ddcc

[Sunil Gurjar, CFTe @sunilgurjar01]

I have watched this clip multiple times, and it's worth revisiting.

A masterclass in thinking about India versus the rest of the emerging market universe.

Pure gold from Sachee Trivedi. 🔥

(Credit - Moneycontrol)

[ddcc @MisclnX]

@dostoevesque Dm the link bro

[Compounding Dividends @CompoundingW]

Dupont Analysis

[Shubh @TheSuperEng]

The best FREE YouTube courses for backend engineering

[Compounding Dividends @CompoundingW]

Financial reports

Understanding financial reports means you understand a business

Here is what you'll learn:
• Consolidated financial statements
• The balance sheet
• The income statement
• The statement of changes in shareholders' equity
• The statement of cash flows
• Audit Reports
• The long view
• Selecting stocks

Source: Merrill Lynch

[Śrēyān Singh @agniyuta]

Yup Lord Rāma is निजबोध रूपं who is of the nature of pure consciousness 🪷✨

– Adhyātma Rāmāyaṇa, Bāla Kāņda, chp. 1 verse 43 📖

Maa Sītā said to Hanuman ji :

[vyom @vy0mbhatia]

"A loonshot is something nobody has dared to do before. A goal so ambitious that you don’t even know if its possible."

-- naman pushp of airbound (substack, 2022)

i am 23 now. i have one skill, it's the ability to tell stories. i want to talk about indians building on research.

[Harri @Harriwxu3]

Math class just got interesting! Forget old methods, this is how to *really* teach kids division using number bonds. It's easier than you think!!?

[Veloria 🌊 @veloriahq]

“𝘛𝘩𝘦 𝘮𝘰𝘴𝘵 𝘵𝘦𝘳𝘳𝘪𝘧𝘺𝘪𝘯𝘨 𝘧𝘳𝘦𝘦𝘥𝘰𝘮 𝘪𝘴 𝘥𝘪𝘴𝘤𝘰𝘷𝘦𝘳𝘪𝘯𝘨 𝘵𝘩𝘢𝘵 𝘦𝘷𝘦𝘯 𝘺𝘰𝘶𝘳 𝘴𝘶𝘧𝘧𝘦𝘳𝘪𝘯𝘨 𝘪𝘴 𝘺𝘰𝘶𝘳 𝘰𝘸𝘯 𝘧𝘢𝘶𝘭𝘵.”

— 𝘍𝘺𝘰𝘥𝘰𝘳 𝘋𝘰𝘴𝘵𝘰𝘦𝘷𝘴𝘬𝘺

[ཤོཀཱ།/Jwaari Shauka @Shauka74]

Sarsong Darboche is celebrated in Changru village after Purnima during the month of Saka Dawa. The Rang people of Changru host the Darboche.
Credit - insta imagexfile

[Essential Mastery @EssentialMastry]

Dostoevsky was right; “Every self-betrayal is a sin. Whenever you go against your nature, your body reminds you.”

If you spend enough time with anything, you start liking it, even sadness. So let’s choose people and spaces that truly elevate us. Your peace is worth it.

[🍂 @Lovandfear]

What a privilege

[Anurag Shukla @Anuraag_Shukla]

The Arthaśāstra may contain the earliest documented state-run rainfall measurement system.

Long before Korea’s 15th-century Cheugugi and Europe’s 17th-century gauges, it linked ecology, agriculture, taxation, and welfare through evidence-based governance.

[عبدالله عوض @Abdullah_1639]

الحصان الذي يعرف وجهته، لا تُشتته الغابة.

[Ayussh @Ayussheth]

Thinking of starting a community for people who want to learn hardware, work in hardware, or just enjoy tinkering with things in general.

Reply to the tweet if you want in.

[sphinx @protosphinx]

Chinese founders are usually:

- engineers
- party members
- capitalists

In that order.

So when they build or acquire a company, maximizing shareholder value is not the first objective. The first objective is acquiring know-how and industrial capability.

The mindset is: "we should know how to build this thing in China for the simple reason that my civilization needs to learn this sooner or later and i don't care about consequences or optics - if it looks like stealing IP so be it, I don't have to explain..."

The only people judging you are in your local party HQ.

If you’re a credible founder in China, you can go to a local party chief and say: "I need x engineers, land, and some starter funds to build this widget company"

And if the state thinks the industry matters, you’ll get the best resources in the province, industrial land and enough support to get going. The rest is up to you.

Many, many fail. Like most people think they would be successful with capital - go to China and see. You get everything - land, capital, people and even then the success ratio is like 1-5%...

OG American founders were also engineer-first. Bill Hewlett and David Packard built HP as engineers. Same with a lot of old American industrial giants. But over time those founders exited and the boards got taken over by pure financial operators focused entirely on maximizing quarterly shareholder value.

A single generation of this mentality hollowed out the entire American industry. Product-first founders like Elon Musk exist today because there was a generational demand for good engineering lead founders.

Indian boomer founders meanwhile were always capitalist-first from day one. Not even saying that negatively. Many come from communities that are insanely optimized around capital survival and allocation. That’s a real skill developed over centuries.

But the downside of that mindset is that they were rarely engineer-first or product-first EVEN if they were engineers by training. They were always capitalist first.

And that's very reasonable. They're on their own. Nobody has their back. They need to perform or die.

So when an Indian conglomerate acquires something like Jaguar, the instinct becomes:

- optimize margins
- reduce costs
- extract shareholder value

But if you don’t deeply understand first principles of car manufacturing, how much value can you really compound long term ? So companies get handed to hired professionals and MBA operators. The exact same class of people that helped hollow out American industry.

Now America is slowly realizing pure financial capitalism can become self-destructive because eventually the spreadsheet people cannibalize the actual industrial base in pursuit of EPS.

India already lives in that reality. Infosys is a good example. A company effectively consuming itself to maintain quarter-on-quarter performance without aggressively building the future.

And as I said they’re not even wrong. Anyone would do the same unless the system is realigned for long term incentives.

Who in India actually has your back if you miss numbers for 2-3 yrs while investing heavily into long-term capability ? Tesla survived because retail investors and the American public effectively backed Elon Musk through a decade of chaos and losses.

Toyota delivers 6-7x of Tesla's profit EVERY QUARTER but Tesla wins because try posting and see Tesla retail investors explaining you the future of automobiles.

Indian scarcity markets can't and won't tolerate that kind of long-duration industrial gamble. Its a 3k gdp/capita country nobody has time for long term nonsense plus who know who's grfiting vs being serious...people talk about nationalism then take your money and run.

China solved this by
- serve the party
- align with state goals
- stay below the radar and build

the system will protect you while you build.

In India you are on your own.

- manage the regulators
- manage capital - which is very expensive
- manage your own power/infra
- deal with corruption
- manage untrained talent

All of that becomes a massive tax on operations.

Nobody has the time to do any long-term thinking. Any anyone who does that would be eaten alive by those who optimize for survival.

[Curious Minds @CuriousMindsHub]

The cycles of Overthinking

[Joe Reeve - 🇬🇧/acc @isnit0]

My brother-in-law runs his own data center/GPU farm at home.

Currently makes him ~$3k/month profit. 30% solar powered. Aiming to get to 60% by end of this summer which will increase profits significantly (mostly down to adding batteries, not panels), then will buy more GPUs.

He sells the compute via some 3rd party service that takes a cut. Apparently a lot of ML/rendering workloads.

You can just do stuff!

[𝑺𝒂𝒏𝒅𝒉𝒚𝒂𝒂'𝒗 @vedicvenus_]

The 8-1 rules for 75 days and see the difference.

[Alex Xu @alexxubyte]

An AI agent can be thought of as a simple While-loop.

It uses an LLM to select an action, executes that action, evaluates the result, and repeats the process until the task is complete. Let’s take a closer look at each of these components:

Brain: The LLM is the core. It reads the situation, thinks, and decides what to do next. The big shift from chatbot to agent: the model isn't writing text anymore, it's making choices.

Planning: Hard tasks need more than one step. Agents break them down using methods like Chain of Thought (think step by step), Tree of Thoughts (try options, pick the best), or
Reflexion (learn from mistakes and retry). Planning turns a fuzzy goal into clear actions.

Tools: An LLM without tools is a brain in a jar. Tools are functions the model can call, like web search, code execution, APIs, files, or browsers (often using the MCP standard). The model requests a tool, the system runs it, and the result comes back.

Memory: Without memory, every turn starts from zero. Short-term memory is the context window. Long-term memory lives in vector stores, files, and knowledge bases. When the window fills up, agents summarize old turns and carry the summary forward.

Loop: All four pieces work together in a cycle. The agent looks at the current state, decides what to do, uses a tool, sees the result, and repeats. It keeps going until it gives a final answer.

Guardrails: Not strictly anatomy, but important. Sandboxing, human checks, token limits, output validation, and scope limits keep autonomy from turning into expensive chaos. The more autonomy you give, the more these matter.

Over to you: when you build an agent, which of these five takes the most work to get right?