On 3 May 2025 I asked my tech network on X:
"If you work in tech, do you use AI in your job? Please vote and (if you can) reply with the tools you use."
682 people voted.
| Role & Usage | Votes | % of all voters |
|---|---|---|
| Developer — uses AI | 572 | 83.9 % |
| Manager — uses AI | 69 | 10.1 % |
| Developer — doesn't use AI | 28 | 4.1 % |
| Manager — doesn't use AI | 13 | 1.9 % |
Within each role
- Developers using AI: 572 / 600 => 95 % (~ 9 in 10)
- Engineering managers using AI: 69 / 82 => 84 % (~ 8 in 10)
The big picture
AI is no longer a "nice to have". Nine out of ten engineers and eight out of ten engineering managers already rely on it daily. Only 6 % of voters remain AI-free.
What tools are hot
From 20 + replies, these names surfaced again and again:
| Category | Popular tools mentioned |
|---|---|
| Coding assistants | GitHub Copilot, Cursor, Claude 3.5 |
| General chat LLMs | ChatGPT, Gemini, Grok |
| Low-/no-code & agents | Flutterflow, Retool, n8n + AI agents |
| Docs & meeting notes | GleanChat, NotebookLM |
| Code review & PR bots | GitHub bots, Copilot-for-Emacs |
| Research / brainstorming | ChatGPT Advanced Data, Gemini |
How people actually use AI
- Rapid POCs and prototyping
- Explaining unfamiliar code bases
- Auto-writing unit tests & configs
- Drafting & polishing documents and RFCs
- Summarising meetings and logs
- Brainstorming solutions before coding
- "Controlled" self-paced learning (ask -> dig -> zoom-out)
Why a few still hold back
- Trust — fear of hallucinations or leaking code.
- Habit — they feel "fast enough" with their current workflow.
Both shrink once teams add guard-rails (private models, review gates) and run small experiments.
Two favourite real-world use-cases
Engineering-manager reply
- Automating daily workflows in n8n (AI Agents + MCP)
- Summarising any thread they're tagged in
- Polishing write-ups
- "Controlled learning" at their own pace
- Vibe-coding MVPs for fun
Engineer reply
"Copilot writes the dull boilerplate, ChatGPT explains legacy code. Feels like I got a junior dev + a tutor on demand."
These show why adoption is so high: AI erases drudge work and unlocks rapid learning — whether you manage people or write code.
My take — opinion
I think AI will soon fade into the background, like IDE auto-complete did years ago. The winning teams will be those that treat AI as a junior teammate — review its output, feed it context, let it handle the boring 80 %, and reserve human focus for the tricky 20 %.
Key takeaway
If you're still on the fence, start small:
- Pick one boring task (e.g. commit messages).
- Test a focused tool (Cursor or Copilot) for a week.
- Keep only what measurably saves time.
Chances are, you'll join the 90 % before month-end.
Got a different experience? Drop a comment below or ping me on X — I'd love to hear it!