Signals

The author argues that agentic AI coding tools are slashing software development costs by up to 90% by automating labor-intensive tasks, unleashing latent demand for custom applications, and shifting the developer's role toward domain expertise and oversight.

IEEE's 2025 programming language rankings spark debate about AI's role in reducing language-specific concerns for developers.

Discussion on the challenges and limitations of using LLMs for code generation in production environments, exploring determinism concerns.

Stanford research examines whether AI tools are replacing or augmenting software developers, with mixed evidence on productivity claims.

Analysis of why AI coding tools haven't produced the expected flood of low-quality software despite productivity claims.

Fowler's provocative take that hallucinations are LLM features, not bugs, ignites philosophical discussion about AI consciousness and human cognition.