AI in 2026: It's About Connecting The Dots

The conversation around AI has become exhaustingly polarized—breathless evangelists on one side, dismissive skeptics on the other. I find myself somewhere in the middle: curious but cautious, experimental but principled.

As I look ahead to 2026, I want to articulate how I envision AI's role in my work as a technology blogger, content creator, and independent web advocate. This is informed by the guiding principles I documented (https://meta.numericcitizen.me/ai/) and shaped by my experience as a hobbyist who loves exploring new information technologies for creative and learning aspirations—not career goals.

AI as Learning Accelerator

I see AI as a force multiplier for learning, particularly for understanding specific technologies where traditional resources are scattered.

As someone who explores various platforms and tools—both for my own use and to cover on my websites and YouTube channel—I'm constantly encountering technologies with varying learning curves. When I'm building small web applications, experimenting with APIs or MCP, or creating automation workflows, documentation can be scattered, incomplete, or written for different skill levels than where I'm starting.

This is where AI becomes invaluable by explaining specific technologies in ways that match my current understanding and specific needs. When I'm trying to understand how to connect two services or figure out why something isn't working, AI can tailor explanations to my specific question and context.

I'm using AI to understand, not to blindly generate solutions. This is about making the process of understanding specific technologies more efficient, so I can spend more time on the creative and analytical work that actually matters. Here are two examples.

Claude Code helps me understand how to approach problems. When I build small projects that support my creative work, it helps me see how experienced developers think about solutions. My goal is to understand enough to build the specific tools I need and satisfy my curiosity about how systems function.

n8n is about making specific parts of my creative workflow more efficient and predictable where it genuinely makes sense. AI supports this by helping me understand how to configure workflows and debug issues—freeing me to focus on content creation, learning, and exploration. As I mentioned in my year-in-review, n8n is becoming my digital playground for 2026.

Summarization: The Essential Use Case

The use case I think about most is summarization. As a technology blogger, I follow numerous information sources across the indie web, productivity software, and information technology. I consume more content across many sources than I can possibly read or watch in full depth.

AI-generated summaries help me triage effectively. I can quickly determine whether content deserves my full attention or whether the core insights are adequately captured. This isn't about replacing primary sources—when something matters, I still engage with the original. It's about making the discovery process manageable and expanding my capacity to cover more ground in content consumption.

My pragmatic conclusion for 2026: I prefer an imperfect summary to missing out on important content entirely.

Connecting the Dots: AI as Writing Partner

One aspect of AI that I find genuinely valuable—and that wasn't even possible five years ago—is using it as a writing assistant. This is another way AI helps me connect the dots.

When I'm drafting essays, blog posts, or thinking through complex topics, AI helps me make connections between concepts and ideas that I might not see immediately. I might be writing about automation workflows and AI can help me recognize how that relates to something I wrote about platform independence months ago. Or I'm exploring a new productivity tool and AI helps me articulate how its approach differs from patterns I've discussed before.

AI helps me see the larger patterns in my own thinking, suggesting connections that I then evaluate and develop in my own words. It acts as a thinking partner that helps me connect dots across my work in ways that make my writing richer and more coherent.

This capability has changed how I approach longer pieces. I can work through ideas conversationally, test connections, and refine my thinking before committing words to the page. Five years ago, this kind of interaction simply didn't exist. Now it's become a valuable part of how I develop my ideas and structure my writing.

Staying Curious, Vigilant, and Critical

As AI capabilities continue to evolve, I'm genuinely curious about how these offerings might impact my digital life as a creator. Will new AI tools emerge that fundamentally change how I research, create, or publish content? Will AI integration become so seamless in the platforms I use that it shifts what's possible in my workflows?

I don't know the answers, and that's what makes 2026 interesting. I want to stay open to possibilities while maintaining the critical lens that has guided my approach so far.

This means continuing to evaluate AI offerings against my established principles: Does this solve a real problem or create busywork? Does it align with my values around privacy and independence? Does it amplify my voice or dilute it? Does it support the indie web ecosystem I advocate for?

The AI landscape moves quickly, and not every development deserves equal attention or adoption. My commitment for 2026 is to remain curious about what's emerging, vigilant about how these tools actually perform in practice, and critical about their true value proposition.

The Independence Paradox

There's an obvious tension here: I advocate for indie web values and platform independence, yet I rely on Claude and ChatGPT—centralized AI services from large tech companies.

I think about this tension as the difference between tools and platforms. I'm using AI as production infrastructure to support work I publish on systems I control, not building my digital presence on AI platforms themselves. It's more like using VS Code than like building my blog on Substack.

But the tension is real. These services could change pricing or terms. They involve sending data through commercial systems. They create dependencies.

For now, I'm comfortable with this trade-off because AI helps me build and maintain my own infrastructure more effectively. But I'm watching it. If the dependencies start compromising the independence I value, I'll need to reconsider.

I suspect many in the indie web community face similar tensions as they evaluate AI tools.

Looking Ahead

I haven't landed on either extreme—the evangelists proclaiming AI will revolutionize everything or the skeptics dismissing it as worthless hype. I'm a hobbyist learner and creator with established principles and a commitment to documenting what works—and what doesn't.

For me in 2026, AI means:

• A learning accelerator for understanding specific technologies
• A processing tool for managing information consumption through summarization
• A writing partner that helps me connect concepts and ideas across my work
• An explanation tool that adapts to my context and learning needs
• A support tool for selective automation that makes creative work more efficient

But always with me in the decision-making seat. My curiosity drives what I explore. My judgment determines what I publish. My values guide how I use these tools. And my creative aspirations, not career goals, shape how I engage with technology.

The indie web has always been about taking ownership of your digital presence, choosing tools intentionally, and building for yourself. AI, used thoughtfully, can be part of that story in 2026—not as a replacement for human creativity and judgment, but as another tool in the independent creator's kit.