it to process images can improve its ability to think through geometric word problems. The capabilities bleed into each other in ways nobody fully engineered.

3. Even Sergey Brin does not know how to prompt these models. He says he is genuinely confused about what level to prompt at. Do you tell it to debug a specific chunk of code, or ask it to write a better neural net training algorithm, or just say, " What should I do today. He admits that even at Google, they do not know exactly where the edges of Gemini's capabilities are.

4. One of the biggest leaps in AI came from the dumbest sounding trick. Chain-of-thought prompting is just telling the model to think step by step before giving your problem. Brin says it seemed like the dumbest thing ever, and there was no obvious reason it should work. But it did, and it spurred a significant increase in AI capability. Some of the most straightforward requests turn out to unlock the most.

5. Brin would not modify his own biology for today's AI. Asked how humans can keep up with the accelerating bandwidth of models, he acknowledged neural links and direct brain connections are being pursued. But he said he would personally wait for the technology to mature a lot before doing anything to change his biology. Today's models do not justify it.

6. Super intelligence does not mean solving the impossible. An audience member argued that true super intelligence would mean solving NP complete problems like the travelling salesman. Brin pushed back. Most computer scientists believe P is not equal to NP, which means no algorithm can reliably solve those problems optimally, and it does not matter how smart the AI is. Impossible stays impossible. Super intelligence just means being smarter than humans.

7. Computers mastering a skill has never stopped humans from pursuing it. Deep Blue beat Kasparov at chess in the 1990s, and people kept playing chess. After AlphaGo, the human game of Go advanced dramatically, and the players who lost to it became vastly better. Brin's point: AI does not retire human ambition in an area; it often pushes the state of the art and pulls people up with it.

8. Brin thinks something close to transformers could get us to AGI. Asked directly if transformers are sufficient, he said his guess is yes, largely because they have proven weirdly flexible, working for image and video far beyond their original text purpose. But he was careful to note they have quietly changed a lot along the way and are not the same architecture as the original transformer paper.

9. AGI means two different things, and one requires understanding the physical world. Brin personally thinks of AGI as AI that can improve itself. But he concedes others define it as AI that can do anything a person can, and he thinks they are probably more correct. To do everything a person can, the AI must understand and interact with the physical world, which is why world models, and robotics, become essential.

10. Inside Google, they now use the AI to build the AI. Brin says the team has shifted a lot of energy toward having the AI do things like monitor training runs and generate its own training data. You start to use the tool to build the tool. That is most of what he spends his time on now, what he calls the self-improvement game.

11. Brin is unusually candid about where Google trails its competitors. He admits Google was a little late to focus deeply on coding. He says Gemini 3.0 and 3.1 were on top across the board six months ago, but other labs have since made strides, particularly in coding. He gives a competitor's model the edge now on deep coding and overnight tasks, while pitching Gemini's flash model as far faster for rapid interactive iteration. hindsight, he says, is that they should have focused on code earlier.

12. He sees his own role as a rabble-rouser, not a manager. Brin is honest that delivering Gemini is Corey and Demis's responsibility, not his. he describes his job as poking and prodding the team, asking, are you really doing that, reminding them of priorities they might be missing and ideas they are not paying enough attention to. He admits this is sometimes a little disruptive.

13. Confidence comes from ignoring the monthly temperature. Brin says if he judged Google's position every month by which competitor just shipped a model, he would lose his confidence very quickly. Instead, he watches the longer arc. Things shift around constantly; one lab leads on one thing, another pulls ahead somewhere else, and he feels good about where Gemini actually is despite the day-to-day noise.

I have been trading for five decades, primarily using charts. I have found nobody better as a pure Edwards and Magee devotee than Aksel Kibar. He is the chartist I most trust for accurate chart analysis

As someone still trying to learn how to read code this is great! Installing the explain-diff skill asap

And now for the good news...

Just about any reasonably healthy 50 year-old can train their body to be fit enough to push their VO2max north of 50.

And yet...

Only ~5% of men and ~1% of women will.

Be a part of that few percent.

Your future self will thank you.

Launching Raaga V1 by Vakyam AI.

Natural, expressive speech for Indian languages.

Frontier-level quality at ₹0.75 per 1K characters (~per min).

Try it now on our playground.

Every product company is facing the same dilemma right now: Do you try to be the agent your users open every day, or do you accept they already live in Claude/Codex and power that agent instead?

Wrote about how to think through it and what building an MCP business might entail

If you’re even remotely interested in fitness (actual fitness) and how to train correctly for endurance and longevity sympathetically, you must follow Alan.

I had a $400 Wagyu ribeye for lunch today.

I didn't pay for it.

An enterprise account executive from a tier 1 cybersecurity firm paid for it.

He's been trying to sell me a cloud-native endpoint detection platform for 8 months.

We don't need a cloud-native endpoint detection platform.

We don't even have endpoints.

Half of our workforce is using refurbished laptops from 2014 that are physically incapable of running his software.

But I told him we're "evaluating"

That phrase means absolutely nothing.

But in B2B sales, it's the equivalent of ringing a dinner bell.

He's bought me 8 lunches this year.

He asks about our migration timeline.

I stare out the window, sigh deeply, and whisper about decentralized integration bottlenecks.

He furiously takes notes and orders another bottle of sparkling water.

My total compensation package is $200K.

But my caloric ROI is incalculable.

Next week I have a pitch meeting with an AI analytics startup.

I checked their Series B funding round before agreeing to the meeting.

They have $40M in venture capital burning a hole in their pocket.

I'm going to let them buy me omakase.

Then I'm going to tell them our legacy infrastructure is experiencing packet loss and we can't deploy until 2029.

Corporate America is just a vast ecosystem of free meals if you know how to string along desperate account managers.