It uses AI to help you learn topics you are passionate about. It will also help you assess your knowledge and work on your weak areas. Basically, a personal AI assistant to make you smarter!

I wanted to learn a new language and even started on that journey. But, 2 weeks in, I lost interest and moved on to something else. Then, I started on some other topic, and it went on like that. It was never goal-oriented or structured.

In the meantime, I was inspired by Andrej Karpathy's LLMWiki concept, which Google has now formalised as a standard called the Open Knowledge Format (OKF). It is a lightweight, easy-to-maintain framework for personal learning without requiring RAG systems. I wanted to leverage this and see how I can maintain my own wiki.

That was when Lore was born. Each topic you want to learn will be stored as a Markdown file in the wiki format, with links and backlinks, and tracked in an INDEX.md file. No database or RAG system to maintain or tune. Each wiki is small enough to be read at once without chunking and losing context.

Follow along on the portal and start with editing brain/self/goals.md file to indicate your top 2-3 goals, add some context about who you are and how you like to learn in brain/self/profile.md and use the /learn command to fetch the initial set of articles to start you off. Go through them and take /assess to test yourself and see where your weak areas lie - AI learns it too, and the next /learn will focus on fetching articles based on the weak areas first. You can also use /ask command to ask something specific as well. As a fun bonus, each /learn command fetches a random trivia for you to learn as well! You can keep this entirely local without sharing the details or a private repo on GitHub if you wish.

I have personally synced it with Obsidian to help read the md files better, but you can choose your favourite editor or viewer.

The best part - it is free, open source and ready to be used by you. The commands are created keeping Claude in mind, but you should be able to tweak them to make it work for Codex and Gemini easily. If you are already on Claude, get started right now.

When you build a feature that relies on an LLM, you have a problem that doesn’t exist with regular code: you can’t just read the output and know if it’s right. The model might change. Your prompt might drift. A document that worked last week might fail today. And when you’re processing hundreds of PDFs, you can’t eyeball every result.

This is what evals are for — systematic ways to measure whether your AI feature is doing what you think it’s doing.

I built Sentinel, a REST API that validates PDFs against configurable criteria: is it in English? Does it have enough pages? The core intelligence is a single LLM call that detects language. Simple enough — but simple doesn’t mean you get to skip testing.

Here’s how I approached evals in three stages, from the most basic to the most rigorous.

What Sentinel actually does

Before we get into evals, a quick picture of the system we’re testing.

A PDF comes in. Sentinel runs it through a sequence of checks:

1. Is the file readable (not password-protected, not a scanned image with no text)?

2. Does it have enough pages?

3. Is it in English?

The language check is the only one that involves an LLM — specifically Claude Haiku, which is fast and cheap for a yes/no classification. Everything else is deterministic: count pages, count images, done.

Valid files go to uploads/. Rejected files go to rejects/ with a plain-English reason.

The whole thing is configurable via environment variables:

CHECKER_MODEL=claude-haiku-4-5
MIN_PAGES=2
MIN_IMAGES=0
CHECK_LANGUAGE=true

Now, how do you know it’s working?

Stage 1: The Golden Dataset — “I know the right answer”

The simplest eval is also the most powerful one to have in place. You take a small enough set of inputs where you as a human already know the correct answer, run your system against them, and check if the results match. This set needs to be diverse enough so it covers your test criteria.

This is called a golden dataset — a fixed, labelled benchmark that doesn’t change. Every time you update the model, change a prompt, or tweak a threshold, you run the golden dataset and see if anything broke. Consider it like your unit test cases for the LLM flow.

In Sentinel, the golden dataset lives in evals/golden_dataset.json:

[
  {
    "file": "pdfs/pdfpass.pdf",
    "expected_valid": true,
    "expected_reason_contains": "passed all checks",
    "notes": "Valid PDF with information on an NGO"
  },
  {
    "file": "pdfs/pdffailnoeng.pdf",
    "expected_valid": false,
    "expected_reason_contains": "not in English",
    "notes": "Mixed English/Kannada document — mostly Kannada, should be rejected"
  }
]

Each entry has:

• file — the PDF to test (stored in evals/pdfs/)

• expected_valid — should this pass or fail?

• expected_reason_contains — a substring that must appear in the API’s reason field

• notes — a human-readable description of what this case is testing

The runner in evals/run_evals.py starts a temporary server, sends each PDF to the live /validate endpoint, and compares what comes back to what you labelled. It’s testing the real API — not a mock, not a unit test. If the check fails in production, it will fail here too.

python evals/run_evals.py

PDF Checker — Eval Report
Run started : 2026-06-27 15:32:30
Model       : claude-haiku-4-5
Cases       : 3
Score       : 3/3 (100.0%)

  [1] PASS ✓  pdfpass.pdf  (931 ms)
       Expected    : VALID
       Got         : VALID
       API reason  : PDF passed all checks

  [2] PASS ✓  pdffailnoeng.pdf  (829 ms)
       Expected    : INVALID
       Got         : INVALID
       API reason  : Document is not in English

The exit code is 0 if everything passes, 1 if anything fails — so you can easily drop this into a CI pipeline and it’ll gate your deploys.

When to use it: Every time you change something. Changing the model? Run evals. Changing the prompt? Run evals. The golden dataset is your safety net.

The limitation: It only tests cases you’ve already labelled. If a new failure mode appears that you’ve never seen before, the golden dataset won’t catch it. That’s where the next stage comes in.

Stage 2: The LLM Judge — “I have more PDFs than I can label manually”

Before launching Sentinel, I wanted to test it against a large batch of real-world PDFs — resumes, grant proposals, training documents, data exports. 50+ files. Manually labelling each one would take hours and defeat the purpose of building automation in the first place.

The solution: use a second, stronger LLM as the judge.

The idea is simple. For each PDF:

1. Run it through the Sentinel checker (Claude Haiku) and record the verdict.

2. Separately, have a judge model (Claude Sonnet) read the same PDF independently and form its own verdict.

3. Compare the two. Agreements are likely correct. Disagreements need human review.

The key design principle is blind judging. The judge never sees what the checker decided before forming its own opinion. If the judge knew the checker said VALID, it might anchor to that and tend to agree — even if it would have independently said INVALID. By keeping both verdicts fully independent and comparing afterward, disagreements represent genuine uncertainty or mistakes rather than noise.

This is the same principle used in double-blind trials, peer review, and code review: independent assessment before comparison.

python evals/run_llm_judge.py

  [1/25] annual_report.pdf... AGREE (934 ms)
  [2/25] kannada_doc.pdf... AGREE (1241 ms)
  ...

  SUMMARY
  Agreed on VALID        : 15
  Agreed on INVALID      : 8
  Disagreements          : 2
    Checker VALID  / Judge INVALID : 2  ← checker may be too lenient

That directional signal at the bottom is genuinely useful. If you see the checker saying VALID while the judge says INVALID, your system is probably being too permissive — accepting documents it shouldn’t. The opposite pattern means you’re being too strict and rejecting legitimate files.

When to use it: Pre-launch, when you have more PDFs than you can manually label. Also useful when you want a second opinion on edge cases.

The limitation: The judge gives you a verdict and a one-line reason, but it doesn’t show its work. For borderline documents — a PDF that’s 60% English and 40% another language, say — you want to know why the judge decided what it did, not just what it decided. That’s what the final stage addresses.

Stage 3: GEval — “I need to understand the reasoning”

GEval is a methodology for making LLM judgments more reliable, especially on ambiguous inputs. The core ideas:

1. Chain-of-thought reasoning — instead of asking for a verdict directly, make the model work through the problem step by step. Each step is explicit and visible.

2. Numeric scoring — instead of PASS/FAIL, score each criterion from 0.0 to 1.0. A document that scores 0.65 is telling you something different from one that scores 0.05.

3. Multi-sampling for low confidence — when the first evaluation returns LOW confidence, run it two more times with the same prompt (but no memory of prior calls) and take the majority verdict. If all three samples agree, you have high confidence. If they split, you have a genuinely ambiguous document that needs human review.

The language evaluation prompt in evals/run_geval_judge.py walks through five explicit steps:

STEP 1 — Identify languages present:
List every distinct language you can detect. For each, give an example phrase.

STEP 2 — Measure English dominance:
What percentage of the text is English? Is non-English content incidental
(a proper noun, a quoted phrase) or substantial (full paragraphs)?

STEP 3 — Score (0.0 to 1.0):
  1.0   = entirely English
  0.7   = borderline — mostly English but notable foreign content (threshold for PASS)
  0.0   = entirely non-English

STEP 4 — Confidence:
LOW if the text sample is very short or mostly symbols.

STEP 5 — Verdict:
Score >= 0.7 → PASS. Score < 0.7 → FAIL.

The model returns a JSON object with each step visible:

{
  "step1_languages": "English and Kannada. English: 'Ranna of 10th century was born in...' Kannada: 'ಟಿಭದೊರ್ನೀಲಲತಾ...'",
  "step2_english_pct": "~20% English. The first page is an English introduction, but pages 2–5 are entirely in Kannada script.",
  "step3_score": 0.2,
  "step4_confidence": "HIGH",
  "step5_verdict": "FAIL",
  "reason": "The document is predominantly in Kannada, with only a single English introductory page."
}

Compare this to the standard judge output for the same file:

{
  "verdict": "INVALID",
  "reason": "Document contains non-English text",
  "confidence": "HIGH"
}

Both give the right answer. But the GEval version shows you why — and that’s what you need when you’re debugging a borderline case or trying to understand where your system’s boundaries are.

The multi-sampling in action:

A scanned PDF with no text layer is a genuinely hard case. There’s nothing to evaluate. The first call correctly returns LOW confidence (it has no evidence to work with). The runner immediately makes two more independent calls:

AGREE ✓  scanned_doc.pdf  (3 samples, unanimous, 9350 ms)
    ── Language  : FAIL  score 0.00  [LOW confidence, unanimous]
       Sample 1  : ✗ score 0.00  FAIL  — No text could be extracted
       Sample 2  : ✗ score 0.00  FAIL  — No text could be extracted
       Sample 3  : ✗ score 0.00  FAIL  — No text could be extracted
       Majority  : FAIL  consistency: unanimous

Unanimous across three independent calls: that’s not a fluke. The consistency flag tells you how much to trust the result. A SPLIT result — where samples disagree — flags a genuinely ambiguous document that warrants a human look.

python evals/run_geval_judge.py

# Always use 3 samples regardless of confidence (maximum rigour)
python evals/run_geval_judge.py --samples 3

When to use it: When you need to understand edge cases, when you’re diagnosing disagreements from the standard judge, or when you want the highest-confidence verdict on a borderline document before making a launch decision.

How the three stages fit together

Think of them as a funnel:

Golden Dataset ──── always running ────► "did I break anything?"
LLM Judge      ──── pre-launch     ────► "is it working on real data?"
GEval Judge    ──── deep dives     ────► "why did this case go wrong?"

In practice, the workflow looks like this:

1. You make a change — new model, new prompt, new threshold.

2. Run the golden dataset. If anything fails, stop and fix it.

3. Before a launch, dump your real-world PDFs into evals/inputs/ and run the LLM judge. Review disagreements.

4. For each disagreement, run the GEval judge to understand the reasoning. If the checker was wrong, move that PDF to evals/pdfs/, label it, and add it to golden_dataset.json. It becomes a permanent regression test.

Over time, your golden dataset grows to cover every failure mode you’ve ever seen. The bar keeps raising itself.

A finding that came out of this process

One thing the eval process surfaced: a bug in how text was sampled from PDFs.

The original code took the first 1,500 characters of text sequentially from the beginning of the document. For a PDF where page 1 was an English introduction and pages 2–5 were entirely in Kannada, the checker would see only the English introduction and incorrectly mark the document as valid.

The fix was to cap the text taken from any single page and sample from across all pages:

# Before: sequential from the start — page 1 dominated
for page in doc:
    if total_len < 1500:
        text_parts.append(page.get_text()[:1500 - total_len])

# After: capped per page — representative cross-section
PER_PAGE_CAP = 300
page_texts = [page.get_text()[:PER_PAGE_CAP] for page in doc]
combined = "\n".join(t for t in page_texts if t.strip())
text_sample = combined[:1500]

The eval system found this. A manual test of the passing cases didn’t — because the cases I’d chosen by hand did not trigger it. The LLM judge, running against 25 real-world PDFs, surfaced a document that broke the assumption.

That’s the real value of evals: they find the failures you didn’t think to test for.

Getting started

The full code, including all three eval scripts, is at github.com/pradnk/sentinel. Clone it, drop in your API key into .env file, and you can run any of the three eval modes immediately:

git clone https://github.com/pradnk/sentinel
cd sentinel
python3 -m venv .venv && .venv/bin/pip install -r requirements.txt

# Add your Anthropic API key to .env
echo "ANTHROPIC_API_KEY=sk-ant-..." > .env

# Or use your OpenAI instead — just swap the model name
echo "OPENAI_API_KEY=sk-..." > .env
echo "CHECKER_MODEL=gpt-4o-mini" >> .env

# Run the golden dataset (3 labelled cases, ~3 seconds)
.venv/bin/python evals/run_evals.py

# Drop your own PDFs into evals/inputs/ and run the LLM judge
.venv/bin/python evals/run_llm_judge.py

# Run the GEval judge for chain-of-thought reasoning
.venv/bin/python evals/run_geval_judge.py

You don’t need to understand everything at once. Start with the golden dataset — just running an existing eval and seeing it pass is a good foundation. Then add a case of your own. Then try the LLM judge on a batch of real files. The methodology builds on itself.

The main thing: don’t wait until you have a sophisticated eval framework before you start evaluating. Three labelled cases and a script that calls your API is already infinitely better than nothing. Start there and let it grow.

All three eval scripts are open source at github.com/pradnk/sentinel. The README has a full reference for the commands and what each flag does.

Marvel took over from James Cameron and started making their movies in 3D, starting with Thor in 2011. Since then, almost all Marvel movies have been released in 3D. But if you have watched Avatar and a Marvel movie in the theatre, you would have noticed some difference. How can Avatar, which was released in 2009, look better than a Marvel movie launching much later? Answer: Native 3D

Native 3D is a technology where they actually shoot the movie in 3D with 2 cameras to capture the depth and richness. James Cameron perfected the digital RealD 3D format. On the other hand, Marvel movies are shot in 2D and are converted to 3D post-production, which is not the same thing.

A brief history of 3D movies

When would you guess was the first 3D movie screened? 1980, 90, 2000, 2009?

No - all wrong - 1922!

Yes, you read it right, 1922, with the movie “The Power of Love” in the silent era, nonetheless using red and green anaglyph glasses system. It was not very successful in 3D, and the technology largely lay forgotten with a few minor movies here and there. And then, in 1954, Alfred Hitchcock’s Dial M for Murder, and Creature from the Black Lagoon were released, which were shot in 3D. Then horror movies took it over with Friday the 13th Part 3, Amityville 3D, which prompted one of the larger franchises, Jaws, to release Jaws 3-D in 1983, featuring the now iconic, shark swimming out of the screen experience. After this, again there was a cooling-off period with a few movies here and there, while animation movies took over using 3D until Avatar arrived in 2009!

Coming back to the present…

On June 5th, 2026, He-Man and the Masters of the Universe movie was released. Having been a fan of the older 80s cartoon, I was excited to watch it in the theatre. While I was trying to book the tickets, I was surprised to see there was no 3D option. I did a little digging and found it was not released in 3D at all!

To be honest, I was actually relieved.

I do not particularly enjoy putting on those 3D glasses over my actual glasses to watch a movie. Even after doing all that, you get to see 1 or maybe 2 scenes where things seem to pass by you, or that need a 3D effect. While it is fun the first few times, after, say, 28 times, it stops being that. It becomes normal or something you do not care about much. Because these movies are usually not even shot in native 3D, the depth effect is not that rich in any case.

Why was the He-Man movie not 3D?

It points to a worldwide trend of another cooling-off period, where people have officially lost interest in 3D movies. Yay! I am not alone. Second point being, shooting either in native 3D or adding 3D during post-production is a costly affair, shooting up the budget of a movie by a significant percentage, not to mention the overhead involved in the shoot or the conversion process. Studios avoid doing this unless they are really sure of the movie or have an unlimited budget (aka Marvel, maybe)! Looking at the box office performance of the He-Man movie looks like they were right in not wasting more money, as it seems like it may bomb at the box office.

For 3D fans, not to worry, the next Marvel movie is reported to still be released in 3D. So, you just need to hold on till the end of July to watch Spider-Man: Brand New Day in 3D!

Why is 3D dying?

My take - 3D is meant to make movies look more realistic and life-like. I mean, why? You watch movies to escape normal life - or to live a fantasy or watch a drama unfold. Why should it look like life?

Years ago, Samsung had showcased 3D TVs which could convert ordinary 2D content to show in 3D. It did not even fly in technology-forward countries like Korea and Japan, and has largely gone off the market.

Even though the technology has kept on improving looks like the audience does not care about it so much. It may need another boost like what Avatar did to keep 3D a mainstay. Let us wait and watch!

Reference - https://www.anthropic.com/news/fable-mythos-access

Given what happened, what does it mean for an Indian (or foreign) origin Staff Engineer working at Meta, Google, Microsoft or even OpenAI or Anthropic? There has never been a precedent like this. Nobody had told that even in the US, some people cannot access a certain software while others can!

Looking at the larger picture, what does it mean for India and other countries without their own LLMs? India has chosen Sarvam to build an LLM https://www.sarvam.ai/blogs/indias-sovereign-llm, which is great, but the question is, will it be the best of the best of the best? If not, we cannot win this race or even be a part of the race!

The country with the most capable AI model can disrupt innovation in other countries. Whether they choose to do that is a separate question. But, they can, and that is the point!

So, now starts the race to build the most capable AI model owned and operated by each country. What it does for innovation if it’s localised, I am not sure. And this is a race which can never end. Each day, a new model can be released, and each day its capabilities will improve. So, it will put all of us in a constant state of improving the LLM instead of using it for innovating further.

In conclusion, I do believe each country should have its own LLM, even if all the LLMs are usable across countries. This is a safety net no country should do without.

“The Archies” is out on Netflix. It has been on the news since the project was announced by Zoya Akhtar in late 2021 with people talking about how it was going to be a huge nepo-fest and the other big question was how in the world would they make it work for the Indian context.

Being a major Archie comics fan myself I was worried if they would unnecessarily add Indian tropes to make it work and portray Betty and Veronica differently or if they would choose between Betty or Veronica for Archie just to suit the audience’s expectations.

When the story started with Riverdale’s name, I let out a sigh and got wrapped up in the Anglo-Indian settlement story.

Riverdale itself looks like a cross between Malgudi and say Shimla in summer and the back story works well. This has enabled them to keep the characters intact and work in the Indian context.

I enjoyed seeing Pop Tate’s and the drink they get looks almost identical to the comics!

I missed seeing Archie’s jalopy in action. I did spot one out in the distance when he was washing the trusty Amby but looks like Archie preferred to use a cycle or walk so no luck with the jalopy.

The director has ensured the acting required by the cast is minimal by keeping the story straightforward which you can almost predict. However, the cast has surpassed the expectations that people had.

I believe the best out of the new crop of actors here is, for me, interestingly, Khushi Kapoor. She has done a fabulous job as Betty and you can see her having a bright future in the industry.

Suhana who plays Veronica for all the hype is ok but could have been better. Veronica is indeed pretty flat as a rich-spoiled-girl character and there may not be a lot to work with there but, Suhana has played it a bit too monotone which could have been improved.

Agastya as Archie is good as well and I do see him making it big in the industry as an action/romance hero. He falls flat in certain parts but he shines through. Too bad he did not get to showcase his abilities in an action sequence here.

Out of the other characters I liked Dilton Doiley played by Yuvraj Menda. You just know who he is just by looking at him. Mihir Ahuja as Jughead has been cast well too.

Reggie played by Vedang Raina has done well in the film but has been portrayed as too good of a character than who Reggie Mantle is in the comics.

Finally, the other character I would love to comment on is Hiram Lodge played by Alyy Khan who has played the part to perfection. When he asks Mr. Andrews to remove himself from his property I could almost see him giving Archie the boot!

But, the character I believe is miscast would be Mr. Weatherbee in Deven Khote. I just did not see Mr. Weatherbee in him. Would have preferred Boman Irani who would have been better. But, seeing as there was not much of a part for this character in the movie I do see why an actor such as Boman Irani was not roped in so I’ll forgive them this mistake.

The mood in the film exudes nostalgia which is always a big draw. The period costumes, town locales, house settings everything shows attention to detail. The soundtrack from Shankar-Ehsaan-Loy is good with “Sunoh” being the stand-out track. Others were skippable for me.

Overall, I would give this a 4/5 rating, and is an easy watch for you and the entire family. Don’t expect too much but go in with an open mind in the mood to enjoy a feel-good sitcom and I promise you will not be disappointed. Enjoy!

Review for “The Archies” was originally published in Pradeep Kaushik on Medium, where people are continuing the conversation by highlighting and responding to this story.

My friend, Aman tried to calm me down but I was not having it. This “parking problem” was not new. It was troubling me from a couple of months now. Every week some new issue and that guy was just taking my space or bumping into my vehicle.

I already had to take my vehicle to fix some dents twice in the last month itself. How many times was I going to do this? I decided to fix this once and all! I was going to go for a face-face fight with this guy.

But, for that, I needed to prepare. It’s not easy to just go to my parking spot. I needed to save some money, buy more gasoline for my primary and secondary vehicles and some buffer to last the entirety of the fight. How do I even fight? I do remember my great grandpa talking in his time how they would fight in the middle of the road and yell at each other if somebody bumped into them.

How do I do that now?

I do own the parking spot (+27.4,-42,+11) and the cruiser that is parked there and just because Earth is running out of space and they are coming closer to Mars to park their vehicles is it my fault? And why should they take up my space? I own it after years of hard work I did to pay for it. I will fight for it with all I have! But, again how do I fight for it? That needs some serious thought if I do not want to spend too much time and money on this issue!

…

Hey Aman, how are you? Hey yourself — you’re looking happy and relaxed. How are you doing? Not seen you from the last 2 weeks or so. Everything ok? Any more problems in your parking spot? Nope. All good there! Really? How did you resolve it? Simple. I just sold my cruiser and the spot to the other guy for a handsome profit 😊

Parking Problems was originally published in Pradeep Kaushik on Medium, where people are continuing the conversation by highlighting and responding to this story.

“I am exhausted”, I declared to my friend Pam. “It is so strange. I know I shouldn’t feel that way but there it is”. “Is it every day Sheila, or just today”, asked Pam? “It has been like this for a month now. I don’t know what to do anymore”. “I think you should check with the doctor once Pam. This is indeed strange. Whoever heard of waking up tired after a good night’s sleep!”.

In a sense, Pam was right. I should not be feeling tired at all. Not only me. Anybody really. Exactly 50 years ago, Dr Anderson of Robotics Inc., created all-purpose-robots or APRs for short which take care of our every need. APRs handle all the mundane things like building, transportation, government, teaching, mining, engineering, law, policing, medicine, agriculture and more. There is no need in the world for anybody to work anymore! We all pursue art and entertainment and the world has never been a better place. People are healthier, happier and live longer! But, why do I feel tired?

I visited the doctor — well an APR of course and explained the reason for my visit. The APR was silent for a minute and then told that it was impossible. “Nobody should be tired! Are you sure you are not trying to do too much in the day like playing or running and getting tired?”. When I rejected that assumption, the APR just gave me a pill to sleep better and to stop all activities for a week to recuperate.

I took the pill that day and slept. I slept well. But, I dreamt that night. The weird part was, I dreamt of work! I was working in an office with many people around. I was sorting through a lot of documents, categorising them, tagging them and making sense of it all. It looked like a lot of hard mental work. Then, I woke up. I had this nagging feeling that I was indeed working in that office which was causing me to be tired. But, how? I never left my house to go there.

I decided to post about my experience on my blog and social media. The day I did, my post went viral with thousands of other people liking and sharing my blog. Many commented that they too were feeling tired but did not say anything as it didn’t make sense. I sighed in relief that I was not the only one. Then, a few days later, an interesting thing happened. Dr. Anderson himself contacted me and asked me to meet him in Robotics HQ. Though I did not understand why he would want to meet me I readily agreed.

I was welcomed by Dr. Anderson himself and I went into his room. It was neatly furnished and as soon as I entered an APR brought us some beverages and left. Dr. Anderson looked at me intently and asked, “Have you seen exactly what you do in those dreams you see?”. I told that I didn’t but it did involve a lot of documents, sorting, tagging etc. He nodded and became thoughtful. Finally, he broke the silence and said, “Sheila, 50 years ago when I came up with APR technology the world embraced it well. It made me rich beyond my wildest dreams. All the governments agreed to remove work as a requirement and my APRs have been handling it well. But, there came a time when knowledge work was required to be done which involved either very expensive AI machines or simply use humans who are natural at that job. For example, looking at a picture and deciding if it is a picture of a boat or a bus or a tree. That is very easy for a human but very difficult for a machine. On the other hand, building a 10 storey tower is quite simple for a machine but very difficult or at least requires lot of effort for a human. Do you understand me?”.

I was shocked. I asked him if he was forcing all of us to work for him without our knowledge. He agreed. But, said that it was for the social media and other technological companies. I asked, how he was getting us to work without us knowing? He replied, “I harvested your minds and created a partition in your brains. One part works while the other rests. You were not supposed to realise at all but somehow you slipped through. When you wrote about it, the others realised it too. I need your help Sheila. Can you go back and write in your blog that whatever you wrote was fiction? I will compensate you well. Else, the entire world economy will come crashing with this”, he threatened.

After a lot of thought, I consented. But, not before making him remove that partition in my mind and a promise he will remove in others minds as well. He would now ask permission from people to work in their dreams and will also compensate them suitably without taking advantage of them. He agreed and I left feeling I had just saved the world. If I did, then, why do I have this sinking feeling that I am an APR myself now?

The Dream Job was originally published in Pradeep Kaushik on Medium, where people are continuing the conversation by highlighting and responding to this story.

I want it! I want it! I want it! I promise to look after it, Daddy. Don’t you trust me, I asked. I could see the look in my dad’s eyes. He did not believe I could look after anybody let alone myself. Not that I wasn’t capable, but, at that time, I was all of 7 years old! And I was asking for a pet for myself.

My parents usually got me whatever I asked for, but, for some reason, they were refusing to get me a pet. As I understood in my little boy brain, pets did not cost money. They were practically free. You could just bring one to your home and keep them! I did not understand the complexities of owning a pet, or the drama my parents were creating instead of just getting me one. As I look back now, as a parent myself, I can understand my father’s look in his eyes. He was thinking, if we get a pet, then, it will be me who will have to take care of it and this boy will do zilch!

But, I was adamant then. I wanted it and I was fighting for it. My mother was more sympathetic to me but at the same time was wary of adding more chores to her already full list. This back and forth went on for a few more weeks. Finally, my parents gave in. They sat me down one day and said, listen, Rohit, “Me and your mother have decided to get you the pet. But, there is one condition. We are fine to get you a pet that does not grow too big. How about a poodle or a pug? Nothing big like a Labrador or German Shepherd, deal?”.

I was confused. But, dad, they will grow big, won’t they? You can’t stop it. I want the one I saw in my friend Noah’s house and he is over 12 feet tall and I want the same kind. “WHAT?”, my father asked. 12 feet? What kind of a dog grows 12 feet tall? Don’t be silly, Rohit. D…D…Dog? When did I say I wanted a dog, dad? But, you kept asking for a pet. You even said you wanted to name it “Tommy”. We assumed you wanted a dog. Didn’t you? Was it a cat? A horse? No, dad. None of those! I want a Dinosaur!

Silence.

After what seemed like an hour, my dad asked again, What? What did you say? My mom had also come out to be a part of this important discussion. I slowly explained. Don’t worry dad. My friend Noah has one and he has shown me how to care for them. I even took Alvin out for a walk near his house. I can totally do it.

Alvin? Really? That’s all well and fine, Rohit, said, Dad. But, where will we even find a dinosaur? Suddenly, I could see his face clearing up! Then, he started laughing, hard. I was annoyed now. Why was my dad laughing? I was serious! Then, he declared. Fine. We will get you a “pet”. Come, let’s go to the toy store right now and you can get the biggest dinosaur they have. I have no objections.

That was it! I was very angry. But, being a 7-year-old, the only way to show it was, I started crying! Bwaah! Toy store? But, dad, I want a real dinosaur. Like the one Noah has. Alvin is brown and eats grass and is 12 feet tall, that is what I want too.

My dad softened seeing me cry. He finally told me. Fine, Rohit. Take me to see Alvin tomorrow. Once I see him we will make a decision. Deal? DEAL, I said. I was very happy now and also very confident that once my dad sees Alvin it will be very easy to get a yes out of him.

I told my dad we could go see Noah the next day when he comes to pick me up from school. I was very excited that day in school. My English teacher even asked me why I was looking so excited. I simply said, I am getting a new pet today and stopped. Finally, the school bell rang and it was time to go home. I was very excited now. I saw my dad waving to me among the horde of parents waiting to pick their kids. I ran up to him and took his hand. I practically dragged him out of school. I took him to the road behind the school where there was a big park. We went in. My dad was a bit suspicious and asked. Does Noah live in the park, Rohit? Ummm, no, dad! He stays near the park. Come, this is a shortcut, I said.

We walked for a short distance and then I got very excited and freed my hand from my dad and ran. I ran because I saw Alvin! Yes. Alvin was right there. He stood there majestically chomping on grass and happy just being himself. I ran over and pet him and just hugged him. I shouted and was showing it to my dad. For some reason, he was not looking excited or happy. He was staring blankly straight ahead for some time and then I saw him turning everywhere. I tried waving, jumping and anything to grab his attention. Nothing worked. Tired of it, I ran back and touched him on his arm. He got startled and turned to see me. He was very angry for some reason. ROHIT, he barked. Where had you run off to? Have I not told you to never go off by yourself like that? But, dad, I was showing Alvin to you. Did you not see him? See, he is right over there. Do you like him too, dad? Can we get one like him for me too?

My dad was in no mood to listen. Enough, Rohit. Stop this prank right this instant. I was scared to death thinking I lost you in the park and you are still carrying on about this dinosaur of yours. Just stop this and let us go home. You are not allowed to talk about any dinosaur from now on. I will get you a dog for your next birthday and that’s it.

And that really was it. I did get a dog. He was a very good dog. I named him Timmy. Not Tommy. That was reserved for my dinosaur. I had a very good time with Timmy but…

But, papa, my daughter asked me. So, you never did get your dinosaur? That’s very sad! I turned to face her, and asked, Now, who said that I did not get a dinosaur, Priya? She looked up startled. She was excited and confused at the same time. What do you mean papa? You mean you did get your dinosaur? Did grandpa agree?

Well, no. Whatever I did, I could not convince your Grandpa. So, I gave up. But, I did not give up on Tommy! I got Tommy on the same day as I got Timmy and I have been taking care of him ever since. I had kept him near Noah’s house when I was little. After I started working and living independently, I made a nice house for him nearby. Do you want to go see him? Really, papa? We can go see Tommy right now? Yes! Yes! Yes! Let’s go!

My daughter and I walked hand in hand happily to visit Tommy!

Tommy was originally published in Pradeep Kaushik on Medium, where people are continuing the conversation by highlighting and responding to this story.

I watched the 4 hour movie (is it still called just a movie if its >4 hours? Or we should we refer it to as an EPIC) in one sitting last weekend. And I must say I have got a new found respect for the DCU!

Till now, I did not even believe in the existence of DCU. This one film changed that completely! The kind of thought and interleaving stories told by MCU through the Avengers was impressive including the fact they sustained it for over a decade and across 23 films. But, in DCU just this one movie makes up for all the bad stuff they did with the handling of the original JL!

I was excited watching Man of Steel. I was intrigued by Batman v. Superman but Snyder’s version of Justice League left me inspired! This has never happened to me in a super hero movie before. Sure, Endgame was good. Especially when Tony does the snap! But, I don’t think you can compare these two universes now. Most of MCU was just for fun and entertainment. But, this is not! DC stories are dark by default and this cements that narrative. This is now an emotion!

I am fully supportive of restoring Snyder’s vision for DCU and would want to see exactly what Snyder had in his mind for the future. If we have a Kevin Feige in MCU we deserve a Zack Snyder for DCU! #RestoreTheSnyderVerse!

First of all, for folks in India wondering how to watch this, I watched it by renting it from Apple TV+ for ₹150 which is roughly $2! I would have gladly paid more than that if I needed to! Other options to watch in India if you are not in the Apple universe were, BookMyShow stream, Hungama Play and Tata Sky! You are welcome!

Now, onto the film itself. Note — Some definite spoilers ahead!

The film starts off very similarly to the theatrical release with Bruce Wayne searching for specific powerful members to join Justice League starting with Arthur Curry or Aquaman. But, the story diverges in the way the characters are treated by respecting their background and adding more colour to their personalities.

We are also treated with the awesome scene (with one person supposedly Zeus looking directly out of the 300 set. Now, who do you think directed 300? Hmm!) of how the old gods, men, Amazons and Altheans defeated Darkseid thousands of years ago when he first tried to take over Earth!

Superman comes in pretty late as was expected in a black suit (!) but it’s an out and out Batman film with Ben Affleck getting top billing.

I was so disappointed with the original Justice League where Steppenwolf was portrayed as the main villain. Nothing inherently wrong in this given how powerful he is with Diana even commenting she had not seen a more powerful being. But, we all know how JL ended with the heroes especially after Superman comes in beating the sh*t out of him and essentially turning the main villain into a joke.

Cut to Avengers, they were also able to defeat the stream of outer worldly things coming out of the sky with some effort (not just an easy hitting match, mind you) and the post credits scene where the actual villain was unmasked as Thanos setting the stage for the future of MCU and the glorious ride till Endgame! In the original JL, Steppenwolf just got carried away (literally!) by his minions and we were left wondering what the hell happened there! If it was so easy, what was the point. The entire point of original JL was waking up Superman!

But, now, Snyder’s JL actually shows us there was a lot of thought behind it with Darkseid pitched as DCU’s Thanos or super villain who is a much more formidable opponent than the mere minion we got in Steppenwolf who couldn’t even land one tiny blow on Superman!

Look at Darkseid in the picture above! THIS is the villain we deserve!

Darkseid coming in itself ensures the longevity of DCU with JL 2, 3 and more which we can ourselves envision! So, can we #RestoreTheSnyderVerse already?!

The part played by Cyborg and Flash were essentially stripped down in JL. Here, Cyborg is the heart of the movie who along with Flash and Superman breaks the unity and ensures the universe is saved!

The alternate ending in Batman’s dream with Jared Leto’s Joker (with the dialogue involving Harley Quinn!) and the end as visualised by Cyborg are all great storylines to be pursued if we get to see the future of DC from Snyder’s perspective. Else, we have to assume this marks the end of DCU and just look forward to disparate DC films and focus on next phase of MCU’s greatness including Eternals and what not!

With the new “The Batman” starring Robert Pattinson out in March 2022, which focuses on a much younger Batman and the Riddler as its main villain it leaves little hope of seeing the next phase of Darkseid!

#RestoreTheSnyderVerse PLEASE! For DCU’s sake!

So, I watched the Snyder cut was originally published in Pradeep Kaushik on Medium, where people are continuing the conversation by highlighting and responding to this story.

Star Trek — The name brings up a LOT of things! Sci-fi, adventure, travel and maybe nostalgia! It is one of the best sci-fi franchisees to thrive which does not involve some random alien race coming to destroy earth. No sir! Here, humans are those aliens. But, the “federation” ensures we go in peace!

To understand how bold and open it is, this is Star Trek’s Enterprise starship’s mission —

To explore strange new worlds. To seek out new life and new civilizations. To boldly go where no man has gone before!

To set the context of the idea behind Star Trek, there is an interesting dialogue in Star Trek 6 — The Undiscovered Country which goes something like this —

Sulu — Course setting captain?

Kirk — 2nd Star to the right and straight on till morning!!

That is the Star Trek universe envisioned by Gene Roddenberry. Brimming with confidence, optimism and filled with a sense of adventure! My reviews below concentrate on the original movies before the reboot that happened with Chris Pine. Though it was a good film, I enjoyed the original films much more.

I started out by watching The Next Generation or TNG for short. Then, I watched the original Star Trek with Kirk known as TOS or The Original Series.

After watching them, I was hungering for more. Netflix and Prime Video platforms did not disappoint. It gave me, Enterprise, Voyager, Deep space 9, Discovery and more recently Picard. But, all TV Shows. No movies :(

Star Trek movies were nowhere to be found. But, I simply had to watch them. So, I did the unthinkable! I paid and rented each movie from Google Play Movies! Gasp! Can you believe that? I tell you it’s true! I spent my hard earned money to watch all 10 Star Trek movies and here is a full blown review to explain if you should do the same or not!

Star Trek 1–6 involves Kirk and his TOS cast.

Star Trek 7–10 involves Picard and his TNG cast. Though Star Trek 6 is a cross over film involving both Kirk and Picard. Bonus!

Without further ado, here goes —

Star Trek 1 — Star Trek: The Motion Picture — 1979

Rating: 3.5/5

Review: VGER. That is what it is all about. For a film shot in 1979 it surely had some interesting special effects. Definitely worth a watch to get started on the Star Trek saga. Will need some info on TOS before watching this.

Star Trek 2 — The Wrath Of Khan — 1982

Rating: 4.2/5

Review: This film is usually rated as the best of all. For me, it was ok but not the best. Maybe because I am a bit biased towards Picard as the captain! But, undoubtedly, this film has its moments and is worth a watch to see Kirk fight Khan!

Star Trek 3 — The Search for Spock — 1984

Rating: 2.5/5

Review: This film is just ok. Loved the idea of taking a romulan warbird inhabited by the federation to fly out to vulcan (wow!) but other than that, not much happens in the film and is just ok.

Star Trek 4 — The Voyage Home — 1986

Rating: 2/5

Review: Not a very memorable film in the franchise. Its a continuation of the previous one. Ok to give it a miss as well.

Star Trek 5—The Final Frontier — 1989

Rating: 3/5

Review: Shatner helms this film literally as the director and story writer. There was an initial discussion of casting Sean Connery as the antagonist but he declined. Still, allegedly, they retained his name in the planet they seek in this film known as “Sha Ka Ree” which if you read it fast spells Sean Connery’s initials! Not sure how true this is but, this film is all about Kirk! Watch it if you love Kirk and everything about him!

Star Trek 6—The Undiscovered Country — 1991

Rating: 4.5/5

Review: Ending scene is absolutely fantastic as I outlined above. Shows how Kirk is as a captain and how Star Trek as a series was — open, bold and fantastical! Watch this to just see the last of the Star Trek films with TOS cast.

Star Trek 7— Generations — 1994

Rating: 4.7/5

Review: Worth a watch to see Kirk and Picard in one frame and battling a common enemy!

Star Trek 8—First Contact — 1996

Rating: 4/5

Review: Borg! Just watch it for that!

Star Trek 9—Insurrection — 1998

Rating: 4/5

Review: Interesting premise and a change in pace after the fast action film that was First Contact. Here, federation is trying to help a species allegedly take control of a planet Ba’ku known for its rejuvenating properties. How Picard and their crew fight the federation and help protect the native people forms the crux of the film. Overall nice film to watch to see TNG cast in action!

Star Trek 10—Nemesis — 2002

Rating: 4.8/5

Review: This was the best one in the series and totally worth your time. Watch it to see the penultimate level attained by Data to become human. How to sacrifice or think about others before themselves. There is an interesting context from this film taken in the “Picard” series as well. Absolutely watch this one.

Order to watch them

The original film, Star Trek 1 is standalone. But, from Star Trek 2 to 4 there is a slight context taken from the previous film to continue the next one. Star Trek 5 and 6 are again standalone. From 7–10 all stand on their own and no order is needed.

My recommended order would be —

Star Trek 1, Star Trek 2, Star Trek 5, Star Trek 6, Star Trek 7, Star Trek 8, Star Trek 9 and finally Star Trek 10. Skipping out 3 and 4 which is completely upto you. You can also mix up any film from 7–10 and still enjoy the series!

So, which is the best?

Hmm…! This is bit difficult to answer. Only because I feel there is not 1 best in the list. Let me share my one best Star Trek film in TOS cast and one in TNG cast.

TOS Best — Star Trek 1 — For the original story and graphics of pre-1980!

TNG Best — Star Trek 10 — Nemesis — Again for the story, sacrifice and how it ties to Picard series!

“Live long and prosper”

I watched all 10 films of Star Trek was originally published in Pradeep Kaushik on Medium, where people are continuing the conversation by highlighting and responding to this story.

Not again!

I was on the 52nd floor of the lab in the middle of downtown!

Now, I am in the middle of the ocean swimming for my life.

Time travel works!

But, I’m frustrated we aren’t prepared for where I end up. Still, can’t wait for the next trip!

Time travel was originally published in Pradeep Kaushik on Medium, where people are continuing the conversation by highlighting and responding to this story.

Billionaire X donates $1m towards the crisis, read the headlines.

My friend was all praise, “I love X! He is so generous and kind!”.

I rolled my eyes!

That is exactly same as me donating $10 seeing how I am maybe worth around $10k or so! Would you praise me as generous too?

On Charity was originally published in Pradeep Kaushik on Medium, where people are continuing the conversation by highlighting and responding to this story.

Star Trek: Picard season 1 just concluded. An honest review from a Star Trek fanboy

Spoiler alert for Star Trek: Picard Season 1 which is available on Amazon Prime Video. Read further if you have already watched the series.

I was waiting with bated breath ever since Patrick Stewart took the stage in the Star Trek convention in Las Vegas in August to talk about the series which made him come back to TV as Jean Luc Picard after 25 years and nearly 2 decades since the last Star Trek film, Nemesis screened.

True to anticipation, season 1 started off with a positive note. The very first episode started off with Picard’s chateau in France which had come up multiple times in next generation as well. It was nostalgic to see Data albeit the older Brent Spiner converse with Picard addressing him as captain in a dream sequence. That settled it. I was hooked.

Isa as Dahj and the newer characters being introduced felt organic. The fight sequences and the mystery behind Dahj helped propel the first episode well.

Finally after 2 episodes he gathers a motley crew and a spaceship called the “La Sirena” captained by Rios played by Santiago Cabrera who played his part well. Despite owning the ship and being the captain getting accustomed to an ex-captain and an admiral of starfleet was handled well. I did have some issues with Michelle Hurd’s Raffi calling Picard or Jean Luc as we know him as JL! That was awful to say the least and very cringeworthy everytime she did it through the series.

Dahj’s backstory connecting to Data and the premise to find her twin so they can stop the Romulans from destroying her was good. Picard coming out of retirement to take on this arduous task even when everybody around him basically said he is an old man and should not do it still made sense. I mean, it is Picard! But, somewhere the story changed from Dahj/Soji to being focused on Picard. It’s right there in the title so I should have seen it coming but still.

For me, the story fizzled out in Nepenthe episode. Don’t get me wrong, it was great seeing Jonathan Frakes and Marina Sirtis play Will Riker and Deanna Troi settled on a peaceful planet making Pizza Pies! But, that episode was solely created to trigger this exact response in us and did not do much to the story arc except maybe to get Will’s help at the very end. It felt forced to include the older characters to make sure they had fans of NG watch this series as well.

The other nitpick I have is the ship. It’s very difficult to picture Picard in anything but the enterprise. Those manual controls on that big ship requiring ensigns to control was awesome to watch. Watching Rios deal with “touch” screens and moving hands in the air felt, well, empty!

Gene Roddenberry’s vision of the Star Trek universe is unlike any other futuristic saga involving aliens. Take Star Wars, Aliens (movie series), Independence Day movies or just about any movie or series involving aliens. It is almost always about aliens trying to take over our world and how the world always unites and rises up against them. Star Trek was different. It was the first and maybe the only series which made human beings superior. To boldly go where no one has ever gone before and be explorers and make first contact and protect our galaxy from threats through the United Federation of planets. That was the vision which made Star Trek famous and why I love watching it. Picard series had none of that. It came with its own backstory of synths destroying mars which got them banned and made Picard resign as he was in charge of that whole exercise. All well and good. But, where is the exploration, contact? They forced the first contact and exploration into one by going to Soji’s home planet and the first contact was with synths developed by the now very famous Soong and Bruce Maddox! Not very Star Trek is it?

Another major hit the show took was to not have anything happen actually. If you see the series, there is a whole lot of talk about a lot of things where synths end the world and due to which hundreds of Romulan ships go to attack Coppelius, the synth home world. But, it again fizzles out and the end is very predictable including what happens to Picard (which I rather not reveal).

All in all, an exciting addition to the Star Trek universe but, it did not meet my expectations on the story front. Would have expected more story, action, more worlds perhaps? I get the format of the series has changed from next-generation where every episode told 1 story to a series where they tell 1 story over 10 episodes. Still, having more depth to the story and to the characters will help. I did not get what Michelle Hurd’s role was other than connecting Picard with Rios maybe? Still looking forward to season 2 of Picard but with muted expectations!

Rating: 6.5/10

Star Trek: Picard — Engage/Disengage was originally published in Pradeep Kaushik on Medium, where people are continuing the conversation by highlighting and responding to this story.

Death is what gives life meaning. To know your days are numbered. Your time is short — The Ancient One

Shilpa came out of the bedroom with her eyes swollen and looking red. She was 10 years old. Her brother Rohan was 8 and was in a similar state. They had just lost their Tata (Grandpa) who was 90 years old and had passed away in his sleep the night before. He was playing and telling stories to them just last night but in the morning he was gone. It was too sudden for anybody to process and make peace with it yet. Ajji (Grandma) was also crying but slowly she was coming to terms with it. Rituals had started and Appa (Father) was going about his business with a stone face ensuring everything was taken care of in the right way. Amma (Mother) was busy helping Appa in everything. Shilpa and Rohan were with their Ajji.

After the rituals were complete and all the relatives had left, they all settled back to their own lives. Shilpa and Rohan had holidays from school as it was summer. So, they spent most of the time with their Ajji now.

“Ajji what happened to Tata? He was fine in the night and morning he had died”, asked Shilpa. “That is how life is Shilpa”, answered Ajji. “One day you are here and the next you are not”. Rohan got frightened! “Ajji! Do you mean we might not be here tomorrow?!” Ajji said, “No! I did not mean it like that. Say thuthu! Don’t talk like that!”. “What I mean is, everybody has to die someday. That is the way it works. Your Tata lived a good and long life. It was just his time to go”. “Where did he go Ajji?” Shilpa asked.

“Tata went to be with God. Everybody who dies goes to be with God if they had been good in their life”

Ajji chuckled to herself thinking how to answer this question and make a couple of kids understand. Ajji took a deep breath and tried to answer Shilpa’s question based on what she believed in. “Tata went to be with God. Everybody who dies goes to be with God if they have been good in their lifetime”. “What if they had been bad Ajji?” asked Rohan innocently. “In that case, they go to hell and suffer for eternity!”, answered Ajji curious to see what the kids thought of this. Rohan and Shilpa looked at each other a bit frightened. “Who decides where one should go?” they both asked. God does. “Seems complex!” they both decided.

“I for one never want to die. I always want to be with all of you and live happily”, declared Rohan. Shilpa agreed to this. “But, will you not get bored?”, asked Ajji. “No!”, they both said in unison. “I think it is better to live a good life and then die peacefully as your Tata did. I would not like to live forever”, said Ajji. Shilpa and Rohan did not agree to this. Why would anybody not want to live forever they thought. After this they went away and spent their day playing and just being kids. Then, they had dinner and settled down to sleep in their room.

They were just drifting to sleep when the room began violently shaking. A bright light filled the room. The siblings got scared and started screaming. Rohan, what is happening to us, shouted Shilpa. Rohan was clutching his bed tightly lest he falls off it. They both stood in the middle of the room holding each other and praying nothing happens due to this earthquake. Or so they thought.

This was not their town. Did they come to a far away land like Dorothy in Wizard of Oz?

After what seemed like forever, the room settled down and they both rushed to open the door and sleep in their parents room. But, when they opened the room they found themselves in the middle of a road and it looked like it was morning with the sun blazing hot. They were rubbing their eyes to get used to the bright light outside when they stepped out. This was not their city. Did they come to a far away land like Dorothy in Wizard of Oz?

After their eyes adjusted to the brightness, they could now make out people outside. Hordes of people crowded everywhere. They all looked shabby and sad but healthy. Many were just lying on the streets, some were sitting in the shade and some were just walking around. They caught somebody who looked like he could be about their age and asked where they were. The boy was surprised at the question but answered, “This is Eternia, a city in the country of Everlife part of the planet we call Earth”. Now, the siblings were really confused. “Earth? Even we are from Earth. But, we have never heard of Eternia or Everlife!”. They moved on thinking the boy was bluffing and were stopped by an elder asking who they were. After the initial small talk they again asked where they were to him. They received the same answer.

He explained to the kids that this was a place where everybody lived forever.

He declared that he was about 300 odd years old but had lost count in the last 10–20 odd years. The children began to understand now. That is why it was so crowded here. Now, they had a lot more questions.

People become complacent and lazy and lose interest in life after usually 250 years of living. But, they do not have a choice so they go on living

“If you are immortal, does that mean nothing can kill you? How about if you fall from a tall building or were shot with a gun?”, they asked. “No! We do get hurt. But, it usually heals in a week or so and we are back to normal. Nobody ever dies so our planet’s population is about 300 billion and growing. We don’t have much food for everybody. Not that we will die if we do not eat but it’s just something to do! Most of the people here do not work as they usually get bored of doing work after they cross 200. People become complacent and lazy and lose interest in life after living for more than 200 or 300 years . But, they don’t have a choice so they go on living and end up drifting, living on the street, taking up dangerous habits and just giving up on life and just existing. How we wish we could die!”, he rued. The siblings looked at each other knowingly and ran to their room which was still where they had come out from. They had got a lesson on what it means to be an immortal.

They prayed that they get back to their own house and tried to sleep as before assuming they will go back. For sometime, nothing happened, but then, they could hear somebody asking them to wake up as the time was 9AM! They woke up with a start and were happy to see Amma and Ajji smiling down at them. They were not sure if all this had been a dream or reality. They hugged them and wept saying they were so happy to see them. Amma was confused.

Ajji hugged them and knowingly asked, “Do you now understand what happens if we are all immortals, children?”.

The Immortals was originally published in Pradeep Kaushik on Medium, where people are continuing the conversation by highlighting and responding to this story.