Spec-driven development emerges as answer to AI coding complexity
This approach turns AI from a code generator into a more reliable development partner—one that builds what you actually need.
AI agents surge in consumer-facing industries as adoption jumps 119%
Consumer industries lead 119% surge in AI agents as retail, travel see 128-133% monthly growth in automation—changing competitive landscape for product teams
Travel's agentic AI moment is arriving slower than the headlines suggest
Over 90% of travelers trust AI-generated travel information, but almost none want the AI to act on that information independently.
Non-human identities are multiplying faster than security teams can track them
Non-human identities outnumber humans 80:1 in many orgs, but most teams lack visibility into AI agents' permissions, ownership, or lifecycle management—creating major governance gaps.
Your AI Is a Black Box- Here Are 3 Keys to Unlock It
By demanding useful explanations, installing human failsafes, and requiring clear "nutrition labels" for our AI, we can begin to pry open the black box.
From testing to reviewing: evaluating AI agents that run 30-step workflows
AI agents fail in production not because of bad architecture, but because we test them like traditional software. Complex 30-step workflows can't be tested—they must be reviewed like human work. This shift changes everything for legal and product teams.
Microsoft and NYU tested what happens when AI becomes employee #1
The research shows we're moving from AI-as-tool to AI-as-colleague, which means rethinking how we structure accountability and human oversight.
Operationalizing NIST AI Risk Model Framework: Beyond Accuracy and Checklists
The NIST framework provides the map, but fostering a true culture of responsibility is the journey.
