Articles

The AI coding tools market doubled to $12.8 billion in 18 months. 90% of professional developers use an AI tool daily. The category has fractured into coding agents, agent frameworks, a protocol layer, generation platforms, and an evaluation stack. Here is the complete field guide to what shipped, what works, and what to watch next.

AI-assisted coding evolved from autocomplete to copilots to autonomous agents in five years. The next phase — intent-driven development, self-healing systems, AI-native languages, and formal verification at scale — will transform not just how we write software but whether we write it at all.

AI in healthcare is shifting from single-purpose models to autonomous agents that reason across patient records, coordinate care workflows, and assist in diagnosis and treatment planning. The FDA has authorized over 1,500 AI-enabled devices, but no autonomous AI prescription system has been cleared. Here is how the transition is unfolding and what engineers building healthcare AI need to know.

Classical computing is hitting walls for AI: training costs in the billions, energy consumption rivaling small countries, and combinatorial optimization bottlenecks that scale exponentially. Quantum computing offers a fundamentally different computational model for the hardest problems in AI.

80% of AI projects fail to deliver value. The top causes are incomplete requirements, missing user research, and skipping discovery. AI agents make building fast, but speed without direction produces throwaway code. Here is the planning framework that changes the odds.