What if chasing the latest software stack is sabotaging your business?
In this revealing episode, we sit down with Lucas Erb, founder of AIExperts.com and former Deloitte consultant, who challenges everything founders think they know about technology decisions. Discover why enterprises waste 38% of their IT budgets on redundant software, how Shopify's "boring" technology choice saved years of migration pain, and why your eight-year-old could now build what took computer science graduates four years to learn. Lucas reveals the hidden costs of constant platform switching, explains why most founders don't need custom AI solutions, and shares practical strategies for leveraging AI without the hype. This is the contrarian tech guidance you need before making your next software decision.
The conventional wisdom says you need the newest tech stack to attract top engineering talent and stay competitive. The reality is far different. While startups chase shiny new frameworks and bleeding-edge tools, they often overlook a fundamental truth: technology decisions should serve your business goals, not the other way around.
Lucas Erb brings a refreshingly practical perspective to technology strategy. Rather than building custom AI platforms that take six months to deploy, focus on what already works and improve it incrementally. The foundation models powering ChatGPT, Claude, and Microsoft Copilot are advancing rapidly. Leave the heavy lifting to companies with venture capital budgets and massive data centers. Your job is to leverage these tools effectively for your specific needs.
The path forward isn't about abandoning innovation. It's about strategic adoption that respects how humans actually change. Businesses are machines full of people, and people don't transform overnight. When you try to implement ten new software tools simultaneously, most go underutilized and deliver poor ROI. The frog-in-boiling-water analogy applies: gradual change succeeds where instant transformation fails.
For most founders, especially those running small to mid-sized businesses, the answer isn't building something new from scratch. It's training your team to use existing tools more effectively. A workforce that uses ChatGPT daily as an interactive tool can achieve twenty to thirty percent productivity improvements without any custom development. That's not theoretical. That's happening right now in businesses that prioritize upskilling over building.
The key is becoming the subject matter expert on your own workflow. You know what you did yesterday in five to ten minute increments. You clicked this application, sent that email, had this phone call. That knowledge, paired with rapid AI experimentation, reveals the biggest opportunities. Start by experimenting manually. When you find yourself running the same ChatGPT prompt repeatedly, that's your signal to automate it with a custom GPT or automated process.
Security concerns are valid but often overblown. If you operate on enterprise tiers and decline data training parameters, your information remains protected. Unless you're running a high-frequency trading firm or government agency with classified data, the same entities you already trust with your information, Google and Microsoft, handle your AI interactions safely. The age of truly proprietary information has largely passed anyway.
The real revolution isn't in the technology itself. It's in who can now build with it. Vibe coding tools like Cursor, Replit, and Claude Code have demolished traditional barriers to software development. An eight-year-old built a functioning Harry Potter app in a day. What once required a four-year computer science degree now happens in an afternoon. This democratization of building changes everything about how founders should approach technology decisions.
But democratization doesn't mean abandoning expertise. Your deep knowledge combined with AI becomes your competitive advantage. A lawyer with AI expertise beats AI alone every time. The same applies to every domain. Your expertise multiplied by AI capability creates value that neither can achieve independently.
The future belongs to founders who embrace proven tools, train their teams effectively, and build incrementally rather than chasing every new framework that emerges. Legacy technology often beats shiny new tools not because it's inherently superior, but because it's stable, understood, and already integrated into your operations. Sometimes the smartest technology decision is using what works and making it work better.
Watch the Full Episode on Why Legacy Tech Beats Shiny New Tools with Lucas Erb below:
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