The AI That Started Writing With Us Wasn’t the Smartest, Just the Most Useful
Article summary
The AI That Started Writing With Us Wasn’t the Smartest, Just the Most Useful Everyone kept asking if it was intelligent. We were asking something else: is it helpful? Not in theory, but in GitHub comments, release notes, user guides. We weren’t designing AI systems, we were integrating with them. And that made all the difference. Copilot changed the question from output to interaction OpenAI and GitHub Copilot had been in technical preview, but this was when the architecture world felt the ripple. This wasn’t just autocomplete. It was contextual completion, trained on open code, injected directly into IDEs. And it didn’t just speed up typing, it changed the tempo of design. Suddenly, developers weren’t working solo. Copilot hovered over each keystroke, suggesting boilerplate, edge cases, even full unit tests.
Read Full Article on MediumPractical takeaway
The main idea behind The AI That Started Writing With Us Wasn’t the Smartest, Just the Most Useful is to help teams move from broad theory to clear, repeatable decision making. When teams apply this thinking, they reduce ambiguity and focus on improvements that deliver measurable momentum.
Example scenario
Imagine a team facing competing priorities. By applying the ideas in The AI That Started Writing With Us Wasn’t the Smartest, Just the Most Useful, they can map dependencies, identify risks and choose the next move that produces progress without destabilizing their system.
Common mistakes to avoid
- Trying to redesign everything instead of taking small steps.
- Ignoring real constraints like incentives, ownership or legacy systems.
- Creating documents that do not lead to any change in code or decisions.
How to apply this in real work
Start by identifying where The AI That Started Writing With Us Wasn’t the Smartest, Just the Most Useful already shows up in your architecture or delivery flow. Then pick one area where clarity would reduce friction. Apply the idea, measure its effect and share the learning.
Signs you are doing it correctly
- Teams make decisions faster and with fewer disagreements.
- Architectural conversations become clearer and less abstract.
- Changes land safely with fewer surprises or rework cycles.