How to think about AI latency in product design
AI latency is not a single number and it does not behave like traditional API latency. The teams that design good AI-powered products understand what makes latency feel acceptable, what makes it feel broken, and how to design around the constraints that cannot be engineered away.
What good AI observability looks like
Traditional observability tells you if your system is up and how fast it is. AI systems need a second layer: is the output quality good, is it degrading, and why? The teams shipping reliable AI have built this layer. Most have not.
What AI means for technical documentation
Technical documentation has a new audience: AI systems that consume it to answer questions, generate code, and assist with operations. That changes what good documentation looks like, which parts of the investment pay off, and where human writing still has no substitute.
How AI is changing software testing
AI tools are reshaping software testing in ways that go beyond generating test boilerplate. The more interesting changes are in what gets tested, who finds the gaps, and how teams decide what 'enough coverage' means.
How AI changes the economics of software development
AI coding tools are compressing certain parts of the software development cycle. The parts they compress are not the expensive parts. Understanding where the real costs live changes how you should think about the productivity claims.