Shashank ಕುಮಾರ್ शंकर

currently product | ex-software engineer | photography. Tweets my own.

[Gems_of_Bharat @Gemsof_Bharat]

Anime is the best method to bring Indian legends on the big screen.

Clean dialogues, Characters having exact traits as described in our scriptures.

[Shashank ಕುಮಾರ್ शंकर @sshank_]

@ved_a thanks for the work. Did my part sharing in family groups to crowdsource.

[Shashank ಕುಮಾರ್ शंकर @sshank_]

@karpathy Another intriguing aspect of using voice prompts is that I become incredibly conscious of my words, even though I know the LLM can comprehend my rambling. This awareness has also enhanced our communication, making our real-life conversations more concise and precise.

[Jason Zook @jasondoesstuff]

Welp, what a difference a month makes:

- Fable 5 for initial plan
- Opus 4.8 for any UI work
- GPT-5.5 for any code
- Fable does review/testing

WAY less back and forth.
WAY more edge cases handled.

Wild what changed in 30 days.

[Bryan Johnson @bryan_johnson]

This is it.
Everything learned spending millions on longevity.

From: Your Immortal Unc and Auntie.
To: Our Immortal nieces and nephews.

0. Sleep is the world's most powerful drug.
1. Be in your bed for 8 hours
2. Same bedtime every night, any time before midnight
3. Don’t eat right before bed
4. Calm foods for dinner
5. No screens 1 hour before bed
6. Avoid added sugar (be aware it’s in everything)
7. Avoid all things in an American convenience store
8. Avoid fried foods
9. Shoes off at the door
10. Eat whole foods, particularly veggies fruits nuts legumes berries
11. Walk a little after meals or air squats
12. Get your heart rate high routinely
13. Lift heavy things
14. Stretch daily
15. Water pik, floss, brush, tongue scrape, morning and night
16. Make an effort to drink water
17. Get sunlight when you wake up (UV is low)
18. Protect skin in midday sun
19. Stand up straight
20. See at least one friend once a week
21. Avoid plastic where you can (in all things)
22. Circulate air in rooms
23. When stressed, breathe, learn to calm your body
24. Go to the dentist
25. Avoid sitting for long times
26. Protect your hearing, the world is too loud
27. Alcohol is bad for you
28. Finish coffee before noon
29. Avoid bright lights after sunset
30. If obese, look into a GLP
31. Sleep in a cold room
32. Texting while driving is dangerous
33. Turn off all notifications
34. Limit social media use
35. Don’t smoke anything
36. If you struggle to sleep, read a physical book before bed
37. 1 hour before bed have a calm wind down routine: bath, read, light walk, listen to music
38. The body is a clock and loves routine. Have a daily morning and evening schedule.
39. Avoid long distance travel where you can
40. Baby steps first: incorporate new things slowly
41. Do less… most things don’t work.

Bonus points if you get your blood checked.

Start here, it will change your life.

[Shashank ಕುಮಾರ್ शंकर @sshank_]

Really good summary most things business.

[Jaynit @jaynitx]

Bill Ackman literally gave a 44-minute masterclass that explains money better than any business school:

[Andrej Karpathy @karpathy]

I've never felt this much behind as a programmer. The profession is being dramatically refactored as the bits contributed by the programmer are increasingly sparse and between. I have a sense that I could be 10X more powerful if I just properly string together what has become available over the last ~year and a failure to claim the boost feels decidedly like skill issue. There's a new programmable layer of abstraction to master (in addition to the usual layers below) involving agents, subagents, their prompts, contexts, memory, modes, permissions, tools, plugins, skills, hooks, MCP, LSP, slash commands, workflows, IDE integrations, and a need to build an all-encompassing mental model for strengths and pitfalls of fundamentally stochastic, fallible, unintelligible and changing entities suddenly intermingled with what used to be good old fashioned engineering. Clearly some powerful alien tool was handed around except it comes with no manual and everyone has to figure out how to hold it and operate it, while the resulting magnitude 9 earthquake is rocking the profession. Roll up your sleeves to not fall behind.

[Shashank ಕುಮಾರ್ शंकर @sshank_]

@deedydas But @NanoBanana can one-shot this without any extra skills.

Till date Nano Banana Pro has been amazing generating Infographics, UXs better than other models.

[Dr. Dominic Ng @DrDominicNg]

As a neuroscientist, here are 7 ways to trick your brain into doing difficult things:

1. Shrink the task to just two minutes.
Your brain resists big commitments. So don't make one.
- "Work out" → do one exercise.
- "Clean the house" → pick up three items.

[Shashank ಕುಮಾರ್ शंकर @sshank_]

Really cool. The number of use cases I find each day with Gemini Pro + Nano Banana is huge.

[Pavol Rusnak @PavolRusnak]

Nice Nano Banana Pro prompt for weather app:

CITY=Prague,Czechia

Present a clear, 45° top-down isometric miniature 3D cartoon scene of [CITY], featuring its most iconic landmarks and architectural elements. Use soft, refined textures with realistic PBR materials and gentle, lifelike lighting and shadows. Integrate the current weather conditions directly into the city environment to create an immersive atmospheric mood.
Use a clean, minimalistic composition with a soft, solid-colored background.

At the top-center, place the title “[CITY]” in large bold text, a prominent weather icon beneath it, then the date (small text) and temperature (medium text).
All text must be centered with consistent spacing, and may subtly overlap the tops of the buildings.
Square 1080x1080 dimension.

[Andrej Karpathy @karpathy]

As a fun Saturday vibe code project and following up on this tweet earlier, I hacked up an **llm-council** web app. It looks exactly like ChatGPT except each user query is 1) dispatched to multiple models on your council using OpenRouter, e.g. currently:

"openai/gpt-5.1",
"google/gemini-3-pro-preview",
"anthropic/claude-sonnet-4.5",
"x-ai/grok-4",

Then 2) all models get to see each other's (anonymized) responses and they review and rank them, and then 3) a "Chairman LLM" gets all of that as context and produces the final response.

It's interesting to see the results from multiple models side by side on the same query, and even more amusingly, to read through their evaluation and ranking of each other's responses.

Quite often, the models are surprisingly willing to select another LLM's response as superior to their own, making this an interesting model evaluation strategy more generally. For example, reading book chapters together with my LLM Council today, the models consistently praise GPT 5.1 as the best and most insightful model, and consistently select Claude as the worst model, with the other models floating in between. But I'm not 100% convinced this aligns with my own qualitative assessment. For example, qualitatively I find GPT 5.1 a little too wordy and sprawled and Gemini 3 a bit more condensed and processed. Claude is too terse in this domain.

That said, there's probably a whole design space of the data flow of your LLM council. The construction of LLM ensembles seems under-explored.

I pushed the vibe coded app to
https://t.co/EZyOqwXd2k
if others would like to play. ty nano banana pro for fun header image for the repo

[Arpan Gupta @arpangup]

When Shohei Ohtani was a high school freshman, he created a detailed "dream sheet" with one central goal: to be the #1 draft pick for 8 NPB (Nippon Professional Baseball) teams.

It was a 64-cell roadmap based on a framework called the Harada Method.

Here's exactly what Shohei did 👇

1. First, some history.... The Harada Method was created by Takashi Harada, a Japanese junior high track coach. He took a team ranked last out of 380 schools and, using his system, turned them into the #1 team in the region within 3 years. They held that top spot for the next 6 years.

2. You start by placing your main goal in the center of an 8x8 grid. For Ohtani, this was "be the #1 draft pick."

3. Next, you identify 8 critical supporting pillars needed to achieve that goal. These surround the main goal.

Ohtani's 8 pillars were:
• Body
• Control
• Sharpness
• Speed
• Pitch Variance
• Personality
• Karma/Luck
• Mental Toughness

4. You then break down each of those 8 pillars into 8 smaller, actionable tasks or daily routines.

This fills out the entire 64-cell grid, turning a massive dream into a concrete, daily action plan.

To improve his karma, he listed tangible actions like:

• Showing Respect to Umpires
• Picking up trash
• Being positive
• Being someone people want to support

5. The method goes far deeper than just technical skills. It forces you to analyze your weaknesses and build confidence. It also has a highlight on service to others, emphasizing that humility and contributing to your community are essential for personal success.

6. The key to the system is daily execution and accountability. Once the 64-cell chart is complete, you turn the tasks and habits into a daily diary and a "Routine Check Sheet." It’s designed to transform abstract intentions into a measurable, daily practice.

[Shashank ಕುಮಾರ್ शंकर @sshank_]

@shreyas It would be nice to start with (B) and end with (D) on how to not make the same mistakes / failures.

[Andrej Karpathy @karpathy]

Agency > Intelligence

I had this intuitively wrong for decades, I think due to a pervasive cultural veneration of intelligence, various entertainment/media, obsession with IQ etc. Agency is significantly more powerful and significantly more scarce. Are you hiring for agency? Are we educating for agency? Are you acting as if you had 10X agency?

Grok explanation is ~close:

“Agency, as a personality trait, refers to an individual's capacity to take initiative, make decisions, and exert control over their actions and environment. It’s about being proactive rather than reactive—someone with high agency doesn’t just let life happen to them; they shape it. Think of it as a blend of self-efficacy, determination, and a sense of ownership over one’s path.

People with strong agency tend to set goals and pursue them with confidence, even in the face of obstacles. They’re the type to say, “I’ll figure it out,” and then actually do it. On the flip side, someone low in agency might feel more like a passenger in their own life, waiting for external forces—like luck, other people, or circumstances—to dictate what happens next.

It’s not quite the same as assertiveness or ambition, though it can overlap. Agency is quieter, more internal—it’s the belief that you *can* act, paired with the will to follow through. Psychologists often tie it to concepts like locus of control: high-agency folks lean toward an internal locus, feeling they steer their fate, while low-agency folks might lean external, seeing life as something that happens *to* them.”

[Claude @claudeai]

A roundup of what’s new in Claude Code:

[Suhail @Suhail]

AI gives you wings

[Shashank ಕುಮಾರ್ शंकर @sshank_]

PSA

[Andrej Karpathy @karpathy]

An attempt to explain (current) ChatGPT versions.

I still run into many, many people who don't know that:
- o3 is the obvious best thing for important/hard things. It is a reasoning model that is much stronger than 4o and if you are using ChatGPT professionally and not using o3 you're ngmi.
- 4o is different from o4. Yes I know lol. 4o is a good "daily driver" for many easy-medium questions. o4 is only available as mini for now, and is not as good as o3, and I'm not super sure why it's out right now.

Example basic "router" in my own personal use:
- Any simple query (e.g. "what foods are high in fiber"?) => 4o (about ~40% of my use)
- Any hard/important enough query where I am willing to wait a bit (e.g. "help me understand this tax thing...") => o3 (about ~40% of my use)
- I am vibe coding (e.g. "change this code so that...") => 4.1 (about ~10% of my use)
- I want to deeply understand one topic - I want GPT to go off for 10 minutes, look at many, many links and summarize a topic for me. (e.g. "help me understand the rise and fall of Luminar"). => Deep Research (about ~10% of my use). Note that Deep Research is not a model version to be picked from the model picker (!!!), it is a toggle inside the Tools. Under the hood it is based on o3, but I believe is not fully equivalent of just asking o3 the same query, but I am not sure.

All of this is only within the ChatGPT universe of models. In practice my use is more complicated because I like to bounce between all of ChatGPT, Claude, Gemini, Grok and Perplexity depending on the task and out of research interest.

[Shashank ಕುಮಾರ್ शंकर @sshank_]

@karatalaamalaka Does it imply that Rishyasringa lived in and around current day Sringeri area?

Isn't the idea that the 3 horned figure seen in IVC stamps was Pashupathi / Rig Vedic Rudra?

[Andrej Karpathy @karpathy]

We have to take the LLMs to school.

When you open any textbook, you'll see three major types of information:

1. Background information / exposition. The meat of the textbook that explains concepts. As you attend over it, your brain is training on that data. This is equivalent to pretraining, where the model is reading the internet and accumulating background knowledge.

2. Worked problems with solutions. These are concrete examples of how an expert solves problems. They are demonstrations to be imitated. This is equivalent to supervised finetuning, where the model is finetuning on "ideal responses" for an Assistant, written by humans.

3. Practice problems. These are prompts to the student, usually without the solution, but always with the final answer. There are usually many, many of these at the end of each chapter. They are prompting the student to learn by trial & error - they have to try a bunch of stuff to get to the right answer. This is equivalent to reinforcement learning.

We've subjected LLMs to a ton of 1 and 2, but 3 is a nascent, emerging frontier. When we're creating datasets for LLMs, it's no different from writing textbooks for them, with these 3 types of data. They have to read, and they have to practice.

[Gokul ⚡️ @gokulns]

(What I consider good) Career advice that no one asked me for: Over the past few weeks, I've been trying to crystallize some of my thoughts around winning in a job/career. Thought of putting this out there, in case it helps someone.