I trace my journey from IIT Madras and IIM Bangalore to co-founding Gramener and joining Straive. I share stories about data visualization, my career at IBM and BCG, and the persistent confusion surrounding my name and beard.

You may know me as S Anand. You may also know me as Prof or Stud at the Indian Institute of Management, Bangalore, as Anand Subramanian at IBM India, Bhalla at Alakananda hostel, IIT Madras, and Bal at Vidya Mandir. LinkedIn CV (2024) History 1974-1978 at home I was born on the 23rd November, 1974 (a Saturday) at Tirupati. I flew back to Madras (now Chennai) in a few days along with my parents. I stayed at home for 4 years, thoroughly enjoying myself. My mother would feed me while telling me stories while I was perched on her hip looking at the cows behind our house (it was no mean feat — I think I weighed 20 kilos). Since I was the youngest grandchild in our family, no one was permitted to get angry with me — especially if I sat on them and hit them with whatever they wouldn’t give me. 1978-1992 at Vidya Mandir In June 1978, I was admitted into Vidya Mandir where I had an enjoyable 14 year stay. In the meantime, I learnt music for a few years. I took up scouting in 1986 as well as Yoga in 1987. I was forced into NCC (National Cadet Corps) for a couple of years. I started fiddling with computers, particularly graphics. Sometime then I developed an active interest in Tamil films, especially the songs. I took to basketball in my ninth standard. Despite these, I managed to do somewhat well at academics. I even found myself in the middle of a National Maths Olympiad. 1992-1996 at IIT Madras I left VM in May 1992 and joined the Indian Institute of Technology (IIT), Madras. I spent four years there - enjoying the last one in particular. I learnt Mrdangam for three years in the meantime, and started my career in computers. The only hitch was that I was in Chemical Engineering! I believe most of my professors had given up hope with regard to me. I managed to see quite a few places in the guise of presenting seminars, played the keyboard on a few occasions, and played a few pranks on some people as well. 1996-1999 at IBM Bangalore In August 1996, I joined IBM India, (which was called Tata Information Systems Ltd. in those days) as a software engineer. I focused mainly on Lotus Notes and Java, and became a project leader in a year-and-half. Like most software engineers, life was filled with deadlines, the occasional trip abroad, treats, movies, late-night browsing, missed meals, and complete lack of social life (to the point where I saw the sun once a month). I loved it! Looks like IBM loved me too. Apart from the fact that I have several wonderful friends there, they also awarded me the “IBM Way” award. 1999-2001 at IIM Bangalore By this time, I was pretty impressed by my managers at IBM, and wanted to be like them. Besides, I was a little peeved at the IIMs for not letting me through on my first attempt. So in July 1999, I finally joined IIM Bangalore (Bangalore is closer to home than Ahmedabad.) Through it all, I never figured what I wanted to specialise in. I worked during the summer at Lehman Brothers (Tokyo), an investment bank. But during my fifth term (at London Business School), I figured finance wasn’t for me. I like technology too much. IIMPressions write-up IIMPressions is the IIMB yearbook. Here’s the writeup about me. God of All Things Stud, Prof Paritraanaaya Saadhoonaam,Vinaashaaya Cha Dushkritaam Dharma Samsthaapanaarthaaya, Sambhavaami Yuge Yuge The sole motto of this God of Kaliyug joining IIM Bangalore was to provide JOY to lesser mortals. So He ditched IIMA. He took tutes for His batch mates and His junior batch. He made sure that the Junior batch was well placed to crack the Aditya Birla Scholarship. He did amazingly good project reports, presentations and assignments for the nis-swaartha purpose of sharing it with junta. Submission of the same and topping the courses were incidental. Of course, He had to do RG sometimes, to justify His human form. For that, He would sit in the library reading fiction or watch movies in the Rec room right before the exams just to psyche people out. Of course, He would do His bit to dip the professors also in the Gyan Saagar. Many profs would constantly look to Him for approval in the class and would take His private tutes to improve their knowledge. One of the profs was also found doing ACP with Him after His CCS presentation. No wonder He had a huge fan following. People who had a crush on Him ranged from PGP Is to professors resembling characters from Sholay. But He was a true IBMer fascinated by AS/400\. However, after a trip to LBS, He is quite excited about long black hair and belly button piercing. His fan following was not restricted just to IIMB. His website would get hits from all over the world. Webmaster of Cybersteering.com, a dotcom in Mumbai, was so impressed by His website that he actually asked His advice for revamping their site and also their operations. Even after having travelled round the globe, He remains a true TamB at heart. Give Him Thaiyuru sadam and pickle and He wouldn’t ask for more. He wants to be within a 3-hour flying radius from Madras. So He spurned Lehman. But surprisingly He was enthralled by Goldman who however decided to have an alliance with Lehman. His priorities in life are very clear. Maths, books, music, which includes playing keyboard and breaking a leg over dancing to Tamil film songs, movies and doing outstanding work. Sleeping at 10 at night would come much higher in His list. He would refuse to attend the block parties for the same reason. Buying clothes and cutting hair are His last priority in life. Being God, He is always very non-threatening, reassuring and very accessible to His bhaktaas whether it be for pursuit of knowledge or psychological support. Thus while He follows pure “Gyaan Maarga”, the rest of us are quite happy following the “Bhakti Maarga” towards Him. However, JOY would have known no bounds if the Bhakti of His true Meera from the West (or East?) had led to Mukti. As per Jewish believers, one doesn’t spell the name of the God. Though He deserted a premier Jewish I-Bank, some of us are still aspiring for it. So honouring the Jewish culture, we bow to this God without ever writing His name. “Barukh atah Ha-shem, Elokaynu, melekh ha-olam” (Hebrew for Blessed art thou Lord, our God, King of the Universe). 2001-2005 at BCG Mumbai I graduated in March 2001 with a couple of gold medals, and joined the Boston Consulting Group in Mumbai. On June 2, 2002, I married Shobana. After a wonderful honeymoon in Europe, we settled into a house-on-the-verge-of-collapse in Bandra (it was torn down in Nov 2004). At work, I had a great time with the big shots in the corporates (the high point being when the AM Naik, the Chairman of L&T, served me soup). At home, we would wander down Linking Road arguing about buying clothes (vs not buying them). 2005-2011 at Infosys Consulting London I was missing technology too much, and we decided to live abroad for a while as well. Since I loved London so much, it was the first choice. I’m now with Infosys Consulting at London, enjoying 40-hour weeks. On Feb 27, 2006, my daughter Dhyeya was born at St Isabel’s Hospital, Chennai. Dhyeya means “one you worship”. She weighed 3.7 kgs at birth. 2012-2023 at Gramener The startup bug bit me. So along with a few good friends, we started Gramener, a data visualisation & analytics company. This combines three interests of mine: statistics, programming and design. I was in Bangalore for most of this time and moved to Singapore in Aug 2023. 2023-now at Straive Straive acquired Gramener in Nov 2023. We liked the people, data, and growth opportunity. (And the valuation.) I continue in Singapore doing what I’ve been doing the last decade — extracting insights from even more data and telling better stories from those. But using LLMs. I had a lot of hair My hair grows very fast. (I take after my father and his father). I had a moustache (thin, I grant) at the age of 13, and a fairly dense beard when I was 16. I was of course asked to shave periodically by almost everybody. My argument against it is simply that it’s too much of trouble, and besides, beards look nice. At least in my opinion. At school and college, I was known by my beard - being the possessor of the largest (if not the only) specimen. It made me quite popular. So I see no reason for me to shave. In August 1996, I started shaving twice a week. People would actually comment if I haven’t shaved! I was driven to this for two reasons. One was that everyone told me that if I wanted to go to office, I had better shave. The second …., well, let me summarize it this way: a girl who’s senior to me called me “Sir”. I shaved. After that, I’ve been compared to the film hero Ajit innumerable times, to another hero Arvindh Swamy at least twice and once to Sharath Kumar. I don’t mind it. But that still leaves my hair and moustache. I’m fiercely proud of my moustache, and won’t shave it off, ever! I may chew on it every now and then, but I’ve recently entered into a contract obliging me to pay Rs.25 per hair on my moustache that I chew, so I’ve curtailed that a bit. In fact, my dedication to my moustache won me a nomination in the IIM Bangalore yearbook. Things got a bit worse at BCG, though. I normally like shaving every other day at best. Except that there’s this character, Alpesh, at BCG, who has no better work than to walk down to my cubicle, peer over my shoulder, and comment, “How did they let you into office with that stubble?” Thanks to him, I shave every working day. My wife suggested I grow a french beard. It tends to be a bit sparse, though. I pluck my beard when I’m thinking, or watching an interesting movie, or reading an interesting book, etc. My mother passed away in 2016, and I shaved for her last rites. I haven't grown back my moustache since. My hair decided to whiten and mostly fall off on its own. My name is a source of confusion I was christened Anand Srinivasan. Anand means happiness: Anandhayathi iti Anandhaha - he makes others happy - hence he is Anand. The Srinivasan’s because I was born at Tirupati whose temple deity is known by the same name. And I was born on a saturday, which makes it all the more special. My official name at school was Anand Subramanian, the latter being my father’s name. I was known to most of the teachers and friends as S.Anand, and that’s the way I’d rather stay. In my third standard, we had to write a Hindi essay on the Moghul poet Birbal, whose name I misspelt as Birbaal (the long ‘A’ instead of the short ‘a’). Kiran Miss declared that I would thereafter be referred to as Bal, and the name stuck. It went to a point where most people did not know that it was my nickname - including at least one teacher. At IIT Madras, I was named Bhalla Nonsense (to be spelt and pronounced “Bhbhallla Naaansense) by extremely bored seniors during my first ragging session. (One was Prasanna, who played the famous guitar interlude of July mAdham in the movie Pudhiya mugam). I was spared the surname, but Bhalla stuck. Since the official records list me as Anand Subramanian, people have a habit of calling me Mr.Subramanian. That’s my father! I’m just Anand. I had a lot of trouble with my passport too, since they insisted on my filling out my first, middle and last name. I told them my name was S.Anand and they could decide which was which. (Of course it didn’t work. They made me stand in a queue for a couple of hours and told me my passport application was invalid.) So my passport actually refers to me as Subramanian Anand. While working at IBM, this was almost rectified, until we moved our mail system to Lotus Notes, which does not permit the first name to be the single character ‘S’. Hence, thanks to the IT revolution, I was known as “Anand Subramanian” again. It was only at IIM Bangalore that this fault was fully rectified. So successfully, in fact, that people wondered what the ‘S’ stood for, and settled at “Stud”. But if I thought that was the end of things, I was mistaken. At BCG, trouble began again, with the head of IT calling me up to confirm if I really was called “S Anand”. I know all about mailing systems by now, and how to get around software. So I tell him, yes. My name is “S” Anand. No, I won’t expand “S”. No, I don’t mind causing too much confusion. Then comes the problem — is “S” my first name or last name? I figured people may as well call me Anand and Mr. S rather than Mr. Anand and S. So my e-mail ID became s.anand@bcg.com. That was just the start. Once I joined, everyone got visiting cards. Except me. My visiting cards were delayed because the printer refused to believe my last name was “S”. So I had to confirm that yes, my last name is “S”, and I really wanted my cards. When I joined Infosys, I managed to convince them to call me just “S Anand”. But sanand@infosys.com, s\anand@infosys.com, anand\s@infosys.com and all other such variants were taken. I positively HATED IDs with numbers in them (like sanand1974), so I ended up with subramanian\anand@infosys.com. At Gramener, I got to decide what email ID to pick, and went back to s.anand@gramener.com. (Yet another source of confusion is my personal e-mail ID, which is “root dot node at gmail.com”. But that’s a long story.) Comments Sudeep Nair 4 Sep 2006 3:23 am: Your site is damn cool. Thanks for letting others take a peek into your perspective on various aspects of life. I am from IIM-A batch of 2001, so I can relate to lot of things written by you. S Anand 4 Sep 2006 7:00 am: Thanks, Sudeep! Where are you based? Sudeep Nair 20 Nov 2006 5:07 am: I am based out of Bangalore and work for Cognizant's Business Tech Consulting group, doing similar work as you do at Infy Consulting. Anonymous 14 Dec 2006 12:21 am: What type of work you do at Infosys, are you more into technology or business side priyanka kunuthuru 25 Dec 2006 1:19 pm: Hi! sir this is priya Iam selected for IBM on this june and waiting for my appointment,can you give some details abt training and workplace in Ibm. Swamy 12 Jan 2007 7:49 pm: Anand...really informative site and wonderful reading!! I graduated from IITM in 2002 and was in Alakananda. we have so much in common...shall call you sometime!! venky 28 Feb 2007 11:18 am: HI Bhalla . This one is really informative. I am a 2nd year student from IITM. I am from saras I would like to talk to u regarding many issues ...so kindly let me know when r u free to chat... Nayana 18 Aug 2008 4:34 am: Really good & informative site! RajaSekhar Batchu 17 Feb 2009 5:39 pm: Hi Anand S,,, Its very nice to read your experiences you had in your life time.. especially the one confusion of the word "S" regards, raj vaikuntanath kakarla 8 Nov 2008 4:57 pm: Hi Anand\ Am also from VM, 1985 batch, now in london. Came across your write-ups when I was searching for my batchmates. Not sure if this would reach you....r u still in london? if so would like to talk to you sometime; if not, well, there's emails / facebook...\ cheers yogesh 22 Jan 2007 12:29 pm: hi i am in 12 th right now and want to take up chem engg at iitm iitd or b. How exactly is the course and how are placements?? btw if we do an mba the engg branch does not really matter right?? yogesh 22 Jan 2007 12:31 pm: chemical enggineer at IBM??can u explain please... deepan 17 Feb 2009 5:39 pm: In the recruitment pages of Infosys consulting)https://www.infosysconsulting.com/our\culture.htm), IIM s are ignored! MKSReddy 17 Feb 2009 5:39 pm: Dhyeya = aim or thing to be achieved or target :) bala 22 Sep 2006 6:19 am: dude..u too have this problem of first, middle and last name ..yes especially south indians find it tough in all places regd these naming nomeclatures sowmya 20 Dec 2008 4:44 am: A post on the name- Enjoyed your narration !\ \ //My name is "S" Anand. No, I won't expand "S".// - haha..\ \ Had a nice time over here\ \ Thanks :) amit 6 Mar 2009 8:17 am: I am from Cal 2001 batch. A close friend shared your story and sent this link today. Quite an enjoyable read (The name story is especially extremely entertaining.. hope you intended it that way!).. I am sure to visit it again. Think there's a lot to explore. God Bless, Amit Hari K T 16 Apr 2009 5:32 pm: Great site man . You are powerful in python ....... :-) . Just peeeped you codes from google . Written nicely the about section . Keep going . Have a great day and great future . Bye . R.Seetharaman 27 Apr 2009 4:29 pm: Dear your site seems to be much informative , though iam average in computers i find ur site worth informative, ur profile was written nicely Maithry 27 May 2009 8:56 am: Hi Anand, Ur narration is simply superb. why dont you try as a writer. this is a small suggestion. bye, maithry Raghavender 11 Jun 2009 1:52 am: Hi Anand.. Really a superb site...such a wide variety of collection and also your vocab is too good..just to add I also work with Infosys Regards Raghu Arun 2 Jul 2009 4:58 pm: Hey Anand, Greetings from a fellow Pythoneer! Really elegant site you have here. Didn't know that you are from IC... your About Me was a very interesting read :) Will keep visiting! S Anand 30 Oct 2009 7:13 am: It's easy enough... just Google "download calvin and hobbes" and the first few links will point you the right way. JW 3 Nov 2009 12:04 pm: Hey, that is so great, thanks for the hint. I didn't think of asking google for it... Cheers Jinni JW 28 Oct 2009 12:15 pm: Hi, I love your "Calvin and Hobbes" comic strip search. Thank you so much for providing it. I have a question: Could I download all the strips at once from somewhere or could you send them to me? I do have them all on paper, but I would love to have them digital so I can have an alternating desktop background. Thanks a lot for all the work! Cheers Jinni Mallikarjun Mangalore 10 Oct 2009 7:58 pm: Hi Anand, First of all thank you very much for designing such wonderfull site. I am from karnataka and terrefic lover Kannada songs.I have downloaded around 800 old kannada songs from your website. It is sucha great pleasure to know, that you have worked earlier with us, I mean IBM. Yes, i am an IBM'er. Thank you very much once agian for this wonderfull site. May god bless, you and your wife and your beautifull daughter. I happy stay, in London. Will try to catch you in London, when i will get opportunity to fly to london. Becoz, my customer is SHELL, UK. Thnak you, Mallikarjun Mangalore Khair 19 Sep 2009 12:11 pm: Hello Anand, I just love the design of your site, very user friendly. The aritcles are pure delight. The content percolates smoothly and very well organised information. Thanks for such a beautiful site. Will come on here frequently. Ahmed 20 Mar 2010 3:08 pm: I have been visiting your site quite often for some time mainly to download tamil songs. I really enjoyed reading about you.Genius. Keep it up Anand ( or Subramaniyam ? ) Ahmed Sudha Chandrasekhar 15 Jul 2010 4:32 pm: Dear Anand, Hope u remember me. I am sumathy aunty's daughter, ur Amma's friend, now in Bangalore, working as a teacher, enjoying songs from the site. I like your website. Thanks ...................... lots. Sudha chandrasekhar. Sachit Bharti 8 May 2010 9:46 pm: Dear Anand Sir, I am so inspired with you and your versatility, really you are exceptionally blessed (I would say blessed with super power) and quoting you "god of all thing" is incredibly true. Sachit Vijay 10 Mar 2010 3:38 am: Cool site mate...Ur site rocks...Pity i didn't come cross this site earlier. Keep it up. Cheers, Vijay Brian 19 May 2010 2:57 am: I usually don't do this, but this is a great site. I don't even know how i ended up here but I'm glad I did. One word to describe this site: Amazing. Brian Saravna Kumar 5 Aug 2010 7:30 am: Anand… Sir, really informative site and wonderful reading!! try to give a chance to see the village life for a little period to your childrens also thank you Jai 16 Jun 2010 11:22 am: Hey Anand, We have probably met each other at Balsu's classes. I live in London. Ping me back. Should be good to catch up. Raghu, Sundi were all my classmates. Cheers, J Vivek 18 Jun 2010 6:44 pm: hi Anand, you are rocking... I like your website. very recently I've written one small story. read it when you get free time and put your comments. Hope you could read tamil https://singamulla.blogspot.com/p/it-part-i.html A 22 Jul 2010 2:14 am: Hi Dude, Nice site. I think Music India online wised up to people cracking their defences and downloading the songs! Now you have a new challenge on your hands - their new site with what looks to be an embedded flash player...can you take a look and give me some pointers? Thanks! shanthi 24 Sep 2010 3:18 pm: No words to describe...want to meet u in person..such a versatile talented,etc etc, Thank you so much for this wonderful site.. shanthi Swapna 11 Oct 2010 6:50 pm: Hello Anand, I am a staunch follower of your site. You are such a talented genious. Wish I could meet you in person. Wishing you all the success! Aruna 19 Nov 2010 11:31 am: Hi Anand, I am a regular visitor of your site. Very informative. Thankyou. hai anand 26 Apr 2012 2:22 pm: Dear anand i am very happy to introduce my self to you. I am Dr.S.Saravanan, Asst.prof and Head Dept. of Commerce IT at Dr.N.G.P. Arts and Science College, Coimbaotre, i would like to invite you to our college for share your valuable experience and knowledge to our students while you come to coimbatore at any time, your presence is precious to our students ,,,, Valji 22 Feb 2012 7:00 pm: Hello Anand, Anand is a lovely name , looks like you truly appreciate joys of life, therfore everyone should bow down and call you Anand-ji. Anandji I cannot contact you as your email address at infosys is no longer valid. I need to discuss some interesting ideas with you yarr. Please email your new contact. Thanks BP 24 Feb 2012 10:12 am: Hi Anand, I was using your xpath server for some RSS feeds, but some links have session-ids, so my Google Reader thinks all items are new every time the feed is fetched. With another site I have the problem that the links don't start with "http://", so the link goes to "http://www.s-anand.net/www.otherdomain.com/..." (you might have noticed that in your error logs). Is it possible to share the code for that xpath server? Kashyap 8 Jan 2011 2:24 am: I positively love the way you write!!! You rock! Sachin 10 Jan 2011 3:46 am: Hey Anand - Wow...this is cool reading..you could have been an avid writer if not in technology probably...wait till you hear from Amir Khan looking for his next script...I must say its a pleasure working with you. Chakradhar 12 Jul 2012 10:21 pm: Hellow Sir, I am very much thankful for your valuable Excel tips and your best links. kishore ssk 11 Nov 2012 7:03 am: sir , u r such an inspiration .. keep posting good links as for me "THIS SITE IS THE ONE STOP INFO FOR EVERYTHING" Chetan Ahuja 2 Jan 2014 2:30 pm: Hi Anand, just bumped into your blog ... looong one . Appreciate your effort. can ask for some mentoring advice on a personal note. If yes just send me a Hi. you are a info Highway. Congrats ! mohtamil 19 Mar 2013 7:40 am: Sir, My interest to you is via Ilayaraja. I have read all your 15 essays on Ilayaraja.I completely agree with your views on Ilayaraja as a person. When people say golden period of Tamil music is from the day Raja composed music I don't agree with them.. For me G Ramanathan is the greatest. Ajay 25 Sep 2014 6:05 pm: Hi Anand, I attended your session today at Emerging Technology Summit, was very impressed and also energized with your energy. You really shared a lot of tips and knowledge, and made the day for everyone who attended the tech conference. Wishing you well, Regards, Ajay Pratyush 23 Aug 2014 6:40 pm: Hi Anand, This is one of the best About me pages. Thoroughly enjoyed reading it. And thanks for all the presentations and resources. They all are so awesome. Suhas 5 Aug 2014 12:23 pm: Wow! You have another 'Bhakta' in the 'Bhakti Maarga' now. :) I do wonder, though, how you motivate yourself to such extents and manage to do so much work and help people and conquer the world and... Udayamoorthy Veluchamy 9 May 2015 4:58 pm: Dear Anand, Impressed a lot while reading this blog. You are sharing lot of excelleent information and mind blowing stuffs to realize the Analytics domain and i am really admired. Please accept my heartiest wishes and thanks. Wish you live long and i am sure Gramner is going to rock in the analytics world. Thanks Regards Uday Niraj Kumar 22 May 2016 5:35 am: Hi Anand, Very impressive narration of your life journey encompassing your IT and management life. I read about you today in TOI and sent you immediately a LinkedIn invitation having found two things that I have been struggling to get 1. How to take my passion of data insight into Data Science road map , and 2. Risk at this stage of life (I am 44) into lateral movement. May i request your no., or mail id , I can have more focused discussion with you. Niraj Sakshita Jayaswal 1 May 2025 10:18 pm: You’re truly inspiring, and I deeply admire your work. As a recent graduate from IIM Lucknow and an AI enthusiast, I’m eager to learn and grow, and I would love the opportunity to learn from your experience and insights. Srijan Mukherjee 31 Aug 2025 11:53 pm: Hi sir, I am a student of your Tools in Data Science course at IIT Madras, and to put it bluntly - you have become my biggest inspiration and have given me a new purpose in life. I started my academic life being called a rather gifted student, and with time, everything went downhill and I, after a lot of personal struggles, found solace in music. For quite some time, my interest in tech and the world of innovation was subdued by my passion for music and I became invested in it full-time. My grades suffered, and it felt like there was no coming back until I took the TDS course. Today was the end-term exam and although it was a breeze, I feel like I could do much better. The most important thing I gained from this course was raw inspiration, and a spark to reignite a side of myself that has been dormant for a long time. Thank you for teaching us, sir! Hope to have your blessings, With regards, Srijan

About me


I detail how I use AI 50 times daily to build an intuitive reflex. Key strategies include 'vibe coding,' having agents interview me for clarity, and maintaining an AGENTS.md file for structured collaboration and skill growth.

Here's AI advice I generally give people. What skills should I learn? AI will erode skills — but that's OK for some skills. Learn what AI won't do well even in the future. Practice manually, then use AI for critique and coaching. Delegate blindly what AI does well. Use saved time to learn new skills. Critical skills in the AI era: Relationship skills. Empathy, bonding, trust, etc. Humans are wired to value humans. Accountability. Giving a commitment, standing behind it, managing the risk that involves. Regulation & social norms reduce AI encroachment. Governance. Values. Ethics. What should we do? How do we decide? How do we make it happen? Problem selection. Learn to quickly discover what's useful for yourself and others. AI can execute them fast. Validation. AI works fast. Learn shortcuts to compare versions, find mistakes, and give feedback — in unfamiliar areas. (Consultants learn this skill well.) Growing skills: Management. Shift from doing the work yourself to managing "teams" of AI agents and interns to handle execution. Learn problem breakdown, team organization, etc. Asking questions. Learn to ask lots of good questions that nudge AI and humans to better results, new horizons. Curiosity helps. Communication. Thinking clearly and expressing it clearly. Storytelling. Guide AI to deliver compelling narratives that move people. Taste. The ability to recognize and guide AI toward high-quality, distinctive output — increasingly scarce as execution becomes cheap. Hard-to-define skills. Skills that are easy to define are easy to train AI on. What we can't even name is valuable. Growing (for a while) skills: Learning fast. Learn how to learn faster. You'll need to learn many subjects quickly (especially to judge AI output). But AI can learn faster. Style and art. Guide AI to write, draw, and code in different styles for different audiences. But AI can learn these too. Verification assets. Design golden sets, test cases, and audit workflows that reliably catch AI errors at scale. Orchestration. Harness engineering: know which agent, model, tool, or skill is best for which task — and how to chain them together. Tooling. Connect things — especially to agentic systems — to give them more execution power. Context engineering. Know what data to feed AI and what to skip — including the right fragments like "ELI15" or specific persona-setting — for the best results. Prototyping. Build and iterate on the smallest working solution (using AI agents) ultra-rapidly. Declining skills: Coding syntax. AI can write it. Factual recall. AI can look it up or derive it. Routine domain depth. Unless you are (or can become) a top expert, AI fills in gaps. That said: domain depth still matters for problem framing, validation, edge cases, and incentive design. Focus on judgment-heavy applications, not rote recall. Following rules. AI can implement a process better. Junior-level execution. Routine grunt work, basic summaries, and entry-level analysis are being fully automated by LLMs. Drafting from scratch. The ability to write a first draft (code or text) is less valuable than the ability to edit and refine an AI-generated baseline. Business intelligence. AI can build dashboards, data stories, and more — and is replacing static dashboards with agents that answer questions directly. Data organization. AI can structure data to make it more analyzable. Data wrangling. AI can handle data engineering, modeling, analysis, and visualization. Tool expertise. AI can use tools for you. Intermediation. AI can translate between groups (e.g. business analysts). Originating ideas in isolation. AI can brainstorm ideas. Focus on evaluating and selecting based on unique context. Here's how some industries have dealt with skill erosion: Autopilots eroded flying skills — which is dangerous. So we enforce flight simulators. Same for surgical knots (robotic surgery), celestial navigation (navy), manual dosing (nurses). Spreadsheets eroded calculation skills. We leveled up from sums to strategy. Same for CAD, electronic trading, spell-check. Photography eroded painting skills. We switched value to impressionism, cubism, etc. Same for vinyl records, luxury watches, craft coffee. GPS eroded navigation skills. We accepted this and don't care much. Same for phone numbers, spelling, mental math. How do I use AI better personally? Buy paid subscriptions to ChatGPT, Claude, and Gemini — all three. Each has different strengths, and $60/month covers almost every need. Enterprise and API plans protect data by default; consumer plans require configuration. Use AI 50 times a day across tiny personal, work, learning, and creative tasks. High volume forces you to find use-cases you'd otherwise ignore, and builds the reflex of reaching for AI first. Ask it first, not Google. When you have a question — or almost any feeling of discomfort, curiosity, or being stuck — ask an agent before searching. Delegate the research. "Just tell me what to do." If you don't know what to ask, have it interview you. Ask the AI to interview you to find out what you want, and then do it for you. Think of it as an intern, fresher, or senior, depending on the task. For creative and domain work: treat AI like a brilliant but opinionated intern — great at fetching and preparing materials, less reliable for nuanced judgment. For open-ended problems: treat it like a smart new hire who needs the same context, rules, and examples you'd give a human. For coding and syntax: treat it like a senior developer who likely knows better than you — defer. Ask AI what it needs. Before you start, ask "What information, tools, or access do you need for X?" and provide it. Use it for validation — but make it show its work. LLMs make mistakes, but using AI to fact-check is effective when you ask for evidence (citations, source links, or code). Have AI cross-check AI. Feed one model's output into a different model and ask it to find errors. Review where they disagree. Critique and steelman your work. Ask for counterarguments. Have it roleplay a skeptical customer, boss, or critic — or quiz you with hard questions to stress-test your work. Use emotions as prompts. Unresolved emotions are a great starting point for AI. "I feel anxious about...", "I'm annoyed by...", "I wish I had..." — ask AI to interview you, name the tension, and suggest experiments. Ask for easier output. Validating or implementing AI output takes time. Ask it for easy-to-review output. If confident, ask it to update the asset or get the work done directly. Ask for multiple, diverse outputs. You don't know what you want, or what it can do. Ask for 5–10 variations. Ask multiple models. Ask in parallel. Drop the weak ones quickly. Use AI-native formats over static ones. AI generates interactive HTML, SVG, and JSON better than it generates PowerPoint or PDF. Ask for these by default — they're more useful, easier to iterate, and more engaging. Use voice mode on mobile to talk to AI while walking or thinking. "Ramble" at it — it can structure your thoughts. This capitalizes on dead time (e.g. commuting) and dumps context faster than typing. Improve your tools by asking AI to optimize your laptop, software, and configurations, and checking if the results are better. Vibe code your own software. As a non-technical person, build apps to solve your own problems. Don't learn to code. Just tell AI tools what you want and have them build it. Make AI write and run code for any numbers. "LLMs hallucinate, but code doesn't." For math, analysis, or logic: tell it to write and run deterministic code rather than reason in prose. Code either works or fails — it's verifiable. Have it rewrite your prompts (meta-prompting). If you aren't getting the results you want, have it tell you what's missing and rewrite your prompt for you. Here are specific ideas you can try: Mine your digital exhaust. Don't delete your "junk" data. Export WhatsApp chats, journal entries, email logs, fitness data, bank statements, and feed them to an LLM. Ask it to find patterns in your behavior, identify blind spots, or summarize your year. Audit your own behavior. Feed your meeting transcripts, email chains, and call recordings into an LLM to find personal blind spots and recurring errors. Ask it to be brutally honest. This is digital exhaust turned into coaching. Repurpose content into multiple formats. A single source can auto-generate a podcast (via NotebookLM), a sketch note, an executive summary, an interactive explainer, a quiz, a slide deck, or a narrative song. Ask for all of them and pick what works. Read papers, books, and attachments. Have it rewrite dry content in the style of your favorite author (e.g. Malcolm Gladwell) to make it engaging. Add "ELI15" (Explain Like I'm 15) for simplicity. Hire an expert. "Hire" it as a personal financial advisor, career coach, relationship counselor, or fitness trainer. For example: Doctor. Summarize your health history, identify gaps, and prepare questions to ask your actual doctor. Detective. Find out what a long-lost contact has been up to, or what a client's public track record looks like. Financial advisor. Have it interview you about your finances, goals, and risk tolerance, then research a personalized plan. Teacher. "I want to learn [topic]. Explain the basics, then ask me 3 questions to test if I understood." How do YOU use agents? Here are some of my behaviors in the agent era: Prototype the prototype. Sometimes, I'm not even sure what to prototype. I have the agent build something based on very quick, crude early thoughts, then iterate on it. Reviews are easier when I have a draft rather than an idea. # Galleries for ideas. I collect prompts and preview output as galleries. I extend based on usage, but big leaps come when I ask agents to create and extend galleries. Audio to analysis. I record calls, transcribe them, and pass to a coding agent to give the other person what they need — without interpreting it myself. I'm mostly getting out of the way of the agent's speed and capability. Itch to experiment. When I have a thought, I have an agent prototype it and run the experiment. With more tools and environments, the space of what it can experiment on grows. Directional feedback. In areas where I'm not the expert, I tell agents how I feel, how I should feel, how I'll know if it's right — and trust the agent's judgment. # Organize context. I record and organize far more data than before (call transcripts, bank statements, phone bills) to pass to agents. Managed digital exhaust is an asset. Ask the agent for anything. When I have almost any feeling — discomfort, curiosity, confusion, being stuck — I'm now trained to ask an agent first. Many email replies are just: copy to Gemini, copy back. Run weekly performance reviews with agents. I ask them: "What can I do to manage and prompt you more effectively?" The answers go into AGENTS.md so I don't repeat the same mistakes. Keep a running impossibility list. I keep a list of tasks agents can't do well yet. I revisit it monthly — model improvements regularly turn previous failures into easy wins. How do I use AI for coding? Vibe code first. Ask for what you want. Let AI build it. If it works, AND is what you want, AND needs to be maintainable, THEN look at code. Non-coders can code. Domain experts (e.g. HR, Finance) can build their own tools using AI, bypassing traditional IT bottlenecks. You don't need syntax — you need enough logic to specify, test, and judge. Use meta-prompting. If you need help, ask AI to write and refine your prompt before you use it for the actual coding task. Vibe code end-to-end. Send AI the recording of your client call and ask it to spec, design, build, test, deploy, and monitor. Stay out of the way; review at the end. Paste the errors. When code fails, paste the exact error log or a screenshot into the chat. The model is often its own best debugger. Code is disposable; prompts and skills are the assets. Code is an AI compilation artifact — don't get attached to it. The prompts, skills, and context files that produced it are your real IP. Scrap and restart freely. Two failures: restart with a summary, not a blank slate. If it fails to fix a bug after two attempts, ask it to produce a failure summary and minimal reproduction case first, then start a fresh thread. Pure restarts lose diagnostic context. In autonomous agents with containers, let them iterate much longer. "LLMs hallucinate, but code doesn't." For analysis, logic, and anything where correctness matters: tell AI to write and execute code rather than reason in prose. Code is binary — it works or it fails. This is the primary mechanism for eliminating hallucinations in production. Use deliberate synthetic data for prototyping. Don't wait for real data. Generate hypothesis-driven fake data with realistic patterns, edge cases, and expected failure modes — not just random numbers. Pick the right model for the task, and keep benchmarking. Model rankings shift quarterly. As of mid-2026: Claude for UI, aesthetic output, and deep coding; ChatGPT for rigorous analysis, financial modeling, and extended thinking; Gemini for Google Workspace, video inputs, and research speed. Blind-test on your exact task; don't freeze model advice. Plan unclear tasks. If your idea is vague or complex, use Plan → Correct → Execute: ask AI to write an easy-to-review plan, scan and correct it, then implement. Maintain reference files. Keep an up-to-date AGENTS.md (or README.md) that explains your intent, code, and architecture to the AI. Saves repeated explanations across sessions. Apply a 1–3 month ROI window to workarounds. Models keep improving. In AGENTS.md, skip prompts that work around current model limitations unless they'll pay back within months. Focus on what will still be true for future models. Generate tests first. For maintainable software, have it define tests first. That makes working code easier to verify. Tests can be 2x the code size — that's fine. Use Playwright to verify. Have Playwright take screenshots and inspect DOM elements to verify frontend work. Saves manual review time. Run post-mortems. When it fails, or after any session, ask it to analyze what went well, what didn't, and how to improve next time. Save these in a SKILL.md. Specify developer styles. Ask it to write in the style of a famous developer (e.g. Luke Edwards) or repo (e.g. SciPy) or team (e.g. Astral) that's apt for the task. How do I build an AI workspace? The shift from "chatting with AI" to "working with AI" requires a structured workspace, not a chat window. Treat prompts as source code. Your prompt library is your primary IP — more valuable than the code it generates. Keep a prompts.md file under version control. Review it. Improve it. The code is disposable; the prompts compound in value. Use a project folder, not just a chat window. Every serious AI project needs: AGENTS.md (folder-specific instructions the agent reads on startup), prompts.md (versioned prompts), a skills/ folder (encapsulated workflows), test fixtures, and a Git repository tracking every change. Encapsulate successful workflows into reusable skills. When an agent succeeds at a task reliably, capture it: the prompt, tools used, constraints, edge cases, and validation tests. Store in a SKILL.md. Skills are the new software libraries — they make complex workflows deterministically repeatable without re-explaining everything. Run coding agents inside Docker containers. This prevents accidental deletion of local files, isolates experiments, and lets you use "YOLO mode" (skip permission prompts) safely. Use containers for anything beyond a throwaway prototype. Use Git as your undo button. Always work inside a Git repository. Instruct the agent to commit at every checkpoint. A bad output is one git checkout away from gone. Let AI maintain its own instruction files. Don't edit AGENTS.md manually. After each session, ask: "What should we add to AGENTS.md based on what we just learned?" The agent updates its own instructions. How can we trust AI when it hallucinates? How do you trust people who can make mistakes? Engineer verification into the workflow — don't add it as an afterthought. Ask for evidence. Reasons, citations, source links, tests, logs, verifiable checklists — ask for a trail, not a conclusion. Quintuple-check. Ask multiple AIs. Consensus lowers review priority. Disagreement is the signal to review manually — route it to a human rather than picking a winner. Use exception triage, not blanket review. Let AI classify outputs as green (auto-approve), yellow (flag for spot-check), or red (human required). Build a golden set to measure your actual accuracy on the specific task — don't assume a universal percentage. Ask for code to generate the answer rather than the answer itself. Code is binary — it either works or fails. For math, logic, and analysis, executable code is dramatically more reliable than prose reasoning. Make reviews easy. Ask for citations, short summaries, structured output, runnable code — anything that reduces the mental effort of validation. Your review time is the bottleneck; optimize for that. Prompt for accuracy. "Never make up an answer." "If you don't know, say so." "Ask me when needed." "Double-check your work." "Cite sources." These matter. Use hallucinations deliberately for ideation. For operations, facts, finance, and regulated outputs: eliminate hallucinations with grounding, code execution, and verification. For brainstorming and research: use hallucinations as stochastic ideation — they surface non-obvious ideas. Use weaker models without extended thinking for creative divergence; save reasoning modes for correctness. How can I safely share data with AI? Match your data handling to the plan type. Consumer plans (ChatGPT, Claude.ai) have data controls you must configure. Enterprise and API plans protect business data by default. For sensitive work, use enterprise/API or run models locally. Don't assume "paid = private." Use least-privilege access. Set Google Drive access to read-only and email access to draft-only. Grant AI access to a dedicated "AI-only" folder rather than your entire Drive. Use separate browser profiles for work and personal AI use. Send schema, run code locally. For tabular data: send the column names, have AI write analysis code, and run it on your machine. This keeps the data local while getting AI's reasoning. Use MCP for structured data access. Model Context Protocol lets agents query specific datasets with scoped, read-only access — without manually copying data into the chat window. Anonymize before sending to cloud AI. Strip or hash PII before uploading to any model you don't fully control. Pick who you trust. If you already trust a provider (e.g. Google, Microsoft), use their enterprise tier. If not, run AI locally or use the techniques above. How to drive AI adoption? Make using AI easy. Reduce friction. No permissions or extra steps required, aligned to current ways of working. Show leaders using AI. When teams see leaders using (not just talking about) AI, it gives them permission and confidence. Security and privacy start with the right controls. Use enterprise models within your cloud tenant (Azure, AWS, or Google). Set least-privilege access — read-only for data, draft-only for email, containers for code. Audit logs for anything consequential. Shift from human-in-the-loop to human-on-the-loop. Run a confidence-building period where humans watch and verify AI output. Then automate routine cases and route only disagreements, low-confidence outputs, and high-stakes decisions to humans. Keep updating models. Monitor the ever-shifting cost-quality frontier and keep switching to cheaper, better models as they appear. Loyalty to a specific model is a liability. Compare accuracy with multiple experts. AI may not match an SME 100%, but one SME may not match another SME either. Check with multiple human experts and see if AI is within the human range of disagreement. Use consensus to improve accuracy, but measure it. Quintuple-check outputs. Consensus lowers review priority. Build a golden set to measure your actual error rate on the specific task — don't assume a published number applies to yours. Generate code for reliability. Instruct LLMs to write and execute deterministic code rather than reasoning in plain text. Find AI enthusiasts. Top-down mandates build frustration. Find and empower the few "builders" or "power users." Measure actual adoption — unique days of use, token consumption, task diversity — not training completion rates. Use games and challenges to teach AI. Replace passive slide decks with Capture the Flag (CTF) challenges, prompt-injection games, forbidden-word jailbreaks, and coding-agent races. Design challenges where using a coding agent is the only practical way to finish in time — this gives binary signal on real proficiency. Standardize evaluation. You'll move much faster with evaluation frameworks (like "LLM-as-a-judge") to score model performance and catch regressions. Lay a good data foundation. Convert unstructured documents into structured formats. AI output quality depends on input data quality. Let anyone build tools. Empower "citizen developers" to build their own tools in English. This de-bottlenecks IT and dramatically increases productivity. Prefer AI-native people. The most effective AI operators aren't necessarily the most experienced — they're the most willing to delegate, verify, and learn fast. Interns, domain experts, and non-coders often outperform technical veterans who resist changing their workflow. Let the owner drive it. Alice building Bob an AI solution rarely works. Bob building it himself (with Alice's help) works better. Build, don't plan. When execution is fast and cheap, don't agonize over the right solution. Build them all. Throw away what doesn't work. Buy foundations, build thin orchestration. Don't train models — they're soon obsolete. Don't build heavy platforms — they're quickly superseded. Do build: skills libraries, prompt repositories, verification layers, data pipelines, and MCP connectors. Adding is easier than changing. Using AI to improve existing work has high inertia and risk. Creating a new workflow or output has less competition. Apply a 1–3 month ROI window to model workarounds. Models improve so fast that things not possible today become possible in months. If a workaround won't pay back within that window, wait. If building now creates learning or strategic leverage, prototype anyway. Watch for urgency windows. Real adoption happens when urgency or FOMO temporarily relaxes process. Anticipate that and arrive with demos, clear risk framing, and low-change integration. Prototype rapidly. Ask for prototypes in days, not weeks. This builds a culture of rapid experimentation. Make reviewability the product. Ask AI agents to cite sources, provide reasoning, flag confidence levels, and generate audit logs. Every output should expose what it's based on, what it assumed, and what's unverifiable. How do I demo and prototype AI? Prototype in hours, not weeks. Build 2-to-8-hour POCs to test feasibility and learn where the system breaks — not to pretend production is solved. Speed of learning matters more than quality of output at this stage. Use deliberate synthetic data to start immediately. Generate hypothesis-driven fake data with realistic patterns, edge cases, and expected failure modes. Don't wait for real data — access delays and compliance concerns will slow you down. Show the output first; defend the architecture only if asked. The most persuasive demo shows a high-fidelity output that exceeds the client's imagination. Architecture slides come later, if at all. Only demo live if the task finishes in under 10 minutes. For slow, credential-heavy, or expensive workflows, use precomputed outputs, simulated backends, or recorded walkthroughs. The goal is to accelerate imagination, not stress-test infrastructure. Push one prototype through the real production pipeline early. This reveals hidden friction — format incompatibilities, latency, approval gates — faster than any strategy document. Treat demos as imagination accelerators. A good demo doesn't just prove capability — it expands what stakeholders believe is possible. Show what's now feasible before arguing about how to build it. Sell outcomes, accountability, and verification — not software. Software is a depreciating asset anyone can regenerate. Durable value: judgment, domain expertise, trust, and taking responsibility for results. Shift toward outcome-based models wherever possible. How to develop taste? See How to develop taste. (But AI can develop taste too — build galleries, curate your rejects, and ask AI to cluster and critique your preferences.) What happens to people when AI takes their jobs? Here are some paths post-automation. It depends on the industry and individual: 1. Exit: Don't adapt. There's no nearby "new task." You're unemployed. E.g. bowling pinsetters → automatic pinsetters; elevator operators; telephone switchboard operators. 2. Downgrade: Serve the machine. Worse job/pay. E.g. textile workers → power-loom tenders; print compositors → machine operators; shoemakers → factory line operatives. 3. Pivot: Focus where automation fails (exceptions, trust, coordination). E.g. bank tellers → relationship managers; travel agents → corporate travel desks. 4. Niche: Treat inefficiency as a feature (soul, authenticity). Small market, high margins. E.g. weaving → artisan textiles; coffee → baristas. 5. Up-Skill: Master the machine. Become AI-native. Much better job/pay. E.g. human computers → programmers; draftsmen → CAD designers; accountants → advisors. The Jevons Paradox applies here too: making cognitive work cheaper increases total demand for cognitive work rather than reducing it. Short-term displacement is real. Medium-term, technology creates more jobs than it destroys. The shift is from execution to verification, judgment, and accountability — which is why those skills are now scarce and valuable.

AI Advice


I collected a series of small AI experiments to unlock creative ideas. I used tools like Gemini and Claude for everything from palmistry readings and jingle creation to automating email labels and generating data-driven research stories.

A collection of little AI experiments that unlock ideas. VOICE Speak to ChatGPT in a language other than English VISION Upload your palm's photo and ask for a palmistry reading Upload a screenshot of a contacts list and ask for a Google Contacts CSV import MUSIC On Gemini select "Create music" (Lyria). Then prompt: "Create a vote of thanks for the following people. [People]" "Create a 30s loopable introduction jingle for [Speaker] who's speaking about [Topic]" IMAGE On Gemini select "Create image" (Nano Banana Pro) and prompt: "Draw this as a visually rich, intricately detailed, colorful, and funny, sketchnote. [Content]" AUTOMATIION On Google Workspace Studio, prompt: "Add an URGENT label to emails that need immediate action by me." On Claude Code Desktop, prompt: "Send a test email to myself." ANALYSIS On ChatGPT, prompt: "Research and compare the AI policies across universities as a table." RESEARCH On Claude Code / Codex, prompt: "Write a data story analyzing movie lengths over time." It will search, download, write code, analyze, and visualize.

AI Experiments


I investigated email confusion at Straive by using an AI agent to find duplicate names in Darwinbox. While I’m one of five 'Anand S' entries, others like 'Ramya R' face even more identity overlap with nine identical records.

At Straive, there's another Anand Subramanian who gets my emails and I get his emails. Name confusion - despite my last name being listed as "S", not "Subramanian". Day-before, we had a double confusion. Pallavi Gupta messaged the other Anand Subramanian who replied to a different Pallavi Gupta connecting me. Like The Comedy of Errors. Out of curiosity, I asked an AI agent to find all duplicate first + last names on Darwinbox. The agent said I found only one exact "Anand Subramanian" in firstname / lastname, but there are 5 "Anand S" records, including likely you: | Name | Designation | City | | ------- | ----------------------- | --------- | | Anand S | Chief Executive Officer | Bangalore | | Anand S | Senior Executive | Chennai | | Anand S | Senior Executive | Chennai | | Anand S | Senior Executive | Chennai | | Anand S | Senior Executive | Trichy | Hello, other "Anand S" people! Welcome to the confusion. But I'm not the only one with this problem. The worst affected is "Ramya R": | Name | Designation | City | | ------- | ---------------- | ------- | | Ramya R | Executive | Chennai | | Ramya R | Executive | Chennai | | Ramya R | Executive | Trichy | | Ramya R | Junior Executive | Chennai | | Ramya R | Senior Executive | Chennai | | Ramya R | Senior Executive | Chennai | | Ramya R | Senior Executive | Chennai | | Ramya R | Senior Executive | Chennai | | Ramya R | Senior Manager | Chennai | There are also 8 "Saravanan K", 8 "Suganya S", 8 "Surash S", 7 "Anh Nguyen", 7 "Huong Nguyen", 7 "Mahalakshmi S", 7 "Raja S", ... And I thought I had a common name!

Duplicate names in Straive


As AI automates entry-level work, I examine how to build expertise when junior roles vanish. I suggest switching to system design for low-risk tasks and using AI as a high-fidelity simulator for critical, high-stakes skill development.

When AI does the entry-level work, what you should learn depends on what it costs to be wrong. AI is replacing entry-level roles, especially technical ones. In the US, Stanford found that since late 2022, employment in AI-exposed jobs like software and customer support fell 16% relatively for 22-25 year-olds. Employment for older workers in the same jobs stayed steady. Matt Beane at UCSB saw this happen in robotic surgery even before AI. Surgeons used to train the next batch of residents. But robotic consoles let surgeons do what residents did earlier, so they stopped bothering with residents. Pretty efficient, but, as Sridhar Vembu asks, where do the next architects come from? Who trains the next generation of experts? History gives us a few ideas. I see three patterns: switch, enforce, or level-up. Switch. Spreadsheets made manual ledger redundant. But that manual bookkeeping taught accountants how to catch errors. Eventually, bookkeeping clerks vanished but accountants didn't, because we switched what the job meant: from checking arithmetic to designing the tests to catch errors, to understanding the system. There are more accountants now than before. Enforce. When being wrong is too risky, we don't let the skill lapse. Autopilots reduced the demand for junior pilots and pilots' hand-flying time and practice. Air France 447 is a popular example of the consequence. Since then, regulators made manual flying mandatory through the FAA's 2014 extended-envelope training rule. Surgeons did the same: simulation centres rebuild what practice robots took away from residents. They mandate practice, simulate rare cases. Level-up. Chess engines should have made chess obsolete. A free phone app now beats any grandmaster. Instead chess engines became coaches instead. Today's young grandmasters are better than most chess players of the past and the game is more popular than ever. So what should you do? It depends on the kind of work, and what happens if it goes wrong. For most work, being wrong is cheap: A bad marketing email costs, a weak first draft, a broken deployment. These cause limited damage or you can undo them. Switch in such cases. There's no point learning what AI already does well. Delegate as much as possible to AI and get out of the way. Watch closely where it fails. Learn to do what AI does badly: choosing the problem, taking action, challenging the question. It's why I prefer interns who use AI agents and catch its mistakes, over experts who patiently write code that AI writes better. For some work, being wrong is expensive, or irreversible: a wrong drug dose, a wrong trade, a bridge, an airplane. Humans are the last line of defence, and Bainbridge showed the better machines get, the harder humans need to train, because their failures are rarer and bigger. Enforce in such cases. Build the skill using AI as the expert. Let it be the teacher who simplifies concepts, the Socratic partner that quizzes you, the clever friend who tries to trip you up with rare edge cases. Flight simulators and surgical sim-centres have been doing this for years. AI makes it cheap enough for everyone. The last type of work we do for its own sake: exercise, chess, sports, music. Machines beat us long ago, but we don't care. The output isn't the point. The process, the competition, the joy of mastery - that's what matters. Level-up in such cases. Use the machine as a coach and break records. Redefine what we thought was impossible. Most software is in the "switch" bucket. Delegate to AI, learn where it fails, and build skills around that. But if you're building mission-critical software, "enforce" skills using AI as a teacher and simulator. On the other hand, if you just enjoy coding for its own sake...

No juniors, no experts?


I now prefer interns over senior developers because they act as efficient thin clients to AI. Since traditional coding tests are obsolete, I evaluate candidates on their ability to nudge agents and own the final result.

Or, Why I Now Prefer Interns Over Senior Developers Ankor runs a company of several thousand people. After a bunch of calls with one of our interns, Varun (a student at IIT Madras), Ankor messaged me: "This guy is fantastic. How is he doing it?" This is what Varun was doing: he records calls, feeds the transcript to Claude Code / Codex, and delivers results. That's the whole process. He doesn't interpret the content. He doesn't apply domain knowledge. He gets out of the way. I gave Varun that instruction deliberately. I told him: "Ankor will say something. Don't try to understand it. You will not understand it anyway. Record the call. Transcribe it. Give it to Claude Code. Deploy to GitHub. Show Ankor. Take feedback. Repeat." Varun is thrice as fast at this than anyone with five years of experience. Weirdly, the experience is the bottleneck. Usha Rengaraju who leads Research at Exa Protocol, and the world's first female triple Kaggle Grandmaster, told me at a panel in Hyderabad this March: until 2024, she employed six to seven interns, predominantly from top Indian Institutes of Technology (IIT), at ₹3-3.5 lakh per month in salaries. Now, she's replaced them with artificial intelligence (AI), saving ₹60-70 lakh a year. She went the opposite direction from me. I'm hiring more interns than before. We're both right. Her work is greenfield prototyping where the model handles everything. My work requires a human in the loop - but one who doesn't slow the loop down. The intern is a thin client to AI. I teach a data science course at IIT Madras to 5,000 students each year. I design the exams. I iterate on them constantly. In March 2026, I pointed a coding agent at one of my own exams (22 questions, 45 minutes) to test if the questions were correctly specified. The agent solved everything in well under 45 minutes. The highest score any actual student achieved: 50 percent. Second highest: 33 percent. And I no longer have a clue of how to judge if an evaluation is easy or hard. This is a measurement crisis. My instruments are calibrated for a world where people produce the output directly. That world ended. The exam still ran. The scores still came back. But what they're... I have no clue anymore. So, I now use this as a feature. Before releasing any exam question, I copy-paste it into ChatGPT. If it gives the answer, I revise the question. I'm using AI to invalidate my own evaluation instruments in real time. (This is a strange sentence to write. I'm writing it anyway.) The hiring equivalent of this is what enterprise software teams are in their own interview loops. Karat's 2026 engineering interview report found that 62 percent of organizations prohibit AI in their technical assessments. But hiring leaders estimate more than half of candidates use it anyway. That's not a skills test. Maybe it's an honesty test? Actually, the candidates who pass are the ones who hide their tools, not the ones who use them best. CodeSignal's 2026 survey says 91 percent of software engineers use agentic AI coding tools, and 75 percent have shipped production code generated at least partly by AI in the past six months. Stack Overflow's 2025 developer survey puts AI tool adoption at 80 percent across developers globally. The take-home project doesn't measure what it used to measure. Nor does the GitHub portfolio. HackerRank's 2025 developer skills report makes it clear: standards good enough two years ago no longer are. The output no longer proves the capability. Anthropic's own two-hour engineering exam, when given to Claude Opus 4.5, produced a score higher than any human candidate ever. To be fair, the model was given several chances at each problem, and the exam measures technical ability under time pressure rather than collaboration or communication. But the direction is clear. Bnchmarks that screen humans now favor machines. What's left that proves anything? The question I now actually ask (when deciding who to bring in) is no longer "Can you write code?" It's: "Can you stop slowing down AI?" Accumulated domain knowledge is often a bottleneck. It makes people second-guess the model, rewrite agent output without reviewing, and retry approaches the model discarded. Usha still runs her coding interviews for important apps. ("I would still have them go through system design interviews, coding rounds." She paused, then added "in 2026". I agree - 2027's too far out.) In banking, pharma, and other regulated domains, expertise matters. A lot. Large language models (LLMs) can hallucinate and we need experts to catch them. But that's not most of software is delivering today. The industry is starting to get it. Meta runs coding interviews that allow AI coding agents. That's how real work happens anyway. Karat's NextGen assessment framework suggests realistic environments and expert interviewers evaluating judgment rather than the code. The question has changed from "Can you write code?" to "Can you define the problem, nudge the model, spot the wrong answer, and own the result?" I don't know what exactly to hire for. My answer keeps changing. But I know the old signals - hard work, practicing problems, time pressure - weren't what we were hiring for either. They were proxies that AI made easy. That's good. Clearly, we weren't measuring what we really wanted. What seems to work for me is: give them a vague problem, a coding agent, and 4 hours. See if they deliver useful output, and if they can explain what the agent got wrong. If they do that, I don't care about their resume. I'll hire them on the spot. Published at on 29 May 2026.

Thinking Beyond Automation to Safeguard Tomorrow’s Software Talent


I pranked my classmate at IIT Madras in 1993 by digitally merging a photo of his crush with a topless shot of him using Autodesk Animator and CorelDRAW!, then mailed the result to his family home.

It began in our second year at IIT Madras (1993). Shiuli Ganguly was an M.Sc. mathematics student, and Anand Thomas Lee was my classmate. And Lee (along with a lot of other people) had a rather high opinion of the lady in question. (He still maintains it. I got a mail in December 1996 saying that he'd tracked her down). However, the same opinion was not held of my computer abilities (understandably so). He bet that there was no conceivable way I could get a photo of Lee and his sweetheart together - by means fair or otherwise. Actually, I lost the bet due to the time constraint, but I did have my revenge. Lee and Shiuli One fine Mardi Gras (IITM's culturals) in 1993, I was roaming around with my camera when I spotted Shiuli. Mustering all the courage I had, and more, I asked her if she would pose - for the Best Face of MG Contest. She did, parting with a "You've made my day!" I sincerely hope I did. The next step was Lee. I knew there'd be no point in just merging two normal photos, so I got Lee to remove his shirt. He posed on the terrace of our hostel - topless. I got him to stand so that the shadow would roughly be in the same direction. Unfortunately, I'd loaded only a black and white film. But that eventually made my task easier. I was working for the campus magazines as publisher. That more or less gave me free access to considerable resources. I insisted that images needed to be scanned for the magazine, and managed to push in these two photos for scanning. Now I had all the resources I wanted. Pulling together all the image processing tools on the campus (Autodesk Animator and CorelDRAW! in particular) I set about removing the background from their images. Since I'd run out of time for the bet anyway, I had worked out a master plan by then. I put them both in front of the IIT gate, photographed the monitor and got what looked close enough to a real photo - though black & white. Our holidays had started by then. (That's what gave me so much time). I had cautiously obtained Lee's home address (as well as Baddy's and a few others', so he wouldn't get suspicious). Once the grades were announced, I looked up his and sent an innocent looking mail to him. Except that it was an unsealed envelope, marked "Personal & Confidential". Dear Lee, Your grades for this sem are blah blah blah. Life's fun here. BTW, I'm enclosing a copy of the photo you and Shiuli took near the gate. The whole class is shocked at your courage in baring yourself outside the gate! I know you asked me not to send this home, but I've marked the envelope "Personal and Confidential", so it's OK. Shiuli's wondering why you haven't replied to her for so long. Weather's fine here blah blah blah... Anand. As I expected, Lee's mother opened the mail! From what I here, it took him two days to convince his family that it wasn't really him standing topless with a girl near the gate. August 1993

Lee and Shiuli


I hacked my friend Lee's RS/6000 account at our Computer Center to win a high-stakes bet. I cheated by using a pre-installed SUID shell and a trojan horse to capture his passwords before the challenge even began.

I had lost and won some minor bets with Lee. It was time for a major coup. There was an RS/6000 installed at our Computer Center, and practically everyone had an account in it. So did Lee. (And so did Pavithra, but Jani told me to keep quiet about it, and besides, that's another story.) Lee was probably a bit irritated that I interfered with his talk sessions, and I was feeling too bored. We struck upon a bet. The deal was again a challenge on my computer abilities. I had to sneak into his ID within 15 days. The stakes were the crux of it. If I won, I'd get to photograph him with his arms around Pavithra (he didn't mind. Why would he?), and if he won...? Shom picked just the wrong time to walk by. If I lost, Lee would get to photograph me without anything on, with Shom holding my... (you get what I mean). The stakes were steep - for both of us. But there was a catch. For, you see, I'd accepted the bet for the simple reason that I'd already sneaked into his ID! Well before he'd logged in for the first time, I knew it would prove useful and took a copy of his SUID shell. He could change his passwords all he wanted (once he used 'iaminvincibleandinvulnerable' and another time, 'andreking' - and was trapped by my trojan horse). But to give an appearance of realism, I waited 13 days - undaunted by his jibes saying that I was giving up. I'm not sure he ever found out it was preplanned. Sorry, Lee! On the morning of the 14th day, I gathered a bunch of guys (and Lee, of course) and asked Lee to log in into his account. He was greeted with a message - my message - saying that a mail was being sent to Pavithra explaining the complete details of the bet. Lee was understandably horrified. Not only had he lost the bet, but the matter was being conveyed to the concerned party in the most disastrous way possible! (Actually, I'd sent a far more toned down version of the mail that he saw). He bunked classes, waited for her to come to the CC, got her to log in, and deleted the mail before she could see it! To date, he hasn't taken the photo, but we're still optimistic. August 1995 Comments Perl, 1994-2011 - S Anand 28 Sep 2024 10:21 pm (pingback): […] Build CCChat – the unofficial IITM email system and software […]

Lee in the CC


I recount a 1995 trip to Vizag where my IIT-M classmates and I relentlessly teased our friend Nandu after encountering his old classmate. I share memories of embarrassing him at a seminar and joking about his romantic history.

Nandu, Tangi, Jani and myself (four IIT-M guys, class of 1996) went for a seminar (Ripples) at Vishakhapatnam. Nandu lives in Vizag, BTW. On our first day, we went in and registered, and couldn't help noticing the gorgeous tall bespectacled dame who filled our forms. We thought no more of it until Nandu walked in to register, and coolly struck conversation with her for quite a while. It bothered me to no end. We cornered him outside and got him to spill the beans. Her name was Sailaja (he nostalgically uttered) and she was his classmate. The conversation beat around the same bush long enough for us to draw conclusions. Apparantly, she wasn't as good looking at school, but then, college changes people. That evening we had dinner at Dolphin, a 3-star hotel. It looked rather like a 5-star one, though. In the midst of a rather hearty meal, I hear my name being shouted. I walked up and observer Sailaja surrounded by our gang. Nandu introduced me to her (generous of him) and I greeted her with a "Yes, I've heard a lot about you." She was a bit taken aback. "From whom?" "Nandu, of course!" I looked at Nandu, who'd turned red. I couldn't figure out why, until (after some reshaping of my physical structure) he told me that it was almost identical to the response that Tangi gave her. One was bad enough, and here were two close friends of Nandu telling her how much he talked about her. Nandu's kindof sensitive about this sort of thing. Hmmm.... Something had to be done about this. The next day, we were having lunch, and Nandu appeared to be surrounded by a gang of girls. (I don't know how he manages it. How, Nandu?) I guess they were taking lessons on the art of diplomacy while presenting seminars, or some such obstruse topic Nandu is famous for. I let out a shout: "Nandu! Coming now, or do you want to freak out more with the girls?" There was a pause in conversation, and a horrified look in my direction. I wasn't to be put down. I shot back "Ok, freak out!" and walked out. I came pretty close to death that night. But what struck me as most intriguing about the whole thing was how his name and Sailaja's were found written together on the walls of the temple as we were climbing down. I was the first to discover it as we were walking down, and I certainly didn't have anything to do with it, did I? Postscript: Nandu is happily married to Madhavi as of now. Sailaja's whereabouts are unknown. October, 1995

Nandu in Vizag


I pranked my coworkers by claiming our new Windows XP laptops had 'transparent screens.' Despite the April Fool's date, my reputation for tech advice led colleagues to spend hours searching for non-existent settings and hardware cameras.

I had changed over the years, and had a sober reputation at BCG. I also had a reputation for giving solid advice about computers. Recently, our laptops had been upgraded to Windows XP. This was also the time the "transparent laptop" craze was rampant. Feeling fairly sure no one at BCG would be aware of this, I sent out a mail, towards the end of the day, on Friday 1st April 2005. (That should've given it away, but it didn't.) Hi everyone, If you're using the new laptops, be sure to check out the Transparent Laptop feature in Windows XP. Here's what it looks like. Picture of transparent laptop I mailed Have fun! Anand Saturday, 2nd April 2005. 4pm "Rrrrring...." "Hello, Anand here." "Hi Anand, Harsh. Yaar, how do you turn on that transparant screen? I've been fiddling around with the desktop properties, but I can't seem to find it. I would've called IT support, but it's Saturday. I've spent nearly an hour looking for it... (etc. etc.)" (interrupting) "Harsh, did you see the date on that mail?" "No. Why?" "It was sent on April 1st." Dead silence. "Oh shit! Good one." Monday, 4th April 2005. 9am "Hey Anand, I couldn't find the camera on the back of the laptop." "What camera?" "The one that's use for the transparent screen. I know the screen's transparent. So there's got to be one." Monday, 4th April 2005. 10am "If anyone other than YOU had sent this mail, I'd have dismissed it as a hoax. But YOU...?" Monday, 4th April 2005. 11am "Anand, please tell everyone that it was an April Fool joke!" "Why Jayesh?" "They're all asking me to upgrade their laptop to one that has transparent screens!" April 1, 2005 Comments Bharath Yadav 31 Aug 2025 11:53 am: 😆😆😆

Transparent laptops


I’ve shared my personal archive of book notes, primarily written in Markdown while reading or listening to audiobooks. These raw, informal records were often captured on mobile while walking, prioritizing quick capture over perfect formatting or spelling.

Book notes I take notes as I read or listen to books. Here are the notes. They're mostly in Markdown. They're meant for me. They may not be as clear to you. They're often written on a mobile while I walk. They may have spelling mistakes.

Book notes