Scaling to Millions & Beyond with Mohammed Ali Chherawalla (Mac)

[00:00:00] Get ready to discover some of the most actionable DevOps techniques and tooling, including performance and reliability for some of the world's smartest engineers. Hey, I'm Joe Colantonio, host of the DevOps Toolchain Podcast and my goal is to help you create DevOps toolchain awesomeness.

[00:00:18] Hey, do you want to learn how to scale to millions and beyond? If so, you're in for a treat because today we have a special episode for you. We have Mac joining us. If you don't know, he's a partner and CTO at Wednesday Solutions, a product engineering firm that's built population scale products, and is now bringing those learnings to help founders in their zero to one journey. They have a lot of great stuff on the website. Really excited to dive into this topic. Mac has a lot experience here. If you want learn how scale, this is the episode for you. You don't want to miss it. Check it out.

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[00:01:43] Joe Colantonio Hey Mac, welcome to the Guild.

[00:01:47] Mohammed Ali Chherawalla (Mac) Hey Joe, thanks for having me over and thank you so much for your kind words, it's an honor to be here.

[00:01:52] Joe Colantonio Absolutely. Thank you so much for joining us. Yeah, I love real world founders that actually have helped a lot of different companies. I know based on your profile, you've helped some of India's top startups to build APIs, just billions of times a day. Before we dive into that, though, could you tell me maybe a little bit more about how did you get into tech? What keeps you excited about today and things like that?

[00:02:15] Mohammed Ali Chherawalla (Mac) Yeah, sure. I did my engineering in computer science. And while I was in engineering itself, I actually started building a lot of real world projects. I was lucky enough to get internships that were also at smaller companies where if either you're an intern or you're a full-time person, everybody is gonna pull their weight, right? So the opportunity to work on some really high impact products, some of them were like, they'd already got Google Awards and I was part of like a 3% team that was sort of building those out. So early on, I got a lot of opportunity in the right places and the right exposure. And I had this love and obsession with building and the dopamine that comes with it. So like out of my own curiosity and my own passion for it, I'd spend nights and days just programming. That passion sort of evolved and it became bit more around being thoughtful around what I'm building rather than just building. So I started thinking a lot about like product loops, why people use products, what action they want to take when they open your product, depending on let's say what time they're opening your product, how they consume it, which then moved on to thinking about distribution, which is sort of now the biggest problem that most of our customers face because we are working with them in the zero to one journey. So yeah, that's sort of been the journey so far for me.

[00:03:43] Joe Colantonio What's the biggest struggle you see from people trying to go from zero to one?

[00:03:47] Mohammed Ali Chherawalla (Mac) I think it's time and resources that's a very big constraint at this point in time, right? So definitely don't have the resources that a series B or C company has at their disposable for let's say marketing spend, ad spend. You have a leaner team, you have a leaner budget and you have lesser number of people thinking about the problem. How then do you optimize and compete versus more established players? Because let's face it in today's world, there is no novel atnew idea that nobody's done before. We love built things. I feel like being able to prioritize effectively is one of the challenges. It's not okay or it's not an amazing place to be in if you've got an amazing product, but we don't have distribution solved for it. I feel distribution is one the biggest pain points for people in the zero-to-one journey.

[00:04:38] Joe Colantonio When you say distributions, what do you see as the biggest lever that people can pull to help with that?

[00:04:43] Mohammed Ali Chherawalla (Mac) I think it depends. In today's age, I think founder persona or let's say socials, etc. really helps being able to be in the right place at the right time really, really matters. And that right time may not always be ideating and thinking about what's best for the product being knee deep in the nitty gritties of each release. I think what people have to definitely do in the one to end journey is figure out systems and ways in which everything can work without them. The people that have a shorter zero-to-one journey already have systems in place and that's why their zero- to-one is shorter.

[00:05:24] Joe Colantonio So I guess the right time is difficult because you probably work with a lot of people that may have a great product, but for some reason doesn't take off, but maybe another company does the same exact thing or some reason they take off. Is there anything involved in that other than luck or is it like, where's the right time? Like, is it just like sometimes that's life, you know?

[00:05:42] Mohammed Ali Chherawalla (Mac) I think active prioritization, so when I see people that are or founders, obviously, it's your baby or very involved and you really care about the product, but I think being able to have a team that is able to take similar decisions that you would take and being able to pass on that ethos is what separates the one that are able to cross the chasm. I think it's active prioritization on going and figuring out more customers, more avenues in which they can acquire that large number of customers. Perhaps it's affiliate programs, perhaps it's different acquisition channels, but I think actively focusing on that and being able to get a product team that's able to do that has been the difference maker.

[00:06:28] Joe Colantonio Nice. You've probably been seeing an uptick in companies that have created maybe software, maybe I'm wrong, using things like cursor or a Bolt AI. A lot of AI kind of like slop now where it looks like maybe they have a good idea, but it wasn't really built to be scalable. Is that an issue you've been noticing? Yeah, okay. You have a product, but that's not, that's like the beginning step, making it scalable, knowing what to do and how to do is probably the biggest obstacle. I could be wrong.

[00:06:55] Mohammed Ali Chherawalla (Mac) No, no, I think I 100% agree with you that there are these tools that are available. And in my opinion, these tools have been available for quite a while. I mean, it may not be as easy as natural language to production code, which it is now. But earlier you had tools like let's say bubble IO, backend list, etc. They were like busy with drag and drop and you can just build stuff out. And everybody thought, oh, this is amazing. I have a product now. And a little time later, they would run into challenges with scaling. I think similar things are happening right now. What we've personally been able to notice is it's a tool like AI is a tool. In the hands of the right person, it's able to get the right result. And in the hands of somebody who use it as a hammer, everything is a need. To your point, we've seen companies come to us that already have a certain product and they acknowledge that okay, this may not be the best in class, the best that's available. And what we've done in those situations is also very interesting. We've been able to use a lot of these tools like IDA chat, even GitHub copilot with the hashtag code base, where it's able to index the entire code base and able to provide insights as to what could be scaling bottlenecks, etc. And then you have an actual engineer or person who understands the tradeoffs. Being taking decision on these things. We're net-net, we're huge AI advocates and we've been able to see a massive uptick in productivity through it. But it's all about using the right tools for the right outcome.

[00:08:37] Joe Colantonio Absolutely. When someone gets to a scaling problem, another thing I might be wrong at, isn't it almost not too late, but it makes it more difficult where if they started from the beginning thinking of scale, that would be a lot easier. Is there like any big mistake to see teams making when trying to plan for scale, maybe from the beginning?

[00:08:52] Mohammed Ali Chherawalla (Mac) I have a slightly contrarian view over here. I think of scale in three year integrals and timelines. If you can today architect for something that will handle whatever perceived scale that you have for the next three years, and you may need to relook at some of these decisions later, I'd rather invest the time and do have actions that can get me these to the total amount of users that I want in these three years. Again, I'm typically talking and my answer will be very different if I was talking about a different set of customers or people that are already in the scaling up phase. Over there, we have a completely different approach. But if you're starting from zero, you're just beginning or building your product from the ground up. I always recommend that just think three years ahead and we'll do things that make sense for the next three years and we make sure that we have contingency for when things really blow up. When you're doing like a probability, the probability of you going viral and getting populations scale tomorrow is highly unlikely. We sort of plan for that practical use case on that practicality.

[00:10:05] Joe Colantonio Interesting. You don't want teams spinning their wheels over optimizing for something that may never happen. Real getting proof of concept and getting users getting real feedback, maybe, I don't know.

[00:10:16] Mohammed Ali Chherawalla (Mac) Yeah, I know exactly that. And it doesn't need to be as scrappy as what your MVP could be, but it doesn t need all of those bells and whistles, your Kubernetes cluster. I can give you an example. It's very interesting. We had a customer a few years ago and they had an advisor on their side who was very certain that they need to use AWS lambdas and they're going to get population scale and this is going to be the only thing that we can do. They wanted to couple it with DynamoDB. If you be aware of DynamoDB as well, and how it's able to handle all the scale, but nobody in the team actually knew Dynamo DB in the deep that they had in their existing team. There's nobody who knew Dynamo DB and lambdas have a lot of issues with the code starts, et cetera. When you're trying to do D2C, you need to make sure that you're either provisioning enough lambdas and there are no issues with code starts. And I was also super excited because I've helped build some part of the serverless framework and the ecosystem over there. But we really needed to step back and talk about not having it because A, your team doesn't know how to use Dynamo and B, you don't need lambdas and the trade-off is not worth it at this point in time. We set up AWS ECS for them and we set that to scale. About two years later, they were serving 300,000 rural women in India loans through WhatsApp. It's still working. This is the max skill that they wanted to achieve and without any of the trade-offs. You do not need to design that Dynamo. I think it would have cost them a lot of time and Dynamo has a steep learning curve. It wouldn't have been justified.

[00:11:58] Joe Colantonio That may be a good reason why someone would work with a company like you, maybe almost like a sounding board, like, hey, we're thinking this and because you have the experience to say, well, I could save you time because you don't have to invest in all this architecture before you actually go live into this.

[00:12:11] Mohammed Ali Chherawalla (Mac) In a certain sense, I think so. I think at the core of our philosophy is that we want to be like advisors and consultants. We may not always do exactly what you want, we will argue with you, we'll debate with you, and we then together figure out what's the right thing to do for the business at this stage and we'll do that.

[00:12:36] Joe Colantonio So that's a good point. When you vibe coding, the AI tries to agree with you, not really play devil's advocate. Having a real human to say, no, that's actually not a great idea. Let's do that. It's more. That makes sense for sure.

[00:12:51] Mohammed Ali Chherawalla (Mac) Yeah, that's been our learning as well.

[00:12:54] Joe Colantonio Awesome. You are passionate about, it sounds like using generative AIs and helping with the enterprises. Where do you see the biggest opportunity or real impact for it today? Maybe beyond hype. I know a lot of people think it's going to replace them. It's the end of the world, universal income. Like you have more experience with this than probably I do. Any thoughts on that?

[00:13:14] Mohammed Ali Chherawalla (Mac) Thank you. I think that's a lovely question. I think of it slightly differently and I'm starting to use it at the peripheries a lot. For example, like a lot of our pull request reviews even before used to be done by CodeRabbit. Now with their LLM integration, those code reviews have become much better. I just keep thinking of it at their peripheries. Now our code reviews are done a lot by Gemini. I feel like the real opportunity is at the peripheries. It's not ready at this point in time to do what a senior software engineer would do, let's say in terms of architecture, do those actual trade-off conversations, et cetera. It's able to do siloed problems. And that's what we've seen it do very well at. We've been able to automate like, I remember times where I've spent like an insane amount of time, like building E2Es, then end-to-end tools like Playwright, which did the recorder really well. And then now we've started using tools like Testim. They've sort of got the vision, GP4 vision integration of sorts. Now it doesn't no longer needs for you to write the data test IDK and just figure out where it needs to click, et cetera. And it's been able to streamline those journeys. We're using tools like Keploy where once you write a few API tests, it's able to extrapolate and figure out the rest same for unit tests, et cetera. At the peripheries is the biggest opportunity. And actually that's where we are seeing of the highest increase and boost in productivity as well. That's my take. In fact, we are piloting another endeavor where we've taken an abstract business problem and we've used something known as prdkit.ai where it asks you a lot of questions. You will need clarity of thought if you want to use these tools for sure. You need to do the thinking. We fleshed out the entire PRD with it. I've supercharged Claude with a lot of context on how I write prds, et cetera. And I trained, so it has all of that context and it starts writing prd is the way I would, right? Again, for a lot back and forth conversation. And then we built out the product with GitHub co-pilot and a few prompts and obviously engineering process. But that entire time that you take weeks earlier was done in a matter of about five or seven hours. I feel like there are opportunities, but they're also in the areas that are not that sexy also. Documentation is completely gone. Ticket creation, like the JIRA MCP does a really good job. I feel that peripheries is where I am more bullish.

[00:15:59] Joe Colantonio All right. You said something could save you five to seven hours. What do you do with those extra time? Do you get rid of the resource you might have used or do you actually invest it somewhere else? Being a business owner, right?

[00:16:10] Mohammed Ali Chherawalla (Mac) I think investing.

[00:16:10] Joe Colantonio Really?

[00:16:10] Mohammed Ali Chherawalla (Mac) Yeah, yeah, yeah. I think, and that's what I'm saying, like, all of us need to invest in distribution. That's the real mode. There's a very interesting quote where it says, first time founders focus on product, second time founders, focus on distribution. I think it could not be truer. At this point in time where we are like exactly, you said everybody's building a product or what they think is a product. Building is not becoming the barrier anymore. But getting people to act because the mindset that people have is still the same. Getting people who actually come and use your product is the real mode. Us being able to spend time in distribution, in creating systems, in creating leverage. That's the real investment that needs to be made. That's what we are seeing across the board. When people are able to finish their programming, they're now asking different questions. They're now ask questions like why are we doing this? What is the benefit? How will the business succeed if I meet this? What can I do so that the business metric is able to move in this direction? What happens after I meet the metric or we meet this metric? That's very interesting because it's a callback to a previous question because now, they understand the entire roadmap and the business trajectory. So now they are taking architectural decisions that can be supported with the growth trajectory of six years later. We've planned for three years. But we are making the foundation to be robust for the next 6 years for example. It becomes very interesting as to what we do with that additional time and you are right, investing it is the only way.

[00:17:50] Joe Colantonio Love it. Love it, great answer. Going the other way, do you see any companies maybe jumping too quickly into AI adoption that causes them issues? I know I have a lot of people telling me, oh, my company gave me a mandate, 50% of your work needs to be using AI, and they're like, they didn't think about the why, they just like, or how, just adopt it.

[00:18:09] Mohammed Ali Chherawalla (Mac) I think so. 100% agree. In fact, like a lot of times I reference the conversation between Lex Friedman and Sundar Pichai, where Lex is asking Sundar, what's the productivity boost that you're seeing with AI? Like, do you worry, like people are worried about their jobs, etc. He says that, like in a nutshell, the lines of code has increased, but lines of code was never an indicator of productivity. Overall, we are seeing a 10% productivity increase. A lot of times when people, and we've had instances also where people have come to us and been like, okay, you know what, I've spent about some time vibe coding this now. It just has one, two issues. Can you help me get through the finish line? It should be possible in a day or two, but that's never really the case. You open, you take a deeper look and it's just a can of worms. We've seen that side of the puzzle as well. But what has been very interesting and I think we spoke about this right in the beginning, the ability to use the right tools to triage these issues and actually make those fix has also reduced, in my opinion. If it's okay, I can give you a small example of something insane.

[00:19:24] Joe Colantonio Yeah, I was going to say, can you expand on that? How was that? Give me an example.

[00:19:29] Mohammed Ali Chherawalla (Mac) Something really insane happened to us. We had a customer that came to us with a very difficult problem. They said, look, I've got multiple mobile applications for different platforms. I've gotten desktop applications for different platform. And I've built all of that. The only problem that I have is in one particular desktop platform. This code base is too archaic. It hasn't. It's been built over the last 13 and a half years. And it has a technology stack that I am finding it very difficult to find good developers for and the ones that I'm finding are not able to do anything because there is no documentation in this. And it was a challenging problem and it had a short time frame as well. The time frame that we had was six weeks. And this product was built over many years, 13 and a half years ago was the time of the first commit. We used IDA chat initially. It wasn't doing this about four or five months ago maybe. We used IDA chat initially, gave some answers. IDA chat indexes the codebase and you can actually chat with the code base now. It gave us some answer, pointed us in the right direction, but there were then some shortcomings. We switched gears. We use GitHub co-pilot. It had just launched the code based feature in review. And we had a six-week timeline. In four weeks, we were able to, so this app, I was using SOAP APIs. It must've been so long since you heard anybody say that, right? This was SOAP API's, which needed to be converted to REST. There was no authentication. They were open APIs. There was a RabbitMQ connection that was created by every platform application. Every client created its own RabbitMQ connection with the server. It was massively, it was not optimized. We needed to use, let's say push notifications. We needed to convert it to RESTful and we needed it to add auth. Essentially we were touching all of the touch points of where it's gonna talk to the outside systems. Very large coverage. We were able to do it in four weeks. I feel like in a pre-Gen AI world, that would have been very challenging to be able to accomplish.

[00:21:59] Joe Colantonio Yeah. I work with a lot of enterprise companies that have a lot of legacy systems and they wouldn't even try to touch it because they'd be afraid to break it. That's a good point. They can help modernize now using these tools and actually would probably save the team because a lot the team has actually aged out and no one knows how to fix it or update it to make it more modern and to grow with the company. That's a great point.

[00:22:21] Mohammed Ali Chherawalla (Mac) Yeah, it was such a big problem because there was no documentation and because the way it was bundled, it six Xcode sort of projects bundled and somehow made to work together. So that build process was also not documented anyway. So it would have actually been so much exploration to try to figure that out. And it still was by was a limited amount because we were able to do contextual searching now. We knew what questions to ask and it knew where to keep pointing us. It was a very interesting journey.

[00:22:54] Joe Colantonio And it probably would have been joyless work if someone tried to do it manually, without the assistant. It's not like it's replacing you, it's helping you and taking care of a lot of these. I'd be worried to death, so it helps you for sure.

[00:23:06] Mohammed Ali Chherawalla (Mac) It definitely. I feel like personally also have been able to see it really help and allow me to do much more with my time.

[00:23:18] Joe Colantonio Absolutely. Yeah, if you're creative, it can help you. If you're not creative, then it's still going to be the same issue. Cause I have a lot of ideas and now I'm able to create all these ideas and mess with it where before, it never got off the ground. It's an enabler as well, right? To do more.

[00:23:32] Mohammed Ali Chherawalla (Mac) Yeah, 100%. I think of it like a kitchen knife. It can be used to create life or take it. The choices in the hands of the person that wields it.

[00:23:46] Joe Colantonio Absolutely. Love that. All right, so changing gears a little bit, I know a lot of people are worried about their jobs or someone's coming into the industry new and they're hearing all about how AI is going to replace them, someone that actually has a company, what do you look for maybe when hiring or mentoring like a future tech leader, what suggestions would you give them or advice or what do you look forward for yourself?

[00:24:05] Mohammed Ali Chherawalla (Mac) Okay, Joe. I'll answer that in two parts. I think the first part is in my opinion, we're going through something similar that went through in the industrial revolution. Like there was a massive change in the way operations were run from everything being manual to then bringing in machines to do this work and then it radically transformed the way we looked at work. I think AI is doing that as well. It's gonna create a lot more opportunities for the ones that are docked. And what we're looking for in the people that we're hiring and the people that we are grooming is if they've adopted to this new wave. And it's very interesting because the number one question that we seek an answer to is what do you do with that extra time? If you're okay, I can give you like a small example of what we do in the hiring process. For me, I think it was very practical. There's no point doing a lot of DSA, etc. I like to talk to people about real challenges that we face in the day-to-day and then we sort of brainstorm and then you build that solution out. And typically because of time constraints earlier, right, people would make a solution that wasn't as sophisticated, for lack of a better word, in the user experience, in the way the different components sort of interact with each other. But now that building is getting, or these independent pieces can be generated faster using some prompts or some AI. It really sort of shows how much I'm thinking about the product. We had somebody who, one of the questions that I ask, I still ask, it's going to probably backfire when I'm hiring. But one of the questions we ask is, okay, let's brainstorm about architecture, etc. of what an e-commerce store would look like, the different components, how you'd handle for scale, et cetera. And the conversation moves towards, okay, let's build something together. And why don't we build the product detail page for a furniture store? In its true form, we've had somebody, a very nice young person who's joined us who said, okay. If I'm going to build a furniture detail store, let me think about what convinces somebody to do add to cart or purchase now when they're on the product detail page. The first thing that he said is, okay, you know what? I need to have reviews of here. I need have ratings over here. I need two have multiple kinds of images. Maybe I need add support for a video that talks about the benefit of this furniture. Maybe I needed to add a component which allows people to take a picture of this and hold their camera and be able to place it somewhere. Around in the room so that they're able to get a feel of what the furniture looks like in their ecosystem. It was an instant hire for me because they were thinking about it from the user's perspective. They were behaving like a product engineer. And when you're surrounded by more of these people, I feel that allows you to start thinking about distribution about getting more users because now you've got people thinking about that product loop that by reality loop over there about the user.

[00:27:24] Joe Colantonio Great, great, love that, love it, love it.

[00:27:26] Mohammed Ali Chherawalla (Mac) That's how hiring has changed for me and that's the kind of people that we're largely looking at now. I feel like brilliance now comes at the intersection of multiple disciplines. Let's say you're an engineer, brilliance really will come at the integration of another discipline, engineering and design, engineering in product, engineering business, business and design, business and product. I feel that's where the magic really happens, being able to do more than one discipline.

[00:27:53] Joe Colantonio Yeah, I forgot what they call that. It's combining your unique skills until like making you what, what makes you great, it almost like building blocks, you have engineering, maybe you have music. And for some reason that combination makes you a good at X, I don't know, whatever it is.

[00:28:10] Mohammed Ali Chherawalla (Mac) Yeah. I think so. I think I adopt that mindset as well.

[00:28:14] Joe Colantonio All right, Mac, for people that are listening, just, we talked a little bit about your company, Wednesday Solutions, but what do you all do if someone's listening like, I'm struggling going from zero to one, I probably could use some help. Maybe a little plug for what you all do that Wednesday's.

[00:28:28] Mohammed Ali Chherawalla (Mac) So at Wednesday, we're a product engineering company. We specialize in applied AI and application development and modernization. We have a launch service that's built specifically for companies that are on the zero to one journey and are looking at getting a lean team that's able to take their product from an MVP and get it to PMF and work with them in that journey. We've designed our service to make sure that there is a high level of trust and credibility before there is a long lock-in. We have an offering called Sprint Zero which comes with a money back guarantee where you get to experience working with us and we'll create the proper plan, technical roadmap, product roadmap, and backlog for your business for the next three to four months. And only when you like that experience of working with us, can you start purchasing Vibe Sprints? Which is our outcome as a service, which means at the beginning of every Vibe Sprint, we're gonna tell you exactly what you're gonna get and only when you achieve that will we bill you. We are questioning and challenging traditional time and material or retainer engagements in that sense.

[00:29:43] Joe Colantonio All right, Mac, you just mentioned something called Vibe Sprint. I've heard of Vibe coding, Vibe testing. This is actually the first time I've heard of Vibe sprinting. Maybe a little context, what does that mean?

[00:29:52] Mohammed Ali Chherawalla (Mac) Sure, sure. In my opinion, Agile is dead, like Agile sprints are dead. It worked at a certain time where you could have like a team leader, scrum master, a project manager, a program manager, product manager, a senior QA person, a QA person, a Senior Engineer, you get the drift, right? It doesn't take 25 people to build a dashboard. I feel a small set of people that are exhibiting the right qualities. The right product qualities are able to pack a massive punch. And that's exactly why we designed Vibe Sprints, which is building a digital product using the right tools, which means your project management is being run using tools like ClickUp. Your product management is done using tools like PRDKit. Your programming is done using tools, like GitHub Copilot. Testing is done with Keploy, with Testim, your code reviews are done with GeminiBot, et cetera, et cetera. But essentially everybody is able to get much more time and actually get more done in one sprint that moves the business metric. And that's what a Vibe Sprint is. It's outcome driven and that outcome is moving a business metric.

[00:31:09] Joe Colantonio Very cool. Okay, Mac, before we go, is there one piece of actionable advice you can give to someone to help them with their scaling efforts and what's the best way to find or contact you?

[00:31:17] Mohammed Ali Chherawalla (Mac) The best way to find or contact me is my LinkedIn or my Twitter. I'll drop those details over and please feel free to reach out, my DMs are open. The best piece of advice that I can try to give people that are listening is that don't be afraid to experiment, right? The more we experiment, the more things we try, we will learn and we'll have insights. And once you have insights, that becomes the first step in the direction towards scaling. Scaling with our insights may not really give the benefits or the results that we're looking for.

[00:31:52] Awesome. And we'll have links to all this awesomeness in the comments down below.

[00:31:57] All right, before we wrap it up, remember, frustrated users quit apps. Don't rely on bad app store reviews. Use SmartBear's Insight Hub to catch, fix, and prevent performance bottlenecks and crashes from affecting your users. Go to SmartBear.com or use the link down below, and try for free for 14 days, no credit card required.

[00:32:17] And for links of everything in value we've covered in this DevOps ToolChain show, head on over to testguild.com/p181. So that's it for this episode of the DevOps ToolChain Show. I'm Joe, my mission is to help you succeed in creating end-to-end full-stack DevOps ToolChain awesomeness. As always, test everything and keep the good. Cheers.

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[00:33:23] Oh, the Test Guild Automation Testing podcast. With lutes and lyres, the bards began their song. A tune of knowledge, a melody of code. Through the air it spread, like wildfire through the land. Guiding testers, showing them the secrets to behold.