Taikhoom10

I just would like to start off and say i really respect Zuck and think he is truly one of a kind, and he really has impacted the world in a great way, with facebook and its other companies all under META. While one could go on about his greatness and accomplishments, ignoring his mistakes would do nobody justice. Today i want to really talk about capital allocation, and how that relates to META, which i believe a lot of you know about already.

I really belive that a CEO has three major tasks year in year out -

Operations

Investor Relations

Capital Allocation

Zuckerberg can do the first two all right, but his track record for the number three is infamous in the wrong way. I will Bring up two famous instances this has been evident. But first Lets talk about capital allocation.

So capital allocation is the activity of attempting to allocate capital in different areas of one’s business. This can look very different based of the complexity of the business. One can only begin to think the different areas where capital could be allocated at places like Google. Allocating capital correctly or incorrectly can be very the much the difference between great returns, and bankruptcy.

So now we look at the acquisition of Oculus, a big mistake, the recent AI frenzy and crazy hiring, and then the freeze. Essentially, everyone has their own circles of competence. For Zuckerberg, that circle of competence does not include capital allocation. If he is to actually lead META in the future long term, that is something he will need to incorporate in his circle of competence.

Everyones building an AI company these days Every pitch deck leads with AIpowered every startup claims to be the next ChatGPT for X and venture capitalists cant stop talking about the artificial intelligence revolution But heres what theyre missing while everyone crowds into the same overhyped pond the real money is being made in boring businesses that solve unglamorous problems The Government Forms Gold Mine Let me tell you about a company that perfectly illustrates this principle While thousands of entrepreneurs were building GPT wrappers and AI chatbots a small team noticed something everyone else ignored people applying for government assistance were drowning in paperwork The process was bureaucratic hell—confusing forms, unclear requirements, and endless back-and-forth with government offices. Most tech entrepreneurs wouldn't give this problem a second glance. It's not sexy. It won't make TechCrunch headlines. It doesn't involve machine learning or neural networks. But guess what? That "boring" form-filling software is now generating $30 million in annual revenue. This is the essence of "fishing where the fish are, not where the fishermen are." While everyone else battles over the same crowded markets, smart entrepreneurs find untapped problems with real paying customers. Why Boring Usually Beats Buzzy The AI gold rush reminds me of every other tech bubble. Remember when everything was "blockchain-powered" or "mobile-first" or "social-enabled"? The companies that survived those hype cycles weren't the ones chasing trends—they were the ones solving real problems that happened to use the technology. Today's AI companies face three fundamental problems: The Commodity Trap: As AI capabilities become more accessible, competitive moats disappear. Your AI chatbot for lawyers looks remarkably similar to everyone else's AI chatbot for lawyers. The Hype Hangover: When the AI bubble deflates (and it will), investors will demand actual profits, not just impressive demos. Many current AI companies have no clear path to profitability. The Dependency Risk: Building your entire business on rapidly evolving AI models means you're one API change away from obsolescence. How to Find Your Boring Gold Mine Finding these overlooked opportunities isn't luck—it's a systematic approach to problem identification: Start With Your Own Pain Points The best business ideas often hide in your daily frustrations. What processes make you want to scream? What tasks eat up hours of your time for no good reason? If it annoys you, it probably annoys thousands of other people too. Mine Your Network Your friends, family, and colleagues are goldmines of business ideas. Ask them: "What's the most frustrating part of your job?" "What takes way longer than it should?" "What would save you hours every week?" Listen for patterns—if multiple people mention similar problems, you've found something worth exploring. Question Everything Manual In 2025, if someone's still using spreadsheets to track important business processes, there's probably an opportunity. If people are printing forms, filling them out by hand, and faxing them back, there's definitely an opportunity. Look for workflows that seem stuck in 1995. Follow the Complaints Reddit, Twitter, and industry forums are filled with people complaining about broken processes. These complaint threads are basically free market research. While flashy startups fight for attention, boring businesses enjoy several unfair advantages: Less Competition: Most entrepreneurs chase shiny objects, leaving mundane problems undersolved. Sticky Customers: Businesses that solve operational headaches create deep integration points that are hard to replace Predictable Revenue: Boring problems tend to be ongoing problems, leading to subscription revenue rather than one-time purchases Lower Customer Acquisition Costs When you solve a real pain point in an underserved market customers find you through word-of-mouth

Hey HN, Tommorow, or maybe this weekend, GPT Five Releases. I remember back in 22 when Chat Gpt based of gpt 3 was released. The world went bezerk on a llm, and 3 years later the world is AI obsessed. I cannot tell you if this is a good thing. Before i move on i am all for the advancement of technology for the betterment of humanity. Who isn't? And personally i am also not worried at all about "AI" taking jobs. New jobs will be created i am sure of it. What i am worried about is Super Intellgence. And you might think i am stupid or silly for being worried, yet if i think i understand the concept of it correctly in essence a thinking computer that can make decisions on its own and is smarter than all of humanity. This may be a bit on the sci fi edge so here is the technical description : an AI that surpasses all humans intellgence in all domains. Now one might point out that super intellgence is not even here, why worry about something that doesnt exist. And while that is true i find it hard to beleive that people do not think at the pace AI is going that sometime in the next decade or so, maybe more that Super Intellgence will be created. My problem with this is that why are we purposely building something that surpasses us. If the answer is China, i just do not think that is good enough. As well as what is a humans role at that point. Before that we were by far the dominant specices why create something more intellgent that could very well end humanity as we know it. Why take that risk, why? I know in the end i have no control over this, yet i just want to know why one should pursue creating Superintellgence.

Hey everyone, i just wanted to share some of the lessons i have learned from working at startups and building my own, soya. Feel free to add or critique anything.

Build and launch fast, charge your customers and assess the demand

Interview potential users before building, understand the problem you are solving deeply

Do not buy into conventional wisdom

Think from first principles, the best solution is rarely the obvious one.

VC isn’t always the path, again don’t buy into conventional wisdom

Talk to your users and iterate accordingly

You don’t need to hire a ton, often small is better and more productive

Buy into Paul graham, Steve blank and others

Always learn from your failures.

Iterate, pivot if necessary

Find market gaps, fill them in. Aka identify opportunities

Be delusional yet realistic at the same time

Constantly test new things, break things move fast.

Learn from your users, understand how they are using your product.

Don’t get obsessed with adding features, start with doing one thing really well and then adding features on top of that.

When marketing never do ads, terrible conversions. Ideally if you build a really great product your users will do the marketing for you.

Build and launch fast, charge your customers and assess the situation.

Talk to customers, understand the problem you are solving deeply

Do not buy into conventional wisdom

Use first principles

VC isn’t always the path, again don’t buy into conventional wisdom

Talk to your users and iterate accordingly

You don’t need to hire a ton, often small is better and more productive

Buy into Paul graham, Steve blank and others

Always learn from your failures.

Iterate, pivot if necessary

Find market gaps, fill them in. Aka identify opportunities

Be delusional yet realistic at the same time

Constantly test new things

Learn from your users, understand how they are using your product.

Don’t get obsessed with adding features, start with doing one thing really well and then adding features on top of that.

When marketing never do ads, terrible conversions. Ideally if you build a really great product your users will do the marketing for you.