Get ahead of the skill library problem now
What compliance teams haven't figured out yet is that they own this problem.
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.
Six data shifts that will shape enterprise AI in 2026
Six data shifts are reshaping enterprise AI in 2026 — from RAG's evolution to contextual memory becoming table stakes. Product counsel need to be in these infrastructure conversations now.
Context beats model: the AI governance shift product counsel is missing
Better context beats a better model — which means AI risk governance needs to shift from the model layer to the retrieval layer. That's where defensibility lives now.
LLMs create a new blind spot in observability
LLMs break traditional observability — and that creates a compliance gap most governance teams haven't addressed yet. If you can't trace the full AI pipeline, you can't audit it.
AI reasoning explanations fail four times in five: what to verify before shipping
The trajectory is encouraging — the most capable models performed best. But 20 percent is not a foundation for compliance frameworks.
