“The illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn, and relearn.” — Alvin Toffler
In this new year, you cannot ignore the paradigm shifts happening in our world, and the paradigm shift right now is AI. A couple years ago, AI was just an interesting toy. Well, that was also true about Linux—just a basement project by Linus Torvalds that became the foundation of the Internet and the open source world. AI is following a similar revolutionary path, and those who take advantage of it will profit while those who don’t will fall behind.
Even with its current limitations—it’s not fully autonomous and lacks common sense—AI can do a lot of useful stuff right now. My professional interest, and probably yours, is making useful tools. It’s good at writing shell scripts and basic code from a single prompt. I had it refactor my Ansible playbooks and found ways to improve what I had.
For bigger projects, so long as you use proper guardrails such as test-driven development, modularizing code, and working within AI’s constraints—you can leverage AI for everyday tasks.
This year I found myself taking on work I wouldn’t have dreamed of before. I stepped outside my familiar lane of JavaScript and Python to embrace frameworks better suited for scaling and efficiency, like Rust and Go. Tools like MCP (Model Context Protocol) opened doors by letting AI coding agents actually see and work with code. I’m now writing agentic systems using frameworks like LangChain and working with vector databases like Pinecone or ChromaDB—tools I had little familiarity with before.
These doors opened because large language models came onto the scene. If you’re holding out until AI is “safe and reliable,” I think you’ll miss the boat. What I’ve found while developing AI applications is that this is a deeply evolving ecosystem requiring you to understand and work with the plumbing in your area of expertise.
You can write agents that manage other agents in workflows using tools like CrewAI, where you create agents based on roles. You can leverage workflow frameworks with AI capabilities like n8n, which enable powerful automations. Better yet, these are self-hosted—so if you’re concerned about proprietary business logic being acquired by Big Tech, you can use open source large language models that are approaching frontier model performance.
It’s not too late to prepare yourself for this year and the coming years. It’s now possible to create a one-person startup once you learn orchestration, agents, and workflows. These systems can manage customer follow-up, lead generation, demonstrations, even writing, reviewing, and debugging code.
While AGI may never become a reality, you can do remarkable things with AI technology as it exists today. Those who learn to adapt will reap the rewards. Those who don’t… go extinct.
Happy New Year.