When to Use AI vs. When to Think
Tech Lead
Architecture decisions, team trade-offs, and roadmap calls — these stay human. Use AI for drafting and research.
Cto
Strategic decisions need your judgment. AI can summarize options; you choose.
When to Use AI vs. When to Think
TL;DR
- AI accelerates tasks with clear inputs and outputs. It struggles with judgment, trade-offs, and "it depends."
- Use AI for drafting, research, and pattern-matching. Don't use it to make decisions for you.
- When in doubt: use AI to explore, you to decide.
Not everything should go through AI. Some tasks get worse when you delegate to a model. Knowing the difference saves time and prevents bad outcomes.
The Quick Decision Test
Use AI when:
- The task has a clear format (code, doc, summary, test).
- You can verify the output (you know the domain).
- The stakes of a wrong answer are low or recoverable.
- You're doing pattern-matching or transformation (e.g., "convert this to TypeScript," "summarize these logs").
Think it through (or think first, then use AI) when:
- The answer depends on context AI doesn't have (org politics, team capacity, legacy constraints).
- The stakes are high (architecture, security, hiring, legal).
- There's no single "right" answer — it's a trade-off.
- You're still figuring out what the question is.
The "It Depends" Trap
AI loves to give a definitive answer. But many real problems are "it depends on X, Y, Z." When you ask "Should we use microservices or a monolith?", AI will give you a balanced essay. It won't know your team size, your deployment cadence, or your tolerance for operational complexity.
Use AI to list options and trade-offs. You supply the context and make the call.
When AI Actively Hurts
- Premature convergence — AI gives you an answer. You stop exploring. Sometimes the best answer is the third one you hadn't thought of.
- False confidence — AI sounds sure. You stop questioning. Verify.
- Context blindness — AI doesn't know your codebase, your customers, or your org. Generic advice can be wrong for you.
- Ethics and judgment — AI can't weigh fairness, culture fit, or "how will this play in the all-hands?"
A Simple Framework
| Situation | Approach |
|---|---|
| "Write a test for this function" | Use AI. Review. Ship. |
| "What's the best way to structure our event pipeline?" | Think first. Use AI to brainstorm options. You choose. |
| "Draft a status update for the exec team" | Use AI for draft. You add nuance, politics, tone. |
| "Should we refactor this now or later?" | Think. AI can't weigh opportunity cost, team capacity, or risk. |
| "Explain this error" | Use AI. Then verify the explanation matches your setup. |
You spend 45 minutes writing a status update email. You research the topic manually. You draft, edit, re-draft. You second-guess the tone. You send it and immediately think of something you forgot.
Click "With AI" to see the difference →
Quick Check
Your team is debating whether to refactor a critical payment service or build a new feature. What's the best use of AI here?
Do This Next
- Audit one decision you made this week. Would AI have helped? Would it have led you astray? Reflect.
- Create a personal "AI or me?" rule of thumb for your role. E.g., "For technical decisions with 3+ options, I think first, then use AI to stress-test."