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April 26, 2022

E008 Prabhjot Singh Lamba: Automation Thought Leader

Automation Thinking Boosts Human Productivity In Business. & Life.

Prabhjot Singh Lamba is an an Automation Thought Leader and the brain behind Craftar.

Prabhjot believes, in this decade, coding will be automated and more people will be able to solve their own problems and the problems of their communities using technology and data.

His Twitter:  @PrabhjotSL


Abdulaziz M Alhamdan 0:07
Once upon a time, there were millions of businesses struggling. Every day they wasted time, effort and money on repetitive tasks that added no value. One day, the better automation podcast by process you came to help them find the way. Because of this, these businesses save time, reduce costs, innovate, and make better decisions because of that. These businesses grow, scale, and use human creativity to change this world. Hello, my name is Aziz, and I'm your host that better automation podcast by process CO, where I interview the world's top experts and share their very best ideas on how to improve automation in your business, processes. And life. My guest today is Prabhjot Singh Lamba. Prabhjot is an automation thought leader and the brain behind crafter, crafter, lets people build API's with no code at lightning speed. And he believes that in this decade, coding will be automated, and more people will be able to solve their own problems and the problems of their communities using technology and data. Prabhjot, how are you today?

Prabhjot Singh Lamba 1:38
Hey, as he's Thank you for having me here. And like I'm doing good. Yeah, looking forward to this. And yeah, hopefully uncover some cool stuff about automation

Abdulaziz M Alhamdan 1:50
100% that I know, as I presented you, as an automation thought leader, you have a lot of thoughts about how humans are automation machines, that programming is basically a form of automation. And the way you perceive workflows and processes in a way that helps you think in an automation optimized manner. Can you share about that?

Prabhjot Singh Lamba 2:17
I think the first thing which I came across, like when I was studying in college, was like, what a robot is in AI. And there were three components to it. So the first component was the sensing. The second was the compute. And the third was the actuation. So most robots pretty much have these three systems. And if you look at humans, we also have these three systems, we have sense organs in which through which we collect the signals and information about the world that we live in. And then we have a brain and the whole central nervous system, peripheral nervous system, which transmits that data to the brain. And then the brain calculates that information recognizes patterns. And over time, as it gets feedback from the environment, it learns to make better decisions. And then for brain to actually go and change something in the environment. It will use hands that we have been given, like movement and walking. So that then gives us feedback about the information that we have connected, and how, like, if a trigger comes in or an environment, some event happens, our brain learns to decide, okay, what is the best path to take, suppose to optimize for rewards and failures. So that's pretty much how our human brains work. And that's like, how automation should work. So this is why I think like humans are automation machines. So that, I think is where it's coming from.

Abdulaziz M Alhamdan 3:50
Thank you. That's absolutely fascinating. And to add even more, because you're interested in automation, you focus on it. It's a big part of the work you do. Why did you find it interesting and important for you to focus on automation? And how did it add value to your work and to your business?

Prabhjot Singh Lamba 4:14
So I think one of the biggest aspects of automation came to me when I started learning about programming. And when I started coding, when I was seven, I didn't think about automation, then it was just fun trying to make things animate on the screen or trying to move some item or when I press a button on my keyboard and then something shows up on the screen and then you're able to change that with rules. I played with like basic languages with everybody does logos basic. And then I learned C++ and then there was Dreamweaver in front pages and we made websites. So it like a lot of the first initial like till college most of it was just like exploration and being fascinated by computers in general. But then After college, I did my engineering in electronics and came across this subject of control systems, which was, I think it's pretty influential in how I think about processes and systems. You have block diagrams, and then those block diagrams have feedback loops. And all that is sort of like very crucial to automation as well. And throughout the whole journey of like, last 12 years of like professional coding, all the patterns have pointed to one direction, which is data. And like, it's all about the data in the end. And if you have the right data, you can then do stuff with it. So I think with crafter, what we are trying to do is allow everybody the access to the data that already exists, there's so much data out there. And it's hard to kind of take that data and extract insights from it, or use that to take decisions for phenomenon that are beyond just like our individual selves. So an example would be if you look at the data in on Twitter, right? So if you're part of an industry, let's say, no code, or communities are something you can look at all the data that people are talking about in communities use that information in smart ways through building flows, that we say, like connect smart machines together to extract insights, like, Okay, who is the influencer in this community, right of marketing. So finding those insights, requires a lot of coding to actually clean the data, extract and store the data in a database, and then run some algorithms on it and then visualize it. And then kind of do the data analysis, data exploration and data inference. So those layers, and then you end up you're saying, Okay, this is the person that I think I need to talk to, to get like the maximum value out of my conversation. So that all takes teams of people to do right now, and a lot of expertise. But I think with no code and abstraction, we are getting to a place where if you have the data, you can pretty much get to those insights and like five hours, one hours, maybe even 10 minutes, because everything else has been automated for you.

Abdulaziz M Alhamdan 7:21
Thank you. And that's a very important issue. You spoke about cleaning out the data thinking about it? Well, when it comes to business people, how will they decide which data is the most valuable? Because like you said, The world is full of so many things that could be measured so much data that is available, how to prioritize, or at least know which data is worth focusing on. And it can be like a key indicator, and which should be maybe secondary or is not important at all?

Prabhjot Singh Lamba 7:56
Yeah, that's a big? That's a good question. Because it's a very hard thing to do. Because not all data makes sense. And it mostly depends on your understanding of the domain that you're in, and the kinds of questions you ask. So if you have, like, if you're working in an industry of let's say, marketing automation, and you want to add in that, specifically, let's say lead generation as an example. So you know, the scope of the problem that you're solving, your goal is to fill the funnel with the right candidates, to take them to the next stage. Right now, having an understanding of the goal very clearly is the first thing that is where expertise comes in. And the second thing is, what's your current process for doing that. And then drawing a diagram of like, this is what we do manually, we collect data in Google Sheets manually. And then we take that data, and then we run it through some Google Excel formulas. And then every time when new data comes in, we have to remove all of that and create a new one, or just like mapping out the process end to end, and then figure out figuring out the rate determining step, right? Like what, which part of your process is the one that is taking the most amount of time, and then trying to automate that part instead of like the whole pipeline at once. And then once you fix that, again, like the rate determining step will shift to something else. And then you fix that. And then over time, you will build like this whole pipeline, which will be as automated as possible. And that's like the approach people should take.

Abdulaziz M Alhamdan 9:31
This is really, really great. And I know you have a lot of experience with larger projects and automating them. I remember it was something related to India and the money and all that that people were doing it in Excel before and you did something to automate it and to make it a lot more effective and under control. Can you share about that project, the benefits, the usefulness and Everything that happened in that situation,

Prabhjot Singh Lamba 10:03
right. So it was a project for the Income Tax department. And the idea was that there's a lot of shell companies which get formed. So people create a company, and then they create a lot of other companies in the name of their family members and people that they know of. And then they transfer funds to those shell companies, and then make it harder for their money to get tracked. And in a population of like a billion people, where the processes are not that automated, it can be hard for people analyzing that data to get to like the seventh company where you actually take out the money into your own account. So it was a like, it's a very data based problem, which is why so many people just get away with it, right of like tax fraud, and just shelling money out of the company. So we basically build like a knowledge graph of all the transactions that happened between two entities. And because of that knowledge graph, finding out the fact where the fraud was happening was almost instant, you could just see the fraud happening on your screen. And you could run algorithms to determine like, which of the people have committed fraud, and all you had to do was like, upload all the returns of everyone. And then you get like a list of all the people who have committed those fraud. So it had a huge impact and like, finding who the people were, and which the companies were, who were doing this, and then creating evidence for that as well, like it generated a report for like, this is what you did in this year with this amount of money. So we have proof. And now we can challenge you.

Abdulaziz M Alhamdan 11:47
Thank you that's very useful, and very important work that you are doing. I don't know whether you use no code tools, or you did the programming yourself for this project. But in general, when it comes to automation, all the competitors in the market, what do you feel might be missing from what they offer? What frustrations could people encounter when using such tools? I know you're focusing with crafter on API's, and, you know, process you're here as well as taking things to the next level compared to competitors. But what is the current frustration? And what do you believe will be the future of automation? What new technologies do you see up and coming that will change things or will make things easier and better?

Prabhjot Singh Lamba 12:38
So the first question to us is like what's happening in the like ecosystem right now, I think there's a lot of focus on building generic automations, like copy data from x service to buy, like from Google Drive to notion or like copy data of your CMS and then use that in some other place, or add data to a CMS. So it's mostly all crud based automation that is very popular, because that's the first thing we need most of the time. But the biggest thing, where I think a lot of companies will not like put up not companies, but the products would fail is like going deeper into the automation. So which is where I think like data cleaning is hard to do in all these systems. like running a for loop is almost impossible in most of these tools. And most data is list and then you have to clean each item in the list and run validation checks. And that's an indication of like the problem with their fundamental design. It's like the blocks, like it's all about blocks. And everybody just talks about blocks, and they think about workflow automation. But then how do you design those blocks. And what they can do is where like, I think the innovation is with craft as well, where we think like be our Lego blocks are better than theirs because of the amount of flexibility it gives. So to expand on that, I think if you think about no code automation, there are two things. One is abstraction and the other is flexibility. So abstraction basically allows you to make tasks simpler by creating higher order functions for it. So like, I could make a single block, which lets you get all your YouTube video information, right? Or I could make a lower level block, which could say, okay, crawl any website, give me the URL, give me the selectors, and then get me the information from it. So you could connect those four blocks and then build that higher level block yourself. Right. So having the capability to run the lower level tasks or play at the top level blocks is what allows for flexibility So a person who doesn't know coding or computational thinking or how to think about rules, if else how browsers work. For them higher order blocks work really well, which is why Zapier is very popular in that category. But when you have to go deeper, and when those higher level blocks don't do exactly what you want them to do, and then you want to change something, that's when you get stuck. And you need to go deeper and allow for like, more customization. So having that is where I think like flexibility in tools comes in. And that I think the next step for automation,

Abdulaziz M Alhamdan 15:33
this is absolutely great and fascinating. And please tell me, I know you're working on a lot of projects, you have focused a lot on automation. Do you feel that other than the bubble? Other than the automation experts like area and niche that you're part of where everybody's trying to be efficient? And automate? Do you feel a lot of business people, entrepreneurs, or busy people in general, take time to automate the repetitive task? Do they understand it? And if not, why not? And if so, what do you think is like the big problem that causes people to begin looking into automation? Who are not coders or people who have grown up understanding that this is an important thing?

Prabhjot Singh Lamba 16:24
I think the basic answer is like one, like most people are now getting, like because of no code tools like bubble, and air table, people are trying to understand, okay, so how do you even organize data and create relationships between data, which is like the fundamental concept you need, like data, like representing intern related data in your head is not that easy as it sounds. For people who know they know, for people who don't know, it's like a big first step to cross. And once you cross that step, then you come to the next step, which is like, okay, so I have this data, which is like very nicely connected related data, which I've built. But there's also data in some other surveys and some other service, and I just want access to that. So then you start thinking in API's, and okay, so I have to connect these multiple data sources into one system. And that is the system that I'm trying to build. And once you get past that barrier, then it comes to like build thinking and systems, right? So I might be building let's say, Flipkart or Amazon, I have to like if you divided into systems, you think of, okay, I need a checkout system, I need a orders tracking system, I need an inventory system. And I need like a browsing system for people. So now you have these four systems, they have their own data sets, they have their own logic and flows. But then they also talk to each other, like when you click on Add to Cart button, it goes to the orders page. And on the inventories, it shows you like this is already in your cart, right, so two systems talking to each other. So that is where I think the problem is, it's like people are learning, it will take some time to for most people to get there. Some people are already there. And the coders have been there for a long time. So the so you can start with like coders and making their life easy and go down the pyramid and like where there are a lot of people or you can start at the pyramid and then go towards a lot of experts. So it depends on like, like, you should think about those things when you're designing your learning content, your initial distribution strategies, and who you're messaging as well. So yeah, just knowing your customer, and then thinking about where they stand in the pyramid kind of helps you stay distinguished from everybody else.

Abdulaziz M Alhamdan 18:46
Thank you. Oh, really, this is I love automation, I believe a lot of human time and human creativity is wasted on mundane, mediocre and repetitive tasks, and that we should evolve beyond that. But at the same time, I want your perspective where some people will think if everything is automated, a lot of people will lose their jobs and they will not be able to do the work they're used to doing while others say, of course, that's great because it liberates the human mind to do greater things that cannot be automated. What's your perspective on this? Did you see any stories or experiences that confirm one or other view about this? And what is like your biggest reason or argument to encourage people to automate more?

Prabhjot Singh Lamba 19:40
They take the major question I think like there's no like, you have different examples for different things. And like if I consider so first I just think of like tell you like how I think about this. So if you think about the Industrial Revolution, and like how assembly line and the production was ailed at that point in manufacturing and all the other aspects of building a lot of products for people to consume, like that threat, the same questions were asked back then, like, what will happen to factory workers? And like what, like if everything is automated, what will we do? And the major counter argument there was, there are things that us as humans are capable of, like the human brain is a very rare thing, right on the planet, and there are better things that it can do. And it when you automate the mundane tasks, you're absolutely right. It frees up people to be more creative and find, think about other aspects as well. And that's where thinking in factories helps. But factories, they are all about raw materials of the world. Today, I think like, well, when you think of workflow automation, I think of it as information processing factories, where the input is not like cotton, or nitrogen, hydrogen, but it's like ones and zeros or data of certain type. And then the output is a data of another type. And you're building like these assembly line kind of systems that convert one data to another form. And that is where like a lot of boring tasks like cleaning data can be covered, you can merge data, which is very complicated to merge otherwise. And that's where a lot of the boring tasks will be done. And people can focus on building applications, solving problems of their community, and actually spending more time on talking to the customers then handling of data, which you can pretty much automate so allows for more third, solving real problems basically like which helped people. So that's one point aspect of it. The other aspect is like, there is AI coming up, you can see like if you saw Dali to what it did with like art. So again, like AI is looking at creative aspects of automation that can be automated, like by would, you need to spend 10 hours on drawing, when you can just type give me an image of a man and a dog. And it shows you like 10 different reference images already drawn, which would be better than what most people are capable of. So I don't know how that will pan out. It's 10 years into the future. But I still think like automation, right now has a role to play with this data, like terabytes of data, which is just kept somewhere, and nobody has the time to go through it. Because they're stuck in basic problems. So if we automate that, we can extract a lot of insights and help a lot of people. And the third point of like, why I think everybody should do automation. And how it helps an individual and small businesses is because automation has always been expensive. It is not that easy to get into even Zapier for a lot of people, like the cost start to scale as your use case start to scale like rapidly. So making it affordable, allows for everybody to get the benefits of the automation, which helps everyone become a maker and not just a consumer. And when you can automate, you can build systems on top of each other. Most people get stuck in a pipeline all their life, like get up, do this and then done. But with this, you could get up do this one's automated and then get up do something else and then automated. And now you have like these stacks of things that you're able to do, which lets you come and get compounding returns.

Abdulaziz M Alhamdan 23:35
I agree compounding returns is what we're all about here at better automation and that process you and just one final question. Imagine there is a business person right now, who wants to scale their business, for example, automate as much as possible so that they can free up people to work on the task that will help the company that is scaling, or anybody else? What is your recommendation to approach any new automation project? What could be the ideal steps? What should the people be aware from aware of which mistakes should they avoid and steer away from? Like, if you could design an ideal approach to someone new automation to undertake their first automation project for their business or for somebody else? What would you recommend?

Prabhjot Singh Lamba 24:31
Identify first step is identify what data you have. Second step is what is your process? Like what are you doing right now? Like what is your business made up of core business? And then what are the operations made up of write them down, map them down? Whether it's like, like you think of it like a recipe. So how do you make a sandwich is a recipe. You write those steps down? And then once you have once you write it down, you'll realize how many assumptions you're making while you're writing that down. And this is like a very classic algorithm example in computer science courses where like, teacher asked you to like, can you write the algorithm to make a sandwich and people miss out steps like, get the bread and then pick one slice of it and then take out the spoon. So break it down as much as possible based on your own understanding, then identify the data, like the input and output of each step. So who is responsible? And what is the data that goes into this system? And then comes out of the system? And then within the system, is there some way to automate it? So if you follow these steps, let's say you have a use case of, I have these PDF documents where we write our RFPs for clients, and then I want to tag them, because we right now I have like 10, people who are manually looking through those dogs, and then identifying keywords and manually tagging them. Right. So now the input is the dog, and the output is the tags. So what is the system that is available that can do this for you? And how well does it function? Right? So that research can tell you, Okay, so basically, I can probably extract those tags, and they are 80% accurate. But then instead of this 10 People, I can get it done with two people who can just look at those tags, and then remove the tags, which don't seem good. So you have reduced the time of doing the task by 10x or something so and then slowly do this for a lot of your operations and your other businesses.

Abdulaziz M Alhamdan 26:34
This is absolutely fascinating. And I recommend what you said 100%. And if people want to know more about you to use your services, or to check out crafter, what are the best links for them to go and I'll make sure to include them in the description.

Prabhjot Singh Lamba 26:54
So you can find me on Twitter, my Twitter handle is structured as hell. And for the product that I'm building, which is an automation platform, which lets you build automations with Lego blocks. It's called crafted CRF

Abdulaziz M Alhamdan 27:11
Thank you very much Prabhjot. And I cannot end this without, you know, letting the listeners know that they can get access to a free account at process yo dot app where they can get one full hour of automation execution, which is equivalent to 100 Human hours. And for those who don't know yet process eo is the modern, low code, no code platform for advanced automation and creating an enterprise grade back end for your software. And you can request access to a free account that you can use for a long time and benefit and simplify your life and free up your time. And any time you're ready to upgrade. Also, there is a wonderful 50% discount code which is better 50 off one word, all capital letters. The link is in the description and Prabhjot this was my pleasure, my honor, and my privilege to spend time with you and thank you for all the insights

Prabhjot Singh Lamba 28:18
thank you so much for hosting and for inviting me and it's an honor to be here. And yeah, it was a fun talking to you about automation