AI is Faster Than I Am

I've spent my career building large-scale websites, mobile apps, and consumer and business platforms. I've always been a pragmatic adopter of new technology-I prefer tools that are mature, reliable, and likely to stick around before I invest time learning them.

That mindset made me late to AI.

When ChatGPT first launched, I was indifferent. It felt like a novelty-interesting, but limited. I didn't spend time exploring it or thinking deeply about where it could go.

Fast forward to early 2025. I had been using AI for code completion for about a year, but it didn't consistently fit my workflow. That changed on February 24, 2025, when Claude Code was released.

For the first time, I could describe what I wanted to build and iteratively refine the output until it matched my intent. It wasn't perfect-but it was a step change.

There were still limitations. When it made a mistake, you could ask it to fix the issue-but if it failed a second time, it was often faster to start over. It wasn't deeply intelligent, but it was responsive. As I improved my prompting, the results improved with me.

Then things accelerated.

Over the following months, the models improved rapidly. Tooling matured. Memory capabilities expanded. Progress was happening faster than I could comfortably track-and that led me to an idea:

Build a system that lets me control my development environment from my phone using voice.

In October 2025, I started building what I called the Bridge to AI Coder. The architecture came together quickly:

• Local speech-to-text to translate voice into commands
• A wrapper around Claude Code to execute tasks
• Hooks to capture output
• Text-to-speech to read responses when I couldn't look at a screen
• A custom document store for generated artifacts

It worked.

More importantly, it gave me leverage. I could code while walking, thinking, or away from my desk. I didn't plan to release it-I viewed it as a personal advantage.

Then the timeline compressed.

On February 25, 2026, Anthropic released remote control capabilities inside their platform. Overnight, the core differentiator of my project disappeared. The hardest part of what I had built was now a native feature.

That moment forced a realization:

AI is evolving faster than most individual builders-or even small teams-can keep up with.

And more importantly, we're all converging on the same ideas.

What I've Learned

1. Assume rapid iteration will solve today's limitations
   Most frustrations with AI tools are temporary. If something doesn't work well today, there's a high probability it will in the near future.
2. Your “edge” may be short-lived
   If you're building on top of foundation models, expect core capabilities to be commoditized quickly.
3. Speed of learning matters more than early adoption
   The advantage doesn't come from using AI first-it comes from adapting continuously.
4. AI is already highly capable-if used correctly
   Results are often constrained more by how we interact with the tools than by the tools themselves.

Final Thought

I'm no longer skeptical of AI's trajectory.

If you're not getting the results you want today, try again in a month. The pace of improvement is real-and it compounds.