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22. George Vettath on reskilling with low code , the axe and chainsaw

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Podcast with George John Vettath Part 3


Podcast with George John Vettath Part 3


George shared his views on convincing management to start digital transformation using low code. You just have to justify that need for the application that should be with the board, but then you get five quotations and try to call vendors. Then it's all about speed and efficiency and how well you deliver. George pointed out that the financial service is the sector with the most complex needs. AI is crucial and AI is rapidly picking up. And I think that while the low code is not so well known, AI is well-known everyone knows that AI is happening, but in the same way this low code revolution is also happening. AI is doing a lot of valuable work in education. The way it's being added into companies is happening in phases. Companies are experimenting. Singularity is probably 15 years away. Most companies will go through those three stages: insights, decision, support, and decision takeover. One by one and each project is being treated as a separate ROI. George thinks that over the last two years companies have developed use cases and that these are successful as well as are getting better. Companies that want to accelerate reskilling should consider using low code or no code tools as an HR strategy. This is akin to the axe and chainsaw story. Companies that want to drive agility and digital transformation on complex big apps will have to use low code to enable speed to market.

Notes and transcript can be found here:

[00:00:00] Andrew Liew Weida: Hi, everyone. Welcome to the AI of mankind show where I share anything interesting about mankind. I'm your host for this season. My name is Andrew Liew. I work across four Continents and 12 international cities. Also, I work in tech startups across a range of roles from selling products, making customers happy, figuring out fundraising, making finance tick, building teams, and developing sticky products. Apart from building startups. I've also worked in fortune 500 companies as a chief data scientist or technologist or people leader. You can call me Jack of all trades or master of learning. I hope to make this podcast show a great learning experience for us In each season, there is a series of interesting things that I invite guests to share their views about their life and interests.

[00:01:09] Andrew Liew Weida: Now let the show begin.

[00:01:27] Andrew Liew Weida: In the previous episode, George offered his views on how can low code enable agility especially on creating complex apps . He also explain how will low code help in completing the specification requirements from 80% to 100% and why big brands low code companies have billion dollar valuation. This episode continues the part 3 conversation with George and George shared his views on convincing management to start digital transformation using low code.

[00:01:51] Andrew Liew Weida: Let's continue.

[00:01:52] Andrew Liew Weida: So let's suppose that a CIO or CEO say, Hey, George, I'm still listening to this podcast. Let's have a chat. I wanna build something with you. Now, what would you say to them to, how do they gonna build a business case to justify to the board, to use low code for their solution? Help them, give them some advice base.

[00:02:14] George Vettath: It's actually very simple. Just get five quotes. From five different vendors, get a quote from us. Also, you'll find that we win. both price and speed. We will be better. Okay, fantastic. You just have to justify that need for the application that should be with the board, but then you get five quotations and try to call vendors. Then it's all about speed and efficiency and how well you deliver. And that has been written in your contract.

[00:02:39] Andrew Liew Weida: So in terms of the solution, does it cover a range of spectrum from different industries, like banking, finance, logistics, or like this low code thing is very niche, like how does it work?

[00:02:50] George Vettath: Yeah. I call it a transaction-oriented system. It doesn't matter which industry. So we have done almost 30 different types of applications in different domains, all domains. We have done financial services. Software services. You name it. we've got that.

[00:03:05] Andrew Liew Weida: Among them, 13 verticals or 13 sectors or industries can you give us an example of which industry you think has the most complexity and why?

[00:03:17] George Vettath: Its hands down financial services run on software.

[00:03:20] George Vettath: Almost everything is centered around financial services, so that's why complexity there, but financial services, a lot of compliance-related implications, and that's why pace is slow for them. We don't blame them. Think that they've gotta deal with a lot of regulations around the, and so they, they all move slowly, but they that's where the most needed. However, the ones that move fast are really the startups that can quickly build apps, and we, the existing incumbents. So it ranges. We've seen all sorts of things, but we have definitely seen that. Service-oriented companies are the ones that need it most.

[00:03:51] Andrew Liew Weida: Okay. So you have financial services. They are the most complex . But, when you mentioned financial services, are we talking about like a hundred apps or 200 apps? That's why it is so complex or is just so happened at you only deal with one project or something like that?

[00:04:04] George Vettath: Very nature of the financial service organization is complex and I think it depends on its size of it. As I mentioned earlier, numbers are fortune 500 means thousands of apps. SMEs means 200 or 300 apps. So it's very complex since here we are juggling with that. Across industries everybody has lots of apps to get developing. Low code is now general solution for all.

[00:04:23] Andrew Liew Weida: So in summary, you're saying that they decided to go with you to build out that project or whatever system that you want. And then once you have what I call workflow, then you digitize the workflow that generates data. So now where do you see AI in the process of digital transformation?

[00:04:41] George Vettath: Okay. AI is crucial and AI is rapidly picking up. And I think that while the low code is not so well known, AI is a well known everyone knows that AI is happening, but the same way this low code revolution is also happening.

[00:04:53] George Vettath: Now, as far as AI is concerned, I'd say that it's moving very rapidly in the consumer-oriented space . For example social media. You can see that it's predicting what articles you should see or what ads you should see now they're getting better at that. Take e-commerce, delivery apps are getting better and that's because there's an AI agent able to initially would to take half an hour to reach your home is reaching your house in 10 minutes. That's possible because AI is doing a lot of valuable work. In education. And a lot of things are happening on various fronts where AI is concerned. IOT devices are automatically recording things so it's a big topic altogether, but AI is across the board. The way it's being added into companies is happening in phases. Companies are experimenting. Now I'll break it up into three possible stages. The first stage could be more like quick insight. Is help. It is supporting it is not managing.

[00:05:46] George Vettath: So for example, a chatbot would help you to give to a response just to something you need, but chatbot would sometimes be wrong. A joke that I've just. Now I got support called the chatbot is going fine. And suddenly it says, okay, you can find more details in this link and I click on the link, it shows me another language and language. So it got it 80% right and then get it wrong. So they're getting better at it. So insights are coming in. Like when you type ahead on Excel, it suggests the next column for you. So this kind of insight comes. The next sales stage is going to happen in general, in B2B businesses, when planning decisions start being taken by the system because AI is now better than people. Because they've got dealing with a lot more data.

[00:06:21] George Vettath: And I don't know what will happen after that because when the machine is now suggesting better than the person then comes singularity, but that's probably 15 years away. Okay. But essentially those three stages, everything will go through those three because insights, decision, support, decision takeover, and companies are slowly doing these steps. One by one and each project is being treated as a separate ROI. Small project. Take the next one. And I think over the last two years use cases that are successful are getting better.

[00:06:49] Andrew Liew Weida: So you're saying that AI has been very useful in generating insights in augmenting decisions. Now we are living in a post-COVID-19 world and a lot of people have to work remotely. And a lot of apps are being digitized. What do you think about the impact of AI or artificial intelligence in the development of the future of work?

[00:07:09] George Vettath: Okay. Future of work. I'm not very good at predictions, so no one is. But essentially we can all see that it's all moving to a hybrid work. People would work at home or come to the office depending on the situation. And HR has got a lot to deal with handling the policies related to working hybrid. Now I think the bigger problem is just ensuring that the systems work in place and better tools are available for people to work better from home, like how you've seen all these remote working tools happen. If you ask me where the prediction will happen, I think it'll go back from hybrid to a 100% work from anywhere situation where, because the meeting rooms are going to be the center of artificial intelligence. Where you are planning a meeting, a lot of the meetings will be intelligently set up and when you're meeting. You will feel like you're talking to people, even though they're halfway around the world, you will have our Avatars of yourself sitting on the conference room table while you are not actually in there. And yet you will see like you're in a meeting, but to do all this, there's a lot of AI and a lot of hard work to happen and I think it's gonna take years before it actually happens, but definitely, the pandemic itself accelerates this situation. One fine day. I will realize that you don't need to leave your home for anything, including work. You can sit at the home and do your content, your meeting, et cetera. And I don't know what kind of world that will be, but that will happen sometime, maybe 10 years from now. So you can predict the path between now and then for all that.

[00:08:31] Andrew Liew Weida: I see. Okay. So it's a hybrid form of work. Some people will work at home. Some people will come to the office and the meeting rooms are where there are a lot of applications of AI. It could be transcribing notes, it could be taking voice to text. It could be even scheduling meetings. And so that's could be the future of work. Now having said that people need to adapt to new behavior. People need to, use low code. Big companies, small companies, everybody needs to skill. How does low code enable the skilling of people, whether is it tech people or non-tech people to enable the companies to move fast with digitization?

[00:09:05] George Vettath: Low code directly helps it. Low code will help build better apps to ensure that people can use the term self learn more. Everything is moving towards self-learning, a lot more towards self-learning or maybe collaborative learning. Okay. And topic-based learning rather than going through a large program.

[00:09:21] George Vettath: So the way the Udemy and the Coursera of the world are coming on with better and better programming programs or people are having shorter courses specifically to learn. I want to learn ML for example. Prediction, what I think would happen is career paths are set up by a combination of a company is whether a so if you're a consultant or individual or freelancer, you set up your own career path, whereas you are a company you would set up a career path for, let's say, high performers or different people have different career paths and you accelerate that by, enabling them to participate in virtual courses conducted internally or externally. And the quality of the courses is going to get better and better as we have better content and better tools like virtual reality, which will make it even more better.

[00:10:00] Andrew Liew Weida: I was thinking more along the line: companies big or small have been traditionally hiring software engineers and let's say the latest language is, angular, Java script. They will get them to learn angular, and Java script. And then they have to learn, and the learning curve can be quite steep if a guy who's Java coming to Java script or R coming to JavaScript, but let's say they were to use stragility or some other low code platform because it is so easy to use. The learning curve is very short and therefore they are able to learn and put it into production very quickly. What is your view on that?

[00:10:34] George Vettath: Low code will help the people who are building applications, learning to do things better. But I think that flexibility has to be built by the person who's building the application that is flexible enough to handle different situations. Like today, there are apps in learning and there are apps for running virtual universities today. There are apps for running set for an individual, sitting at home to set up a training program, and setting up a bunch of courses on their own. There are apps to put your content in. All kinds of apps are coming out there and it's getting innovative. So I would rather give the credit to those innovative companies to improve the low code, the learning and development area rather than low code per se. .

[00:11:14] Andrew Liew Weida: So you're saying that there is more innovation in learning and development apps. It doesn't matter whether the guy is using traditional software engineering or using low code because the learning curve is the same.

[00:11:27] George Vettath: It doesn't matter what the tools that people use are something like. Whether you use one brand or concrete to build a building on another building. And that is a building that needs to be built so let's leave it to the developers to decide what platform they're going to use.

[00:11:40] George Vettath: Low-code is more of the construction material whereas the actual app is built by companies, by individuals building these apps. So that's where all the innovations going to happen. So I'm not putting low-code here. I'm putting more, more like the quality of the apps, which determines how well learning.

[00:11:57] Andrew Liew Weida: Ah, so you're saying the quality of the application production is also a factor, even though you can have a low code that makes it easy for the developer to use it.

[00:12:08] George Vettath: Absolutely because it's like this if earlier I was using wood to build a building and now I have concrete. it's still that those days the people are building using wood to build nice houses.

[00:12:17] Andrew Liew: This is how I see how low code makes learning easy to build a better core workforce and keep talents in today's world. traditional software engineering is like using an X to chop a tree.

[00:12:26] Axe chopper: Listen to the axe being used. Look at the axe after I chop with serious effort.

[00:12:37] Andrew Liew: Now low code is like using a chainsaw to chop the same tree. , yeah. And then a chainsaw definitely will be faster than X,

[00:12:45] Chainsaw guy: So let's get started. (Listen to the chain saw cutting the tree)

[00:13:04] Chainsaw guy: There you have it, a felled tree. And now look at the greenhouse is in full song.

[00:13:11] George Vettath: Yeah. That's a better example. Absolutely. You gave a better example.

[00:13:14] Andrew Liew Weida: So if using an axe is so much effort and maybe it takes a longer time, let's say it takes, let's say three years to be a skillful X chopper, just to chopper tree whereas a chainsaw maybe takes like maybe 30 minutes or one hour to learn how safe it is, how to ramp it, how to charge the chain. So I'll be able to chop the tree in a shorter time.

[00:13:34] George Vettath: Absolutely. It's just that you still need an experienced person to come and make sure when you're cutting the tree falls in the right way so that it doesn't fall in your head. So say you gotta do it carefully. You gotta build it like how you're doing, except that you do things faster. That's all. So I can put it this way. SDLC in low code, nothing changes. It's just that each stage becomes faster. You do the speaking faster, you do the design faster, you do the development much faster, and we do the testing much faster. That's all it

[00:13:58] Andrew Liew Weida: Can I say that if a junior software engineer were to use a low code platform, he will still be as good as a senior software engineer?

[00:14:06] George Vettath: Yes, I'll just turn that same thing slightly different. Earlier to build a complex app. You need a team that involves a project manager, involves business consultants. You will need a technology architect. You will need a solution architect. You will need a senior developer for the front end, bring a developer for the back end senior developer to write web services and then you'll need a tester. So you're talking about minimum so much. Minimum so much to do it well. Okay. That's why they look for below full stack developers who are supposed to do all this. You never get a good one, very rate to get a good full stack. Whereas with low code, what happens is the entire stack is built automatically. You are only attaching rules, you're only changing the UI. So the team now changes to a very good consultant who will model the system, maybe a front end developer who's going to do some special UI for end users and somebody who writes business rules for custom logic that's required. So you're seeing the team size shrink of a very large team to a [00:15:00] small team to build any complex application.

[00:15:01] Andrew Liew Weida: That really is a game changer. If it is easier to learn and faster to deploy then companies are definitely way more open because now we are living in a world where it seems that skillful, technological talents are in short supply. And so one way is either we go back to the government or ramp up a lot of schools or mobile open online courses, which is MOOCs, and hopefully there's a lot of software engineers or developers. Now with this kind of low code. I can immediately get output with fewer people, and they're easy to learn to use the tools.

[00:15:38] Andrew Liew Weida: Hi everyone, thanks for tuning into this episode. We have come to the end of part 3 with George. In the next episode, we will continue with George on part 4 which George talked about his books and apps. Finally, he will share with us some career tips to build a career with AI.

[00:15:51] Andrew Liew Weida: Hi guys. Thanks for listening to this podcast. If this is the first time you are tuning in. Remember to subscribe to this show. If you have subscribed to this show and love this. Please share it with your friends, family, and acquaintances. See you later and see you soon.

Source: Chainsaw

Source: Using axe to chop the tree