2026 means stabilizing AI tools, not launching new ones
2026 isn't about new AI capabilities — it's about stabilizing the ones we already have. For product counsel, governance built on shifting tools is governance built on sand.
Law-following AI turns legal compliance from afterthought into architecture
The authors suggest treating AI agents as "legal actors" — entities that bear duties — without granting them legal personhood.
The real satisfying bottleneck in enterprise AI isn't the model
Contextual AI's Agent Composer makes the case that the real enterprise AI bottleneck isn't the model — it's context, auditability, and governance baked into the infrastructure from day one.
Smaller models aren't a compromise — they're a governance feature
Enterprise AI doesn't need models that can do everything. It needs models scoped to the problem. Constraint isn't a limitation — it's a governance feature.
The AI employee is here, and it comes with a management platform
Most companies are still debating whether to adopt AI agents. Reload is already building the HR platform to manage them. That's the gap between strategy decks and product roadmaps.
When agents forget, who's accountable?
Engineers call this context management. Lawyers should call it something else: selective deletion with no retention policy.
Why I rebuilt Karpathy's AI job exposure map
I rebuilt the project from scratch to understand what it actually measures, where it's useful, and where it breaks down.
Memory-driven AI agents create governance problems, not just engineering ones
AI agents with memory aren't just smarter — they're harder to govern. Each memory layer creates distinct privacy and retention obligations product counsel needs to address at the architecture stage.
