Open source didn’t die. It became the control plane for AI.
Generating code without a rigorous validation framework is not engineering. It is simply mass-producing technical debt.
Permissions for agentic systems are a mess of vendor-specific toggles. We need something like a ‘Creative Commons’ for agent behavior.
As LLMs and coding agents reduce reliance on small open-source libraries and make large ones harder to maintain, the future of open source looks smaller, quieter, and much more exclusive.
Improving developer productivity isn’t about producing more code faster, but producing well-architected, secure, and maintainable code. It’s about platforms, golden paths, and guardrails.
The database is no longer just where data lives, but where context gets assembled. And in AI, context is everything.
To keep AI coding assistants from running amok, developers must learn to write good specs and develop product management skills.
Developer trust in tools and a reliable ecosystem are a hard combination to beat. Competing tools, like Google’s Antigravity, need to deliver more than innovation.