Insights, guides, and best practices for AI-powered solutions in enterprise environments.
66% of enterprises say real-time data is non-negotiable for trusted AI agents. The actual gap is governed, fresh, auditable knowledge infrastructure.
The Agent-Friendly Documentation Spec formalizes what many teams already know: agents fail on docs built for human readers. Here's what that means for enterprise knowledge.
RSAC 2026 saw Cisco, CrowdStrike, Microsoft, and Palo Alto converge on agent identity as a product layer. Here's what they built and what they missed.
The market is separating agent memory from generic RAG. Long-running agents need durable, policy-aware memory — and that creates a new enterprise infrastructure problem.
Public websites are being restructured for AI agents. For enterprise teams, the lesson is not about SEO: it is about what makes knowledge usable for agents.
Visa, Mastercard, and UQPAY are building payment controls for AI agents. Authenticated transactions don't fix the broken knowledge those agents reason from.
80% of Fortune 500 companies use AI agents. 1 in 3 are unsanctioned. Enterprise security is focused on agent identity. Nobody's talking about what those agents actually know.
Two federal rulings 17 days apart drew a bright line: consumer AI used independently is discoverable. The deciding factor isn't capability — it's what your vendor's privacy policy says when prosecutors ask.
The Pentagon's Anthropic ban is being covered as a vendor risk story. It's actually a knowledge continuity story — and every enterprise running AI should take note.
Newsom's executive order makes AI safeguards a procurement requirement. For RAG platforms and enterprise AI vendors, that means governed knowledge just became a selling requirement.
Compiled AI knowledge bases promise lower token load and better synthesis, but they create a new governance problem: stale abstractions that look authoritative.
Deutsche Bank’s new compliance AI assistant shows where enterprise AI is heading in banking: policy-grounded systems that live or die by the quality of the knowledge behind them.
DigitalOcean's Katanemo acquisition shows the agent cloud is shifting toward orchestration, observability, and safety. The harder problem is still trusted knowledge.
NVIDIA's GTC announcement with 17 enterprise adopters signals platform consolidation is real. The next bottleneck isn't the stack — it's the knowledge beneath it.
Agent ops is becoming a real engineering discipline. Microsoft and Cyara both shipped operational tooling for AI agents in March 2026. Here's what that means.
Microsoft paused the forced Copilot rollout the same day ThoughtSpot named the 'Context Gap.' These aren't separate stories. They're the same market reality.
Two benchmark reports published March 10 confirm the enterprise AI integration gap is real — and point to the same cause: the knowledge foundation is missing.
OpenAI just paid $119M for AI agent security. The SEC is auditing AI governance. But the most dangerous AI vulnerability — inaccurate knowledge — has no buyer yet.
The FTC publishes its AI policy statement tomorrow. If your enterprise AI system gives wrong answers from a stale knowledge base, you may have more than a UX problem.
Google's Gemma 4 removes the infrastructure barriers to local agentic AI. It doesn't remove the risk of agents acting on stale, contradictory, or ungoverned knowledge.
Access controls and model safety aren't the last line of defense. Enterprise AI now needs an evidence layer: source provenance, reconstructable context, and a defensible audit trail.
Model quality alone doesn't determine agent reliability. The harness — instructions, tools, permissions, retrieval, verification — is the real engineering problem.
At HIMSS26, federal officials admitted healthcare AI has 'few guardrails' while 1,300+ AI devices run in hospitals. Here's what that gap means in practice.
Insurers faced $107M in AI fines in Q1 2026. Every response focuses on model audits. Nobody's asking what happens when the documents the model reads aren't explainable.
The Delve controversy isn't just startup drama. It signals a buyer shift: compliance automation will be judged on whether every claim traces back to real, verified evidence.
The LiteLLM supply-chain compromise wasn't just a dependency hygiene failure. It revealed that agent tooling is turning local knowledge sprawl into enterprise security risk.
Oracle's 22+ Fusion Agentic Applications execute business decisions autonomously. The transactional layer is covered. The document knowledge layer isn't.
Different agents operating from different business definitions create silent failures at scale. Microsoft's Fabric IQ points to the semantic infrastructure fix.
Adecco's unlimited Agentforce deal targets €12B in AI-driven revenue across 60 countries. The knowledge layer feeding those agents is the risk nobody's writing about.
Claude computer use now lets AI agents act on your documents without you watching. The knowledge quality problem didn't just get worse — it changed registers entirely.
At RSAC 2026, the message is clear: the AI knowledge layer is the primary attack surface. Here's what that means for enterprise security.
Enterprise AI evaluation is shifting from model benchmarks to system stress tests. Here's what production-ready agent evals now require — and why knowledge quality is the variable most miss.