Why AI can't replace skilled developers with strong foundations
AI coding assistants are reshaping how teams develop software, but over-reliance on these tools risks creating developers who lack deep technical expertise and problem-solving skills.
AI coding assistants are reshaping how teams develop software, but over-reliance on these tools risks creating developers who lack deep technical expertise and problem-solving skills.

Figma’s AI design assistant now bridges the gap between visual editing and production codebases, enabling non-technical teams to push changes directly to GitHub while maintaining engineering guardrails.

Anthropic’s AI model now authors over 80% of its production code, forcing enterprises to rethink development workflows and adopt AI agents for scalable automation.

Moonshot AI’s latest K2.7-Code update claims to slash thinking tokens by 30% and boost coding performance, yet independent tests reveal uneven results. What does this mean for teams evaluating AI coding models?