Working With AI in 2026
March 2026
AI is everywhere now. It's in your phone, your email app, your search results. But most guides for "using AI" treat it like a magical assistant that "understands" you.
It doesn't. Here's a practical framework for working with AI tools productively.
AI Is a Tool, Not a Colleague
The AI doesn't know you. It doesn't care about your goals. It's not "thinking" in any meaningful sense. It's pattern-matching on an enormous scale.
This isn't dismissive — it's clarifying. A calculator doesn't "understand" math, but it's incredibly useful for solving equations. Same principle.
When AI Excels
- First drafts: Getting something on paper when you're stuck
- Explaining concepts: "Explain this like I'm 15"
- Code patterns: Boilerplate, syntax, debugging obvious errors
- Brainstorming: Generating options you can evaluate yourself
- Research directions: Finding terms and concepts to investigate further
When AI Fails
- Novel facts: It confidently states things that aren't true
- Recent events: Training data has a cutoff
- Nuanced judgment: Ethics, taste, "is this good?"
- Citation: It creates plausible-looking references that don't exist
- Emotional support: It can simulate empathy but has none
Rule of thumb: If you'd feel weird asking a search engine, you probably shouldn't ask AI either. For everything else, verify the output.
The Verification Discipline
Get in the habit of:
- Getting the AI output
- Asking "why did it say that?"
- Checking key claims against actual sources
- Treating the output as a rough draft, not a final answer
This takes longer than copy-pasting, but it's how you avoid being the person who cited a hallucinated paper.
Bringing It Back to People
We built Merciful.ai with this in mind. It's a thinking tool — use it to work through ideas, then take those ideas to real people.
Read more about how it works or check out our other posts on human-AI connections and AI safeguards.