I recently debated a point from a post by Muhammad Usman, where he argued that MVPs don’t fail due to small budgets — they fail due to waste. I completely agree with him.
However, I disagreed with his example: Amazon.
Having spent two years at Amazon as a Software Development Manager, I saw firsthand that despite Amazon's core value of Frugality, many teams operate inefficiently and wastefully. This was true in my group and in my interactions with other teams — but that’s a discussion for another time.
To Muhammad’s credit, he welcomed my critique, which I deeply respect. We had a great exchange in the comments, and he was curious to hear more about Amazon’s inefficiencies. I explained that it was too big a topic for a comment thread and would be better discussed in person — an idea he agreed with. Then, he asked a great question:
"If you had to pick one takeaway from your time there that startups should either embrace or avoid, what would it be?"
I'm making one assumption with this article, that the goal is to build a sustainable successful profitable technology business.
I've worked with companies of all sizes, from tech giants like Amazon and Microsoft (as a contractor) to enterprise firms like Electronic Arts and CompuServe. I've also collaborated with small teams and multiple startups. Along the way, I’ve had to work with technology that was decades old — often leading to massive technical debt that, in some cases, contributed to a company’s bankruptcy or insolvency. A few startups even brought me in specifically to untangle the mess left by their first developers.
Startups don’t always fail immediately. Sometimes, an early technology misstep sets them on a slow path to collapse. They may survive multiple rounds of funding, even turn a profit for a while, but eventually, poor technical decisions turn into a money pit. What seemed like a minor choice at the beginning can later erode the entire foundation.
The first developer always plays a critical role. It's rarely intentional, and I wouldn't call it incompetence — but key decisions made early on can lead to enormous financial waste. Not just in infrastructure costs, but in time (which is money) and salaries.
I'll share some examples, then share what I believe is the core issue.
Cybux - which had the potential to be a strong competitor to PayPal in the Canadian market, ultimately failed due to a critical early technology decision. Around 2001, the first development team chose Java as their primary language. While Java thrived in enterprise environments, it was a poor fit for web applications at the time — complex frameworks, slow performance, expensive hardware requirements, and Sun’s waning support made it an inefficient choice for front-end development. In contrast, PHP, ASP, and Perl provided faster and more effective development cycles.
After spending over $200,000 on a three-person development team, the founder was left with an incomplete product and a bitter fallout. The developers took the source code with them. I was brought in to rebuild what they had spent 18 months developing — and I did it in just three months using ASP.NET. Ironically, I was still learning the framework at the time, but it was the right choice for the job.
Envoy Trading – A currency trading platform launched around 2003. The original development team chose ASP, which had been a solid choice a few years earlier for simple websites but was ill-suited for high-frequency trading. In the FX markets, pips change in milliseconds, and the web UI needed to be both highly responsive and secure — especially given that trade requirements ranged from $100,000 to $1,000,000. After burning through a small fortune, the initial development team was pushed out.
I stepped in and quickly recognized that ASP.NET was the better choice. Ruby on Rails had just emerged, but I wasn’t willing to gamble the project on unproven technology. Instead, I leveraged my expertise in securing ASP.NET while ensuring the platform met the strict performance requirements. In just two months, I replicated the previous team’s work, which had taken them far longer. With additional funding, we spent another ten months refining and completing the platform.
Beta testing was successful, but in 2006 — just before the market crash — the banking partner pulled out. Had the platform been completed a year or two earlier, it might have succeeded.
BuildDirect was founded in 1999, and by the time I joined in the spring of 2016, the company had received significant investment but had yet to turn a profit. The original development team consisted of two smart, fresh-out-of-school developers. However, their lack of experience led to critical architectural mistakes — issues that went unnoticed for years.
In 2015, the company made a drastic decision to replace ASP.NET with React, believing it to be the future. This decision was driven by young, talented, but inexperienced developers, along with senior engineers who backed the change.
While working there, I quickly realized that ASP.NET itself wasn’t the problem — it had simply been implemented poorly. The system had been hammering SQL servers for years, inflating costs and slowing down development. The real architectural mistakes had been made in the company’s early years, but instead of addressing them, they opted for a full-stack rewrite.
BuildDirect was positioned as the Amazon of building products, but by the time I joined, the renovation boom was already slowing. Too much time and money had been wasted on software development missteps. I left shortly after discovering that a business decision to expand the product catalog had inadvertently buried high-demand products in search results. Soon after, one of the founders left, and within a year, the company filed for bankruptcy. While BuildDirect still exists today, it remains unprofitable.
Amazon Freight — a startup within Amazon — was where I worked. The team opted for the latest and greatest technology: React, DynamoDB, and other tools designed for Amazon-scale operations. The problem? They didn’t need Amazon-scale technology.
Even at peak success, they would only be booking around 5,000 full trailer loads per week for third parties — a fraction of the traffic that Amazon Retail handles. Yet, they built an over-engineered system that required a team of seven developers to manage a website with just five dynamic customer-facing pages and static pages that required developer involvement just to update.
The reality? Customers didn’t need a high-tech platform — they just wanted a simple email system. As far as I know, Amazon Freight is still active, but if it had been built outside of Amazon, it likely would have failed.
I need to keep the name confidential, but I wanted to share why I believe a particular AI startup is unlikely to succeed.
The founder has been bootstrapping the company for about 18 months. He has an IT background and can write Python but has never worked as a software developer building products. From the start, he insisted on building entirely in the cloud, despite never having enough cash to sustain it.
His approach leans more toward "measure once, cut twice" rather than the tried-and-true "measure twice, cut once." As a result, he has burned through tens of thousands of dollars in free cloud credits from Amazon, Google, and Microsoft — yet still struggles to deliver a functional MVP.
Without a more disciplined approach to architecture and cost management, I don’t see how this startup will make it.
Time and again, I’ve seen startups set themselves on a path to failure — not because of bad ideas, but because of the wrong technical hires making the wrong early decisions. These missteps compound over time, burning through cash, slowing development, and ultimately crippling the business.
1. Overengineering and Misguided Tech Stacks
Startups often fall into the trap of using overly complex or mismatched technologies for their actual needs.
- Cybux failed because its first developers chose Java in 2001, when it was too complex and inefficient for web applications.
- Envoy Trading relied on outdated ASP for a high-speed trading platform, which couldn't meet performance demands.
- Amazon Freight overbuilt their system using Amazon-scale tech for a niche service that customers only wanted simple email workflows for.
In each case, a simpler, more pragmatic technology choice would have saved time, money, and effort.
2. Rewrites That Solve the Wrong Problem
When technical debt piles up, inexperienced teams often rewrite instead of refactor.
- BuildDirect blamed ASP.NET for performance issues and spent years migrating to React — when the real issue was a poorly designed 3-tier architecture that had been hammering servers for years.
- Cybux’s original developers walked away with the source code after burning over tens of thousands of dollars, yet I rebuilt their work in three months using ASP.NET — proving the tech choice wasn’t the issue, the implementation was.
Instead of fixing core architectural mistakes, companies chase the latest "hot" technology, wasting time and money without addressing the root problem.
3. Founders Without a Product-Building Background
Startups led by non-developers or inexperienced engineers tend to mismanage technical execution.
- The AI startup I know has a founder with an IT background but no real software development experience. He chose cloud-first development without a clear cost strategy, burning through tens of thousands of dollars in free credits — yet still struggles to build an MVP.
- Startups frequently fail to grasp that engineering at scale is different from engineering for startups. Amazon-scale solutions for a 5-page website (as seen in Amazon Freight) is overkill and drains resources.
4. The Cost of Early Bad Hires
The first technical hire in a startup can make or break it.
- The first two developers at BuildDirect were fresh out of school — smart, but inexperienced. Their poor architectural decisions went unnoticed for years, costing the company millions and leading to bankruptcy.
- Startups often hire based on credentials or trends, rather than a pragmatic, product-focused mindset.
- The best early engineers aren't just coders — they think about cost, scalability, and business goals from day one.
The Takeaway: Startups Fail at the First Hire
Most startup failures can be traced back to one early technical decision made by the wrong person. The wrong hire, the wrong tech stack, and a focus on trends over practical solutions set startups on an irreversible path of technical debt, wasted investment, and eventual failure.
The startups that succeed? They start lean, choose tech based on real needs, and hire pragmatic engineers who think beyond the code.
I’m building a startup — an AI product with a prompt-based interface designed to run on a company’s own hardware to protect their intellectual property.
How am I building it? Not in the cloud.
Instead, I’m using a gaming PC packed with RAM, large SSDs, and a mid-range GPU that I originally bought for my sons six years ago. With a high-speed optical internet connection, I can run everything at zero cost until I secure customers or investment.
No wasted cloud credits. No unnecessary overhead. Just a lean, efficient approach to getting the product off the ground.