AIP Podcast EP 79 - Accelerating MVP Development with AI-Augmented Engineering by Codalio

This episode’s guest, Ehsan Mirdamadi, Co-Founder and CEO of Codalio, joins host Anne to explore the realities behind the rise of agentic AI and “vibe coding.” Ehsan shares his journey from early cloud computing pioneer to startup advisor, and how those experiences led him to build Codalio—an AI-augmented platform designed to help founders move from idea to enterprise-ready product faster and more efficiently.

He dives into the challenges non-engineers face when building software without strong architectural foundations, and why systems thinking, product clarity, and structured development still matter in an AI-driven world. Ehsan also discusses how Codalio helps startups reduce MVP development costs, accelerate time-to-market, and shift focus toward commercialization and customer validation. Tune in to learn how Codalio is bridging the gap between innovation and execution, empowering startups to build smarter, scale faster, and succeed in today’s rapidly evolving AI landscape.

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Website: https://www.codalio.com/
LinkedIn: https://www.linkedin.com/company/codalio/

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The AIP Podcast is hosted by Anne Cheng, on behalf of the AI Partnerships, a Railtown company

Transcript

SPEAKER_00 0:00

Developments in the age of agentic AI have given rise to a plethora of vibe coding solutions and a multitude of applications and websites being generated and launched ever so quickly. But with the rise of vibe coding comes its inherent downside. Non-engineers attempting to engineer without an understanding of engineering principles, nor the relevant planning and architectural solutioning. Good morning, good afternoon, and good evening to all our listeners from wherever you are tuning in. Once again, I am Anne Cheng, and welcome to the AIP podcast on behalf of the AI Partnerships Corps. I read not too long ago that AI isn't building better code, but actually melting the layers and layers of architecture that has been built up through proper computer science. But it's no wonder that while enterprises are embracing AI-ready transformation, digital engineering teams are barely picking up vibe coding in all its supposed glory. Well, my guest today, Esan Midamadi, has advised hundreds of startups in delivering their minimum viable products or MVP to enterprise-grade solutions. He's now translated this capability to Codelio, an enterprise ready solution. Let's dive right in.

SPEAKER_01 1:34

Thank you so much for having me.

SPEAKER_00 1:36

Airsan, tell us your backstory. How did you go from academia to startups to AI product extraordinaire?

SPEAKER_01 1:44

Of course. Well, I studied computer science back in 99 at York University in Toronto. And same year I started my very first company, which was cloud computing, before even the term cloud computing existed. And I got lucky being able to just bootstrap the company and grow it to about 100,000 clients in the span of about 14 years. We were amongst the very few Canadian cloud computing providers, and so we had the opportunity to actually go after a lot of the government contracts, a lot of opportunities that required the sovereign host of applications and infrastructure. And I eventually, again, fortunate enough that I was able to sell the company, exit. And you know, one of the things that really bothered me, or maybe say just, you know, kept me occupied mentally was that how come on earth we started a lot of the great innovation in Canada, but we are not able to make them globally a scalable uh type of platforms or uh businesses. And so to find that answer, I moved to California for about a couple of years, wanted to experience the whole startup ecosystem and the mindset firsthand. And uh I ended up um spending some time with some researchers at Stanford University, and I helped them out and led the whole commercialization activities for DNA sequencing technology. Again, it was a successful journey and ride. And um after that, learning uh if you know many great things from that ecosystem, I came back to Canada and started uh coaching, advising, investing in you know many companies, especially with the deep tech or strong uh technology at core environments. And so through that experience and engaging myself with a lot of the interesting startup hotspots in in Southern Ontario and uh the incubators connected to the universities, uh specifically University of Waterloo, Toronto, Ryerson, um, and uh York and McMaster University, I was able to kind of get a better sense firsthand of how other entrepreneurs, or let's call them new entrepreneurs, um, were thinking about building things, doing things, scaling companies, and really bringing the deep tech mindset or engineering mindset into the market through some obviously support that they were getting from the ecosystem. Uh, eventually knowing what the where the gaps were, I started putting together a CTO, fraction CTO service company that was helping and supporting a lot of these LESH companies throughout their journey, building products, getting into the market. Um, and then also created this early SH VC fund out of Waterloo that was supporting those companies going through that experience, that exercise. And so the main narrative in all of this, as I learned after better, was that uh we in Canada are investing about $52 billion in RD, but only 1% of all of that research and innovation coming out of it are were being commercialized. So I wanted to do something about it. And uh, you know, having the engineering background myself, knowing what sort of struggles and challenges challenges I had to go through, um, you know, really thought about you know doing something about it, and then uh ended up creating Codalio that really is positioned to help the engineer, the entrepreneurs to get to the market a lot faster by building products more efficiently.

SPEAKER_00 5:34

It's amazing. You know, startups unfortunately have had their odds stacked against them, particularly in getting into enterprise customers and building the products to be adopted by much larger companies. How does Codalio help to bridge this gap?

SPEAKER_01 5:52

Of course. Well, throughout my experience, as I described, uh dealing, engaging, interacting with a lot of um, you know, strong companies in our ecosystem, what I realized was that good chunk of the earliest edge investment that they receive goes into the tech development, um, you know, uh specifically MVP uh build. And so in that exercise, in that process, um, you're dealing with you know challenges of, you know, uh on many levels software development, figuring out what exactly to build and how to align with the problems and the challenges they were seeing in the market for the target audience that we're going after. And so um, even though many of those companies were very successful doing all of these things, at the end of the day, they were running out of capital so quickly before they could essentially start investing in market discovery and adoption and you know, essentially supporting and facilitating the early adoption. And so um, again, looking at the nuances, looking at the uh situations that I had to deal with, uh, the biggest challenge for them was obviously not knowing how the software was built properly. You know, they teach you at school how to build, how to write good code, how to essentially think about the architectural considerations of a software. But they don't, what they don't teach you is that how to really build applications, which requires a lot of soft skills, a lot of you know understanding of how you essentially define a roadmap, define milestones, objectives, priorities for your software developers, for your engineers, but also how you bring them together and how you make sure you have a sound product MVP out the door more efficiently, more effectively. So what Codalio does is that not only it facilitates um the whole elicitation of the ideas and the requirements from the minds of the founders, but also allows to go through a, let's say, AI-augmented process that allows them to move things a lot faster, more efficiently, and more quickly in the age of AI. And so when you are reducing the costs of the building MVP by good 90%, that hopefully gives you enough breath, enough you know, resources to be able to really just um compensate for the challenges that I that I just mentioned, which basically means that you can maybe double down on commercializing and marketing the product out into the market.

SPEAKER_00 8:19

That's amazing. You know, I'm gonna skip ahead here. You know, I've heard Jensen Huang of NVIDIA, he famously mentioned that tomorrow's developers will not write a single line of code. What are your views on the need for systems thinking and actual computer engineering and writing code?

SPEAKER_01 8:39

Of course. So the majority of the tools that you see out there into the market today are designed for the software developers. And in my view, they are most effective for the more senior software developers because your code is as good as your prompt. And if you do not have some level of seniority and expertise that helps you to build better prompts, good prompts that aligns with your business logic, aligns with the objective of the business, you're obviously not going to be able to get the outcome, the code that you will require, um, you know, obviously for your for your play. And so, yes, AI is gonna help you to just avoid writing the specifics of the code, but um in my view, and I guess from the uh even the industry perspective today, um it's just not there yet. You still need a layer that extracts the requirements, the business logic, the goals and the objectives of the target audience more efficiently and more effectively, because AI cannot be reading mined. And at the end of the day, if you are innovating, if you're building an MVP for something new, you're essentially inventing something that has never existed before. So AI wouldn't be able on its own to really bring about that sort of a comprehensiveness as you're building architecting and then writing your code and putting the software out there.

SPEAKER_00 10:10

That's definitely true. Um, but do you think, just one for the road, do you think that the reason why so many startups fail is really because of the inability to launch their products effectively? Because a lot of people say that startups tend to fail or failure to launch is really because they've not really tested their hypothesis sufficiently with the right paying customers. Where do you see that balance between the product side and the commercialization side of things?

SPEAKER_01 10:44

Well, um, we all know about the whole notion of the product development. And if you don't do the proper product development in your um early days, which means if you're not thinking properly about whom you're targeting, why you're targeting, what sort of a pain points you're addressing, um, you're gonna end up in a situation that you're building something that is not going to be used by anybody. And in this time and day, as things are moving a lot faster, if you're not quick enough to be able to really bring some of those ideas, that product thinking into the market, you may end up in a situation that uh by the time you get to the market, the needs and the mindset of the market has changed. So, in my view, um, yes, have the product development thinking early on, make sure that you do understand what you're building, whom you're building it for, and what sort of a value propositions you're uh you're doubling down on. And make sure that you use uh these new AI tools, the new wave of AI tools, effectively, um to your best interest to move things a lot faster and to really um uh try to build something very quickly, put it in the hands of people and validate your hypothesis as soon as possible and go back and reiterate uh again faster.

SPEAKER_00 12:04

That's brilliant. Well, Esan, it's been absolutely delightful having you on our show today. And for our audience, thank you for joining us. And once again, don't forget to like, share, and follow our podcast. You know how much that means to us. Once again, my guest has been Esan Mirdamari of Kodalio, and I am An Cheng on behalf of the AI Partnerships core signing off.