Best Recipes Ever

Tag: microsoft 365

  • The Role of AI in Fast-Tracking Development and Reducing Technical Debt

    The Role of AI in Fast-Tracking Development and Reducing Technical Debt

    Throughout my career, whether in process improvement, business analysis, or low-code solution design, one theme has been painfully clear: time is always the constraint, and technical debt is always the silent killer.

    In recent years, AI has become less of a buzzword for me and more of a practical tool — especially when combined with platforms like Power Platform, Microsoft 365, and cloud services like AWS. AI, when applied correctly, doesn’t replace developers; it supports them in shipping better solutions faster and avoiding the future burden of rushed decisions.

    AI as a Development Companion, Not a Shortcut

    In the real world, most projects don’t fail because the team can’t write code. They fail because requirements evolve, businesses pivot, and quick fixes become permanent.

    AI helps address that problem early by:

    • speeding up repetitive or manual design tasks,
    • improving decision-making with better data insights, and
    • enabling automation of system behaviors that usually rely on human attention.

    For me, the turning point was when I stopped thinking of AI as a separate “feature” and started seeing it as an assistant woven into the development lifecycle.

    How AI Actively Reduces Technical Debt

    1. Smarter Requirement Gathering and Validation

    One of the most expensive sources of technical debt is misaligned requirements. AI services, especially in natural language processing (like AWS Transcribe, OpenAI’s APIs, or Azure AI), can turn voice notes, meetings, or unstructured conversations into actionable and reviewable documentation.

    In one of my recent projects, I used this approach to streamline the initial stages of solution design — cutting down on revisions later and lowering the risk of “building the wrong thing fast.”

    2. Predictive Automation for Maintenance

    AI isn’t just about development; it’s about sustaining the solution. Predictive analytics can help spot bottlenecks, usage anomalies, or scaling issues before they become production incidents.

    This proactive visibility reduces the need for hotfixes, rushed patches, and manual monitoring, which are all contributors to long-term technical debt.

    3. Intelligent Integration Mapping

    When connecting multiple systems (think SharePoint lists, document libraries, cloud storage, AI APIs) — one of the main causes of future rework is misaligned data mapping.

    Using AI-powered tools, you can automate much of this mapping and even detect schema drift or inconsistent data patterns before they silently break your workflows.

    AI + Low-Code: A Strong Combination

    In the context of low-code development, AI feels less like “advanced tech” and more like an invisible design partner.

    For example:

    • Automating document classification in SharePoint using AI-powered models,
    • Translating audio to structured text for form inputs using AWS Transcribe,
    • Using AI to suggest improvements in workflow paths in Power Automate.

    All these use cases save development time and dramatically reduce the kind of patchwork fixes that would otherwise turn into long-term technical debt.

    Final Thoughts

    AI isn’t about replacing developers or solving every problem automatically. It’s about giving development teams, business analysts, and solution designers the tools to avoid costly mistakes and repetitive tasks.

    In my own experience, AI works best when you treat it as part of the solution architecture — not as a post-launch enhancement.

    Less manual work. Fewer last-minute fixes. More sustainable solutions.

    That’s how AI really helps reduce technical debt.

  • Why Low-Code Isn’t Just a Shortcut — It’s a Smarter Way to Build

    Why Low-Code Isn’t Just a Shortcut — It’s a Smarter Way to Build

    When I started my journey designing solutions for real businesses, I wasn’t chasing fancy codebases or trendy frameworks. I was trying to solve real problems: messy processes, scattered data, inefficient handoffs, and the gap between what businesses need and what IT can deliver.

    That’s where low-code platforms stepped in — not as a replacement for traditional development, but as an accelerator for meaningful, maintainable solutions.

    The Case for Low-Code: Beyond the Buzzwords

    Low-code development is often marketed as a way for “non-technical users” to build apps. While that’s true to some extent, it misses the bigger picture: low-code is about enabling faster delivery, better iteration, and tighter alignment between business goals and technical implementation.

    In my own projects — whether automating document handling in SharePoint, building Power Platform apps for requirement gathering, or integrating AI services like AWS Transcribe into business workflows — low-code helped me focus on the part that matters most: the problem, not the plumbing.

    Here’s why I believe low-code deserves a permanent place in the modern development toolbox.

    Advantages of Low-Code: Practical Wins

    1. Faster Time-to-Value

    When a process is broken, businesses can’t afford six-month development cycles. Low-code tools make it possible to go from idea to prototype — and often production — in days or weeks, not quarters.

    In one of my projects, using Power Automate and SharePoint cut the time needed to develop a document intake system from an estimated 2 months of custom code to 2 weeks of iterative, testable builds. The business got what it needed faster, and the feedback loop stayed tight.

    2. Integration Made Easier

    Low-code platforms are often underestimated in how well they handle integration. Through connectors, APIs, and extensible components, I’ve seen low-code solutions connect legacy systems, cloud services, and modern AI APIs — all without rewriting the wheel.

    For example, sending audio files from Power Automate to AWS S3 for transcription, and routing the processed data back into SharePoint, would’ve traditionally involved custom scripts and manual deployment pipelines. With a low-code approach, I focused on the business logic and data flow, not server management.

    3. Lower Maintenance Overhead

    Code is only fun on the day you write it. Long-term, it becomes technical debt. Low-code platforms shift some of that burden to managed services, freeing you to focus on evolving the solution rather than babysitting it.

    4. Business-Driven Innovation

    This is the most underrated advantage: low-code forces developers to think like business analysts, and empowers analysts to think like solution designers.

    I’ve worked both sides of that fence. Low-code helped me bridge the gap between “what the business wants” and “what IT can build” — by allowing both sides to collaborate around real, functional prototypes, not endless slide decks.

    The Other Side of the Coin: Disadvantages

    No technology is perfect, and low-code has its limitations. Here’s what I’ve learned:

    1. Black Box Problems

    Sometimes you need to step outside the visual environment to debug or optimize performance. Low-code platforms can abstract away too much, making deep troubleshooting difficult unless you understand the underlying systems.

    2. Vendor Lock-In

    Your app is only as future-proof as your platform. I’ve faced situations where moving a solution away from Microsoft’s ecosystem (or AWS, for that matter) meant almost starting from scratch. Designing with portability in mind is key.

    3. Scalability Isn’t Always Plug-and-Play

    While low-code scales well for many internal business solutions, you’ll hit ceilings if you try to push them like traditional cloud-native apps. Understanding where low-code shines — and where traditional development should take over — is part of the craft.

    The Bottom Line: Use the Right Tool for the Job

    Low-code isn’t about replacing developers, and it’s not a “magic wand” for digital transformation. It’s about compressing the time between problem discovery and solution delivery, and empowering more people to participate in that process.

    For me, it’s become more than a tool — it’s part of how I think about solutions: start simple, iterate fast, automate where possible, and leave room for growth.

    Whether you’re building a requirements app, automating document handling, or integrating AI into your business logic, low-code platforms give you the freedom to focus on solving real problems — not just writing code.