AI in Your Workflow

Use it like a tool, not like a personality.

Chapter 3 of 3

Where AI Fits in a Workday

The mistake most people make is treating AI as a separate activity. They open ChatGPT, have a conversation, copy the result, close the tab, and go back to work. That is like keeping a calculator in a different room.

AI tools work best when they are embedded in the flow of work, not bolted on top of it.


The Five-Minute Rule

If you are stuck on something and five minutes of AI assistance would unblock you, use it. If the task requires deep thought, domain knowledge, or creative judgment, the model will waste your time more than it saves.

Good five-minute uses:

Bad five-minute uses:

The first group has a clear, verifiable answer. The second group requires judgment that the model does not have.


IDE Integration

The highest-value AI integration for most engineers is inside the editor. GitHub Copilot, Cursor, Claude Code, Cody — the specific tool matters less than the habit.

What Works

What Does Not Work

The Habit

The habit to build is: small, frequent, verified. Use AI for small things, often, and always verify the output. That is the workflow that actually makes you faster without introducing risk.


For Teams

If you are a lead or manager thinking about how your team uses AI tools, a few things to consider.

Establish Norms, Not Bans

Blanket bans on AI tools are counterproductive. People will use them anyway — they will just hide it. Instead, establish norms:

AI Does Not Replace Code Review

AI-generated code needs the same review as human-written code. Maybe more, because the failure modes are different — models generate plausible-looking code that passes a casual glance but fails in edge cases a human writer would have caught.

If someone on your team submits a PR and says “AI wrote it,” the review standard does not change. The person who commits the code is responsible for it, regardless of who or what wrote it.

Knowledge Sharing Still Matters

A risk of heavy AI use is that people stop building shared understanding. Instead of asking a colleague how a service works, they ask the model. Instead of writing documentation, they generate it. Instead of discussing tradeoffs in a meeting, they paste the question into a chat.

The model cannot replace the knowledge that lives in your team’s heads. It cannot tell you why a decision was made, what was considered and rejected, or what the political context was. That knowledge transfers through conversations, code reviews, and documentation written by people who were there.

AI accelerates individual work. Shared understanding is what makes the team work. Do not let the first erode the second.


The Long View

AI tools will get better. Whatever limitations I described here will shrink or vanish in a few years. The models will know more, hallucinate less, and integrate deeper into every tool you use.

That means “how to use ChatGPT” is ephemeral knowledge. The skills that last are:

The people who benefit most from AI tools are the ones who were already good at their jobs. The tools amplify capability — they do not replace it.

Use them deliberately, verify the output, and keep thinking for yourself.


Chapter 3 of 3