AI-agentsagentic-AIbusiness-automationAI-ROIAI-implementationmulti-agent-systemsRAGMCPenterprise-AIAI-governance
AITeams frequently ask "should we fine-tune or use RAG?" as if it's binary. In production, the strongest systems use both: RAG for dynamic factual grounding, and light fine-tuning (or just careful prompting) for output style, tone, and domain-specific reasoning patterns. Don't fine-tune to teach the model facts — that's what retrieval is for.
AIThe Shift to Cloud 3.0: Architecting Low-Latency Apps With On-Device AI :root { --sp: 0.28s; } [data-theme="dark"]…
AIThe most effective Manager Agent implementations share four design principles: (1) Explicit capability registry — the manager knows exactly what each worker agent can and can't do, and this knowledge is structured data, not emergent from a system prompt. (2) State-based rather than event-based coordination — the manager tracks the current state of each agent and the overall goal rather than responding to events as they arrive.