The AI Developer Workflow
We past the middle of 2025 and we are still inside an AI bubble. The winners from 6 months ago are the losers of tomorrow. New AI technologies, habits and tools change faster than the geopolitical climate in the US. Yesterday, all the AI hype was about Cursor but today, everything is about Gemini and Claude Code.
The early players are now irrelevant (who still talk about GitHub copilot?), and model providers are doing everything possible to go beyond the API and capture the value delivered at the application level. We are seeing this with coding tools (Anthropic with Claude Code, OpenAI with Codex, Google with Gemini CLI) and it starts to happen in other domains as well (see Claude for financial services or even the AI companions from Grok).
There is the workflow I use today for:
search: any search is done with ChatGPT desktop. When alone/at home, I rely on voice mode and type when in the office. I rarely use Google anymore and when searching, use alternative search engines (brave or kagi)
large coding tasks: I use Claude Code (at work) or Gemini (at home) for any coding tasks larger than 2 lines. Both Claude Code and Gemini have similar performance and write 90%+ of the code I ship today.
refining code: I use whatever is integrated in my IDE to refine the generated code and complete a line. IDEs like JetBrains have internal inline completion that are pretty good and free. Users now expect IDEs to have a good inline completion out of the box.
I feel we are still not in the final stage of what AI-enabled development tools can do. We may abstract them more and instead of writing code in the command line, integrate them into projects management tools (e.g. Jira). Claude Code or Gemini CLI may be the cool kids today but I wouldn’t be surprised if new tools come in a few months with a better integration into the developer workflow.