# Computational thinking matters more than syntax mastery

Markdown copy of https://realalpha.app/s/computational-thinking-matters-more-than-syntax-mastery/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Amjad Masad](https://realalpha.app/builders/amjad-masad/) · Amjad Masad is founder and CEO of Replit. · Co-founded and leads Replit, a browser-based coding platform letting anyone write and deploy code.
- Host: [Reid Hoffman](https://realalpha.app/people/reid-hoffman/) · Co-founder, Manas AI · Co-founded LinkedIn; one of OpenAI's first investors; Greylock partner.
- Host: Aria Finger
- Show: Possible
- Episode: [Amjad Masad on vibe coding, AI agents, and the end of boilerplate](https://realalpha.app/v/xPDQXfS_vTE/), Jan 7, 2026
- Moment: 15:46 to 20:40 of the episode (5 min), playing on https://realalpha.app/s/computational-thinking-matters-more-than-syntax-mastery/; the episode from there: https://realalpha.app/v/xPDQXfS_vTE/?t=946

## Quote

> “I would focus more on the **abstract concept of computation** as opposed to, again, null is not an object type of thing.”
> — [Amjad Masad](https://realalpha.app/builders/amjad-masad/) at [18:11](https://realalpha.app/v/xPDQXfS_vTE/?t=1091) · Possible

## Takeaways

1. Practice breaking problems into clear, communicable parts.
2. Teach computational concepts, not just language-specific syntax.
3. Understand that LLMs produce probabilistic, sometimes inconsistent results.

## About this segment

Amjad Masad argues that communication and breaking problems down matter more as AI handles code. Learners still need concepts such as databases, persistence, and probabilistic systems.

From “Amjad Masad on vibe coding, AI agents, and the end of boilerplate”, Jan 7, 2026. [Watch the full episode](https://realalpha.app/v/xPDQXfS_vTE/)

## Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

[15:53](https://realalpha.app/v/xPDQXfS_vTE/?t=953) programming in natural language. That's a great segue to one of the questions I've been thinking about is like, what is the New literacy is the highlight, because obviously, you know, previously literacy was reading and writing, and part of how we get to a massive elevation of humanity is through as broad-based literacy amongst the billions of people as we possibly can, because what enables everything else enables learning, enables cultural evolution, enables patterns of thought.

[16:18](https://realalpha.app/v/xPDQXfS_vTE/?t=978) Now, with the no-code code, you know, kind of like the vibing as opposed to vibe coding or the, you know, whichever, that's a new form of literacy. So say a little bit about how you think about this new form of literacy. And then also add in a little bit is like one of the things I think is I think actually, in fact, everyone's going to be having a coding co-pilot, whatever, a coding, vibe coding.

[16:42](https://realalpha.app/v/xPDQXfS_vTE/?t=1002) Because just like that CEO or anything else, it's like that's now part of just the way that you would also write. Like write an email or anything else as we're doing it. So give a little bit of this kind of literacy and future of how everyone's going to be navigating thinking and information spaces. Well, the first thing I will say is that soft skills, I think, are more important than ever. So for a while in the U.S., at least, we're all with STEM, STEM, STEM.

[17:08](https://realalpha.app/v/xPDQXfS_vTE/?t=1028) And STEM is still really important. But I think, you know, you have a lot of engineers going to work right now and they don't really are not very good at communication and like talking about ideas. They're good at writing the code, translating some of those ideas into code. But I think now the way we see our product being used by product managers, for example, product managers are some of the best vibe coders because they're really good at taking problems and breaking them down into their constituent parts and communicating them very well to the machine.

[17:39](https://realalpha.app/v/xPDQXfS_vTE/?t=1059) and then like the machine can, can build them. So whatever we do, if it's like a question about education in our education system, it needs to get better at much, much better at like being able to take problems and breaking them down. There was a hype word, like I think 10, 15 years ago called like computational thinking. And like people were building startups around teaching people computational thinking.

[17:59](https://realalpha.app/v/xPDQXfS_vTE/?t=1079) And I think that's still important because underlying all of this is still computational. So when you're describing an idea to an LLM to build it, you need to be able to talk about databases. You need to be able to talk about persistence. You need to be able to talk about lists and things like that. So if I'm designing a computer course for young people, I would focus more on the abstract concept of computation as opposed to, again, null is not an object type of thing.

[18:26](https://realalpha.app/v/xPDQXfS_vTE/?t=1106) Part of that to elaborate is not only is the baseline computation about what the three of us learned, even if it goes all the way back to freshman year, CS, Yes, which it tends to be a very deterministic, algorithmic, data structures, memory management, other kinds of things. But also I think what's going to happen is we're going to bring in a set of other computational concepts. I think it'll be probabilistic concepts.

[18:48](https://realalpha.app/v/xPDQXfS_vTE/?t=1128) Yes. Because actually most of like LLMs and everything else is very interesting. It's probabilistic. Right. I think it'll be maybe even quantum, but a bunch of other things where compute is not just like 1 plus 1 equals 2. There's a richer sense of compute. Yes. Have you seen any of that yet with Replit? or is that still kind of in the glimmerings of what's coming? We see the problems of not understanding it.

[19:08](https://realalpha.app/v/xPDQXfS_vTE/?t=1148) We see the problems of user not understanding that it's a probabilistic system, it's a stochastic system, they expect results to be reproducible and all of that stuff. So 100%, I think the future is understanding these concepts really well. And by the way, once you understand them, you can predict how these tools might work and you can go from one tool to another and still have the same mental model understanding of it.

[19:29](https://realalpha.app/v/xPDQXfS_vTE/?t=1169) In the same way that when I was growing up, I really understood how computers work and that'll allow me to build all these businesses and programs, whatever. Understanding how LLMs work is going to be very, very important. Now, the problem is most people's experiences with ChatGPT that is trained to sound like a friend, you're not getting raw access into the LLM in order to figure out how to program it.

[19:51](https://realalpha.app/v/xPDQXfS_vTE/?t=1191) And so we just introduced a set of AI integration. So now if you ask for AppLite, like make me an app that takes a prompt, generates an image model, audio model, puts it in. together or something like that. It's so simple. You don't have to do anything. Just put in that prompt. It will tell you, we're going to use OpenAI for this. We're going to use Gemini for this. We'll take care of the billing.

[20:07](https://realalpha.app/v/xPDQXfS_vTE/?t=1207) We'll bill you on behalf of them. But I feel like there needs to also be a sort of UI. I don't think we've invented the UI for how to mix and match these LLMs and how to program them. So as much as I am a big believer in natural language-based programming, I think at some And at some point, as agents get better and they're working most of the time in the background, we need to invent the new interfaces for how to program these machines.

[20:33](https://realalpha.app/v/xPDQXfS_vTE/?t=1233) Well, also, I mean, you said that most people,