Seattle AI Consultant

Tag: Gen AI

  • Will AI Kill No-Code Tools?

    Will AI Kill No-Code Tools?

    The no-code and low-code revolution made it possible for almost anyone to build web and mobile apps without writing code. Entrepreneurs, small business owners, and non-technical product managers could create robust, data-driven applications using tools like Bubble, Glide, or OutSystems. These platforms lowered the barrier to entry—and the cost—of software development.

    Now AI is entering the scene, and many are asking: will AI replace no-code tools?

    The short answer is no, not anytime soon. But the longer answer is more interesting—because AI is transforming the no-code landscape in two big ways. Depending on how you look at it, that might feel like competition—or a major upgrade.

    AI as an enhancer of no-code platforms

    The first shift is straightforward: AI is making no-code and low-code tools better.

    If you’ve used Make.com or Zapier lately, you’ve likely seen AI-powered steps for things like summarizing messages or drafting personalized emails. Tools like Bubble and Softr are embedding natural language interfaces that let you build app features by typing what you want, instead of using drag-and-drop.

    This integration gives no-code tools a major boost in usability. You can describe what you want, and the system fills in much of the setup. Need a dashboard with KPIs from Google Sheets? Just ask, and the tool does the heavy lifting—at least part of it.

    AI doesn’t replace the no-code tool; it improves it.

    AI as an alternative to no-code

    We’re also seeing something more radical: AI starting to function as a no-code tool.

    With models like GPT-4, Gemini, and Claude, users can now describe entire applications in plain English. These tools generate working code, database schemas, and even deployable app components based on prompts. Several startups now promise “an app in five minutes” by chatting with a bot.

    Here, AI is the builder. It’s not just integrated into the platform—it is the platform.

    That might sound like the end of no-code. But not so fast.

    Reality check: AI still needs humans—especially skilled ones

    A recent survey from Unqork found that 84% of tech leaders say AI won’t replace no-code and low-code tools. Why? Because AI alone isn’t enough—especially for business-critical apps that need to be secure, scalable, and maintainable.

    Right now, AI-generated apps are often half-baked. They might work in a demo, but under the hood they can be fragile, poorly structured, or riddled with incorrect assumptions. Fixing them often requires solid software knowledge—sometimes more than if you’d built the app from scratch.

    In other words, AI is a powerful assistant, but not a substitute for experienced developers or no-code pros.

    And while visual tools may have a learning curve, they offer control. Many users prefer being able to see exactly how their data flows, what logic drives automations, and where the system might break.

    So where are we headed?

    We’re heading into a blended future—where AI and no-code tools work together.

    For everyday users, AI will make no-code tools more accessible and less frustrating. You’ll be able to start faster, make changes with simple instructions, and get AI-generated suggestions to improve your app.

    For developers and advanced users, AI becomes a tool for scaffolding—helping you build faster, then handing off control for refinement and scale.

    And for AI and no-code consultants like me, this hybrid world opens new opportunities: helping businesses bridge the gap between what AI can generate and what they actually need. Whether that means integrating AI into workflows, building with Make.com, or troubleshooting an AI-built app that almost works—we’re here to help.

    No, AI isn’t killing no-code. It’s pushing it to the next level.

  • Boost Your Writing with Multiple Personas: An Advanced AI Prompting Technique

    Boost Your Writing with Multiple Personas: An Advanced AI Prompting Technique

    As someone who works in AI communications, I’ve seen firsthand how generative AI is transforming the way we write. But here’s the secret sauce to taking your content to the next level: multiple personas. It’s an advanced prompting technique that taps into AI tools trained on different datasets to enrich your writing with incredible depth and variety.

    Think of it like having a team of co-writers, each with their own voice and expertise. One persona might specialize in data-driven analysis, another could channel a creative storyteller, while a third offers a casual, conversational tone (like this one). By blending these perspectives, you get content that’s nuanced, dynamic, and, most importantly, engaging.

    Why does this work so well? Because different personas bring different strengths to the table. As highlighted in this Forbes article, combining personas helps bridge gaps in tone and perspective, creating more balanced and versatile content. It’s like tapping into multiple viewpoints to ensure your message resonates with a broader audience.

    Here’s an example: Say you’re writing a blog on climate change. You could prompt one persona to take an academic approach, diving into hard data. Then, you could ask another persona to write a heartfelt call to action. Finally, a third persona might add practical tips for readers. Merge these inputs, and suddenly you’ve got a well-rounded, compelling piece that informs, moves, and inspires.

    The key to mastering this technique is knowing your audience and selecting personas that align with their needs. Whether you’re crafting marketing copy, educational materials, or storytelling, the multi-persona method adds layers of sophistication to your work.

    So, why settle for one voice when you can have a chorus? With AI personas, you’re not just writing—you’re orchestrating. And the results? Complex, captivating content that stands out.