Books, Bots, and Blind Spots

Steve Jobs once said,

"Yu can't connect the dots looking forward; yu can only connect them looking backward. So yu have to trust that the dots will somehow connect in your future."

Let me stretch that thought a little further.

If Jobs hadn't attended that calligraphy class and learnt about typography, perhaps the Macintosh would never have had the beautiful fonts it became famous for. One seemingly unrelated decision ended up influencing an entire generation of computers.

Now imagine if "vibe coding" or chatGPT or Claude or some similar AI stack existed back then.

Imagine if Jobs had simply learnt what was needed for the next task and nothing more. Maybe the Macintosh would still have been built. But would it have been the same Macintosh? Would it have carried the same attention to detail, creativity, and elegance?

This whole thought came to me on my recent flight from Mumbai to Bangalore.

The person sitting next to me was genuinely surprised to see me reading a thick technical reference book and asked me why I didn't ask ChatGPT to summarize it ?

That conversation stayed with me.

I told him that this is simply how I learn better. More importantly, I'm trying to understand the fundamentals behind the things I use and build almost every day—LLMs, databases, distributed systems, and much more.

Later, he mentioned he was a 2000-batch IIT B.Tech graduate. We started talking about IIT libraries, and I realized we both shared the same appreciation for spending hours with big reference books. (I loved the IIT library too. 😊)

Now, does this mean we shouldn't learn using AI?

Hell no.

I use AI every single day. I'm definitely not a 100% bookworm. 😄

Take my personal website as an example.

Instead of using WordPress, I'm building most of it myself. I use Codex and GitHub Copilot extensively. We discuss what I want to build, plan together, I let it generate code, and then I come back wearing my tester's hat to make sure everything behaves the way I expect.

For hobby projects like this, it works wonderfully.

But then I hit issues like canonical tags, CSS layouts, or some random frontend bug, and suddenly I spend half a day trying to fix something that someone with solid HTML and CSS fundamentals might solve in ten minutes.

That's when I end up learning on the go.

Now compare that with my day job.

Here, I can't skip understanding different machine learning models, ignore hyperparameter tuning, or wait for something to fail before learning how it actually works.

I need those tools in my arsenal.

I may not use every algorithm every day, but knowing they exist gives me multiple ways to approach a problem and, more importantly, choose the right one for the situation at hand.

Another thing I appreciate about textbooks, good courses, and even research papers is that they are structured.

They've been refined over years, sometimes decades. They build concepts layer by layer.

When I start learning something with ChatGPT, I usually begin with one question. An hour later, I've learnt a lot... but I'm often in a completely different place than where I started. Sometimes I skip important intermediate concepts without even realizing it.

With a book, I can go back and forth, revisit chapters, connect ideas, and slowly build deeper understanding.

For people who learn by doing—absolutely, yu learn a lot on the job.

But I still believe yu need a strong foundation to build on.

So maybe this is where I've landed—for now.

Pick a few areas in life that truly matter to yu.

Go deep.

Read the textbooks.

Read research papers.

Build projects.

Understand why things work.

For everything else, let AI help yu move faster.

Maybe that's the balance.

Or maybe, ten years from now, I'll read this post again and realize I was completely wrong.

Just another dot waiting to connect.

 

Vibe Surgeon

Doctor and GenAI -- I like to take an extreme example of a doctor and try to imagine different scenarios of docs using GenAI (LLMs) in order to replicate what engineers do or what we expect them to do and all that.

Maybe the stakes are very different, and I do believe that based on sensitivity and cost impact, different AI and analytics models can be valuable. But for a second, let us go back to the doctor in an operating theatre.

So, "vibe coding" -- imagine a Vibe Surgeon. A doc comes into the OT and uploads all reports -- maybe X-rays and a live video feed -- and asks AI to guide the surgery. Starting from which surgery to perform.

Now, say our doc knows just a little bit about tool use and how the human body works, and starts getting into the surgery. Then suddenly, he sees that this particular patient has some complications. This is realized after the initial cut. Then our AI goes into thinking mode, and after 5 minutes, again lists down 5 root causes and maybe 5 more things to look for, etc, etc. And our Surgeon follows it religiously and sees things worsening.

So here is my hypothesis, or one explanation: LLM models are trained on internet data, and they just predict the next word and then the next, and so on and so on. Common structures are bound to get higher probability, and so they will pop up more. One can tune some parameters and make the model more creative, and it will do that by matching words for very, very different domains that may or may not make sense. Meanwhile, here our patient's situation is worsening, and it turns out this is one of those edge cases. And even our GenAI is not able to fully understand the situation.

I don't want to comment on how it ends.

Marvel fan or not -- if you have watched Dr. Strange, then this paragraph may make more sense. Remember how our egotistical Dr. Strange looks at a few cases and says -- A, B, C -- simple or not worth my time or anyone else can do -- and then picks some unique case and he is like, "Yes, this is worth my thing," and all that. We need such experts. And with the way things are going on, these experts are going to be fewer and fewer. Already they are rare species, and 10 years from now? Phew. Just can't imagine.

Lesson or something -- well -- thanks for reading, but I don't have a specific takeaway for you. Just my thoughts, building a persona of a Vibe Surgeon, and I would love to hear from you.