👨‍💻 Ben Matthews

Ten minutes to prototype. But technical debt accumulates faster than ever before. Yet I believe GitHub Copilot's 55% productivity gains fundamentally outweigh debugging overhead when examining comprehensive business impact data. I'm witnessing an unprecedented paradigm shift in software development that extends far beyond simple coding acceleration, fundamentally transforming how organizations conceptualize, validate, and iterate on complex products. Reddit's CPO confirms engineering teams conceptualize ideas one day and deploy functional prototypes the next morning. Traditional boundaries between discovery and testing have dissolved as AI enables "vibe coding" - exploratory development without extensive upfront architecture. Small companies with minimal engineering resources leverage these tools as competitive advantages, moving with unprecedented organizational agility while established enterprises struggle with legacy architectural constraints. However, Google's DORA report reveals 25% AI usage increase leads to 7.2% decrease in delivery stability across enterprise organizations. I counter that forward-thinking organizations treat AI prototypes as strategic starting points while maintaining rigorous architectural oversight and governance frameworks. Smart enterprises adapt without abandoning engineering best practices. Transformation accelerates.

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PSA: If you remove or deprecate a feature, give your engineering team the time to fully remove that feature from your codebase. Your future self (and your future team) will probably not remember to thank you, but their higher velocity might be a thank you enough. Every line of code in production comes with a cost, however hidden it may be in the present moment. End of message.

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The main benefit of practicing TDD is in producing fast tests. When not doing TDD, we tend to end up with sluggish, long-running tests. That situation creates the mood of avoiding adding more tests. With TDD, we don't paint ourselves into that ugly corner. I don't see any other way to produce fast-running tests.

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A lot of software process exists to solve a specific problem IMO: Devs get married to their first implementation; Stakeholders don’t tolerate rework If companies and individuals could throw more away, then we wouldn’t need to obsess over planning. The “spec” and “design” would get discovered through doing and redoing. I’ve never worked anywhere where a long up front design addressed the important design issues. Those almost always get discovered when you’ve tried to implement a solution a few times and failed. If we say throwing away as a feature rather than a bug, we’d probably work more efficiently.

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80% of software agencies deliver exactly what CTOs fear: • No real leadership • Zero accountability for outcomes • Technical debt instead of solutions I've had clients come to us after spending $250K with other agencies. Result: A pile of code that needs complete refactoring. The space is broken. At Nolte, I'm so confident in our delivery that I've invested in 90% of our clients over the past 3-4 years. That's not normal in this industry. But it should be. The difference: → We optimize for ROI, not billable hours → We own outcomes, not just deliverables → We bring strategic thinking, not just code Most agencies are vendors. We're partners. When you truly believe in what you're building, you put your money where your mouth is.

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A great craftsman never blames their tools—but they sure as heck know how to pick the right ones. 🛠️ Welcome to Part 4 of my series on building a QA Center of Excellence (CoE). We’ve covered Charter, Process, and Metrics. Today, we talk about the fourth pillar: Tools & Technology. In a CoE model, the goal isn't to mandate a single tool for everyone. It’s to provide a curated ecosystem that eliminates friction. My philosophy is that the tech stack should be a "force multiplier" for the engineering team, not a maintenance burden. As I’ve been diving deeper into Agentic AI Testing, it’s becoming clear that the next evolution of this pillar isn't just about better scripts—it's about intelligent automation. When building out this pillar, we focus on: Interoperability: Do our tools talk to each other? (From Jira to GitHub to our automation frameworks). Scalability: Can our infrastructure handle a 10x increase in test volume without breaking the bank? The AI Shift: Moving beyond static scripts toward self-healing tests and AI-driven exploratory tools. The right tech stack allows your QA engineers to stop acting like manual data entry clerks and start acting like Quality Architects. As we move into 2026, what’s the one tool in your stack that you consider "un-fireable"? And are you already looking at how AI will replace or augment it? #TestAutomation #AzureAI #QACoE #SoftwareEngineering #TechStack #AIinTesting

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Thinking of staying in software development? I wrote up a few thoughts, observations, and opinions on the topic for anybody wanting to get into or stay in software development in the coming years. The changes coming aren't going to be easy, they're likely to be somewhat brutal, for a number of reasons. This particular post I've kept the politics and the initial history of why we're here out of the post and focused on what to do. But I've got more coming and for now would love your thoughts, observations, hot takes, and the like.

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APIs break more often than you think, but not when they're built like this. High-traffic. High-stakes. High expectations. If your API can’t scale, secure, and sustain itself, your entire product might stall. That’s why every layer matters: ✅ Controller structuring ✅ Middleware setup ✅ Dependency injection ✅ Clean versioning and more This isn’t just a best-practices list; it’s a blueprint for building robust APIs with .NET Core and C#. 🔗 Read the full guide by Khurram Minhas, Principal SE at Arbisoft: https://lnkd.in/ddbyRbVC #DotNetCore #CSharp #APIdevelopment #ArbisoftBlogs

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If you have access to it, GitHub Spark is a great way to create quick prototypes. You can create real apps that use TypeScript and React using just prompts. If you are a Product Manager that wants to prototype something to show your engineering team, it's one of the easiest ways to do so. I've created a quick video of me creating a "chat with your PDF" app. The whole process took 8 minutes (the video is 75 seconds because I've accelerated it in some parts), including fixing a bug.

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If you’re planning to modernize a legacy system that's been running for years and still manages a high volume of client traffic, the strangler fig pattern might be something that can help. Read Martin Fowler's blog post about the Strangler Fig pattern application. https://lnkd.in/gxKMuQ5G https://lnkd.in/gMxK3KUS If you’ve walked this path, what tipped your decision one way or another? #modernization #StranglerFig #SRE #softwarearchitecture #engineeringmanagement

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