૮༼⚆︿⚆༽つ junior gatekeeping engineer

It doesn’t matter if your government is 🇹🇱 corrupt 🇮🇩 corrupt 🇵🇭 corrupt 🇸🇬 corrupt 🇧🇳 corrupt 🇲🇾 corrupt 🇹🇭 corrupt 🇲🇲 corrupt 🇰🇭 corrupt 🇱🇦 corrupt 🇻🇳 corrupt

Honestly, the more I think about it, a lot about learning and growing in computer science is just discovering which things are secretly the same underlying thing (e.g. how there are monads everywhere for those with eyes too see them)

lesson learn: don't let ai rewrote ur gh issue cuz it may treat the analysis as evidence with 100% confidence. write ur bug report in ur own words so agent can treat it as a hypotheses. issue report should be like an observation diary.

unpopular opinion, less code is still good, replacing well-documented/tested libraries with what-will-become unmaintained codegen is not better

my fav talk when i think american idea of entrepreunership is broken

🚨 THE ENTIRE AI BOOM MIGHT BE BUILT ON FAKE REVENUE. Latest corporate filings show that OpenAI and Anthropic alone make up over half of the entire $2 trillion future cloud backlog held by Microsoft, Oracle, Google, and Amazon. This massive pipeline is actually being created through a circular accounting trick called a round trip revenue loop. But how it works ? A tech giant gives billions of dollars to an AI startup as an "investment". But hidden in the contract is a strict rule forcing the startup to hand that exact same money straight back to the tech giant to rent their computer servers. Look at the documented case of Microsoft and OpenAI. When Microsoft invested $13 billion into OpenAI, it didn't just give them cash; it gave them "cloud credits" to use Microsoft servers. OpenAI used those exact credits to train its AI models, and Microsoft then turned around and recorded that server usage as brand new "cloud revenue" from a customer. The tech giant is literally paying itself with its own money and calling it a sale. This is why OpenAI’s annual cloud bill has ballooned to over $60 billion, double its actual revenue of $25 billion, kept alive solely by this recycled funding loop. Anthropic runs the exact same play, spending $2.66 billion on Amazon Web Services in just nine months, which was basically 100% of all the money it earned at the time. This manufactured demand triggers a second accounting trick where tech giants book massive paper profits. Every time a startup gets a higher value from a new funding round, the tech giant updates the value of its investment on its books and counts that unearned paper gain as direct profit. In Q1 2026, Alphabet reported a record $62.6 billion profit, but $28.7 billion nearly half, was just a paper markup on its Anthropic investment. In the same quarter, Amazon reported $30.3 billion in profit, but $16.8 billion of it was just an Anthropic paper gain. While Amazon reported record profits, its actual free cash flow collapsed 95% to just $1.2 billion because it had to spend $44.2 billion in real cash to build physical data centers. This has created a massive danger where these giant companies rely heavily on just one or two unstable startups. Microsoft has 49% of its $627 billion future backlog tied to OpenAI, while Oracle has an incredible 54% of its entire $553 billion pipeline relying on OpenAI alone. This perfectly mirrors the 2001 dot-com crash when Global Crossing and Qwest Communications swapped identical fiber-optic network capacity with each other just to book fake sales. Qwest had to erase $1.4 billion in fake income, and Global Crossing went completely bankrupt. The only difference is that the dot-com swaps were illegal, but today's AI loop is fully legal under current accounting rules. This legal loop inflates tech company stock prices, forcing automatic retirement accounts and index funds to buy even more of these tech stocks. It is a self feeding loop where investments, sales, and stock prices all go up on paper without the AI technology ever making real cash profits.

Blackout Sumatera, PLN minta maaf Enak amat minta maaf, kami aja kalau telat bayar kalian cabut listriknya! Pagii pagi bikin kesel bapaknya

Agents don't need types. They're perfectly capable of pulling off incredible refactorings without. Give them a linter and a test suite, and you have all you need. Token efficiency is where it's at.

Agents don't need types. They're perfectly capable of pulling off incredible refactorings without. Give them a linter and a test suite, and you have all you need. Token efficiency is where it's at.