The Everything Feed - All Packet Pushers Pods HN790: From Rule-Based to Goal-Based: Rethinking Autonomous AI Operations (Sponsored)
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Aug 1, 2025 Omar Sultan, Cisco's Director for Product Management of Automation and AI, and Javier Antich, the Chief Mad Scientist for AI at Cisco, dive into the revolutionary shifts in network operations driven by AI. They explore the transition from rule-based systems to goal-based autonomy, enhancing decision-making and adaptability. The discussion covers the necessity of knowledge graphs for AI coherence, security risks tied to AI autonomy, and practical strategies for adopting agentic AI within organizations. Their insights pave the way for a future where AI and human engineers can thrive together.
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Rule-Based vs. Goal-Based Systems
- Rule-based systems define how to solve problems with explicit programming.
- Goal-based autonomy enables systems to self-adapt and find how to achieve goals without fixed rules.
Agents Translate Goals Dynamically
- Goal-based systems dynamically translate intents to execution without predefined rules.
- LLM-powered agents can devise the "how" to meet user goals beyond static automation.
AI Enables Proactive Network Management
- Agentic AI handles novel network situations by mapping high-level goals to configurations dynamically.
- This replaces reactive, rule-based configs with proactive, intent-driven network management.
