Legacy system modernization approaches span six proven strategies, from rehosting to replacing, now accelerated by AI tools that cut timelines and reduce risk.
How AI-Accelerated Software Development Is Changing Engineering Teams
Over the past year, we’ve had a lot of conversations with developers and engineering leaders asking the same question: “Is AI going to replace software engineers?” It’s a fair concern. AI coding tools can now generate code, write tests, and handle implementation work that used to take hours. But that’s not what we’re seeing in real enterprise software development environments …
AI Software Development Costs 2026: Enterprise Spending, TCO, and ROI Analysis
2026 analysis of AI software development costs exploring enterprise spending trends, total cost of ownership (TCO), build-vs-buy decisions, and how AI-accelerated development is reducing delivery timelines and improving ROI for CTOs and engineering leaders.
Mobile App Deployment in the Real World: Subscriptions, Services, and Platform Realities (Part 3)
Mobile app deployment is where many promising ideas start to encounter real-world friction. What worked as a prototype suddenly has to meet the expectations of app store ecosystems, subscription models, and an increasingly complex stack of services. In this third part of the Pennies-AI journey, we’ll explore what it actually takes to navigate the maze of mobile deployment and monetization. …
Turning a Prototype into a Production App: Architecture, Costs, and Hard Lessons (Part 2)
Part 2 of my series focuses on what it took to move from “it works” to turning a prototype into a production app, something stable enough to depend on and run in production. Beyond new features, it explores the architectural decisions, infrastructure trade-offs, and real-world costs involved in turning a prototype into a production app. Many of those lessons don’t show up in code, but they are every bit as important for success once real users and real expectations are involved.