AI agents now plan, code, and test at senior-dev levels. The new bottleneck isn’t typing speed—it’s your ability to clarify intent, structure work, and review output.
The story
I’m watching software shift from “type faster” to “think clearer,” and it’s a whole new *mode*.
When AI agents can plan, code, and test, the bottleneck moves from fingers… to judgment, and that’s the *code*.
Data point that matters: 84% of developers are using or planning to use AI tools, up from 76% last year. Adoption isn’t a vibe; it’s a migration.
So how necessary is traditional dev experience to write good software now? Less necessary than it used to be. Not “never,” not “magic,” just… different leverage. Tools like Devin and other agentic systems are hitting senior-level performance on benchmarks like SWE-bench, and copilots like GitHub Copilot, JetBrains AI, Cursor Composer, and OpenHands can operate across real codebases.
Can anyone write good software? Potentially, yes, if they can do the two human jobs AI still can’t outsource cleanly:
1] Clarify intent: requirements, constraints, acceptance tests.
2] Structure the work: chunking, modular prompts, no “vibe coding.”
3] Oversee reality: review for business fit, security, maintainability.
4] Run the loop: generate, test, iterate, deploy.
If you want to make the most of AI, aim for #EfficientAIUse: pick the right model for reasoning or computer control, then manage the agents like a tiny team. Less hero-coder energy; more calm product owner with a debugger.
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