Finding clarity in the chaos

Most people try AI tools, get mediocre results, and go back to doing things the old way. They're right, in a way. If you approach AI as a one-shot replacement for your existing workflow, you'll probably be disappointed and will feel slower.

But what if we see beyond that and flip our understanding and intention?

The AI-first mindset

For the past couple of months, I've been experimenting with a different approach. Before starting any task, I ask: how can AI help me do this faster and better?

Not to do it for me. Enable me.

This shift led me to share my recent experience with Claude Code where I used it to rapidly iterate on Buffer's engineering direction. The breakthrough came from enhancing my entire personal knowledge management system. Being able to access, navigate, and synthesize years of thinking at a completely different speed and depth.

When you approach tasks with AI as your assistant rather than your replacement, and lead with curiosity, something shifts. The friction disappears. Even when the output isn't immediately perfect, you learn something. And that learning compounds.

I believe so strongly in the impact of embracing AI to assist with everything that I made it one of our strategic themes in Buffer's engineering direction. Not as a nice-to-have, but as a fundamental shift in how we work. We must become AI-native in order to thrive.

The compound effect of curiosity

Sam Altman's 36 life reflections resonate deeply with my own 36 years on this planet. One insight particularly stands out: the small patterns compound into decades of learning.

When you shift to an AI-first mindset, you're not just changing how you work today. You're compounding advantages that will matter years from now.

Every experiment teaches you something. Every failed attempt reveals boundaries. Every success becomes a pattern you can replicate.

Making the shift

The transition to AI-first thinking isn't about tools. It's about approach.

Instead of asking "Can AI do this for me?" ask "How can AI enable me to do this better?"

Instead of one-shot attempts, think iterative refinement.

Instead of replacement, think augmentation.

The people who get value from AI aren't necessarily smarter or more technical. They're just more curious. They lead with questions rather than assumptions.

The future is already here

We're at an inflection point. The gap between AI-native and AI-resistant will only grow wider.

Not because AI will replace anyone. But because those who learn to work with AI will operate at a fundamentally different level of productivity and creativity.

The choice isn't whether to adopt AI. It's whether to adopt it now while the learning curve is manageable, or later when it's a competitive necessity.

Here's to more experiments, more documentation, and less perfection.

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