Building an MVP that delivers value is key for a startup. Oftentimes, startups struggle with getting the first version out in a timely manner. There are some deadly mistakes that founders need to avoid to prevent sinking their startup. Today, we’re chatting with the Director of infrastructure, Alan Laser. Will be discussing how startup should approach their MVP, delight their customers, and much more.
What is the inspiration behind TechEmpower?
The inspiration behind TechEmpower is “Making it Safe to Innovate.” Generative AI is sparking a new wave of innovation across the entire tech space. The businesses that are being founded today will shape the way we interact with computers and with each other for the next century. It’s our job to help founders and CEOs take part in this revolution with confidence. Our clients provide the vision, and we provide the technical expertise. Our 25 years of experience means we know what it takes to succeed – not just how to build software, but also how to work with our clients to build the right software the right way.
We often get calls from founders who have faced difficulties after selecting the wrong tech team. It makes you wonder – how many startups burn through their first round of funding with nothing to show for it but a half-built, buggy MVP? That’s why we like to start our engagements by asking – and helping founders answer – questions like “What components should we buy versus build? What are my startup metrics? When will I need a CTO? ” Even founders with technical backgrounds often forget to ask these questions when starting out on their own.
Our goal is to make it safe to have great ideas. Our app development, fractional CTO, staff augmentation, hiring help, and technical review services are designed to help founders innovate with confidence.
What mistakes do you see founders make when it comes to MVP?
One common mistake we see is overbuilding. MV stands for “Minimally Viable!” To start with, your best bet is to build just enough of your product to get early customer metrics, most often your Customer Acquisition Cost (CAC) and Customer Lifetime Value (CLV). If you can get CAC and CLV signals (they don’t need to be perfect) then you can prove your business model. Here are some other tips we recommend:
Get a technical advisor. You probably don’t need a full-time CTO, but a fractional one is a good investment. A good technical advisor can help you answer questions you didn’t know to ask.
Be aggressive about asking questions, whoever your tech provider is. And if your tech provider isn’t asking you any, find someone else!
Set milestones and keep them. Don’t let feature creep turn your MVP into vaporware. And remember, your development team owes you demos to show they’re worth the money.
Worry about scaling if you’re just starting out. If your business model works out, then scaling becomes a question of capital.
Spend developer time or money on complicated backend and reporting tools. Google Sheets is already more than most startups need.
How should founders go about building useful products that deliver value?
Founders are a special kind of entrepreneur. They have a knack for seeing a problem and then building a product or a service to solve that problem. Of course, you want your business to be profitable – but if this were just about money, you’d be better off opening a Subway. You chose the founder’s path – despite the uncertainty – because of your unique vision.
The best way to deliver value will depend on just what problem you’re solving and how you’re solving it. But in our 25 years helping startups succeed, we’ve learned what works. Here are our top four recommendations on the best ways to build a valuable product or service:
Focus on a single problem, and find the simplest solution. Be absolutely clear about the problem you are solving. A well-defined problem will guide your product development process and help you stay focused. Always keep the KISS principle in mind. Complex solutions are risky, difficult and costly to build. Don’t overcomplicate your product with unnecessary features.
Build a strong user base, even if it’s small. Start by developing a deep understanding of your target audience. What are their pain points? What do they value? And as your user base grows, pay attention to what they want. Let their feedback prioritize bug fixes and guide new feature development. Think of your users as partners, not just customers.
Keep your MVP a MVP! The purpose of an MVP is to test your assumptions about your product and its market fit. It’s not meant to be a final product! If it’s complete enough to validate your business model, then it’s done.
Focus on user experience. Software is a competitive space. New products – especially B2C apps – need to invite the user in, and make their experience easy and enjoyable right away. Think about the last time you tried out a new app or a website. How long did it take you to decide to keep it, or to click uninstall? Probably not very long.
How does AI play a role in product development?
Generative AI should play a big role in the development of any software product, even if it’s not an “AI app.” If you’re building from the ground up, you’ve got a great opportunity to integrate AI into your product right from the very start. And if you’re looking for a way to inject value into an existing platform, then AI should be the first thing you look at.
Why should your application have empty textboxes when an LLM can provide writing prompts? Why settle for a traditional keyword-based search engine when you can have interactive natural language search? And these are just two obvious examples. AI has practical applications in customer service, sales and marketing, software engineering, customer operations, administrative reporting – the list goes on.
Where do you see the software development industry in the next five years?
In a word: busy. Generative AI will transform the way humans interact with computers. But it’s going to take time, and a lot of work, to make that transformation happen. Right now – and we think this will be the case for some time – generative AI is an 80% solution. It’s amazing, but it’s incomplete. The remaining 20% has to be filled in by human software engineers and human founders working together. And that’s going to keep us very busy!
Over the next five years, we expect to see radically new SDLC methodologies that integrate AI as a programmer, a smart automated tester, and a smart CI/CD engine. That doesn’t mean fewer engineering jobs, at least in the short term. If anything, demand for AI integrations is likely to cause a boom.
What is technical debt when it comes to startups? What tips do you have for founders?
Don’t be fooled – tech debt can be a problem even for startups.
Just as a reminder, here’s the standard definition: Technical debt is the cost of additional rework caused by choosing an easier/faster solution now instead of using a better approach that would take longer. In simpler terms – there wasn’t enough time to do it right, so now you have to do it over.
For startups, time-to-market takes precedence over quality code and architecture. We understand! Sometimes this is a necessary risk. But it’s always a risk. Even MVPs can be sunk by technical debt.
Here are some ways you can minimize your debt risk:
Prioritize Quality from the Start: Invest the time to create quality. If your goal is an acquisition, remember that someone will be reviewing the code before they buy or invest.
Code Reviews are Essential: All changes should go through peer and senior review. This saves time even in the short run, because it keeps devs up to date on parts of the code they might be working on tomorrow.
Your Codebase is More than Just Code: When we perform technical due diligence for investors, the very first thing we look at is metacode – documentation, inline comments, and commit messages. Why? Because if a team is doing those things right, it means they’ve got the discipline to do everything else right too. And with AI to help, there’s no excuse to skimp on good metacode.
What’s next with TechEmpower?
We’ve been successful for 25 years because of two reasons: our engineers and architects are the best in the business, and we’re passionate about helping founders build cool stuff. That’s not going to change. What has changed is the AI landscape. It’s already improving our ability to help founders succeed. We use Generative AI in-house now (while working on AI projects!) to chatshore documentation, automate testing, and prototype. It’s had a tremendously positive impact on our productivity. TechEmpower at 30 will be nimbler, faster, and even better than it is at 25.
Where can people learn more about TechEmpower?
You can learn more about TechEmpower by following our blog at https://www.techempower.com/blog or by following us on LinkedIn at https://www.linkedin.com/company/techempower We’re also always happy to talk to anyone about their software development needs! https://calendly.com/alaser