Cooking with Agents

The Exploration

What if cooking assistance wasn't a single chatbot, but a team of specialized agents working together? This prototype explores:

• •Recipe Agent: Finds and adapts recipes based on dietary needs and available ingredients
• •Technique Agent: Provides real-time cooking guidance and troubleshooting
• •Planning Agent: Manages timing, prep work, and multi-dish coordination
• •Shopping Agent: Generates smart grocery lists and suggests substitutions

Why This Matters

Multi-agent systems represent a shift from "one AI does everything" to "specialized AIs collaborate." Cooking is a perfect test case because it requires:

• •Domain expertise (techniques, flavor profiles, food science)
• •Real-time adaptation (substitutions, timing adjustments)
• •Coordination across tasks (prep while something bakes)
• •User context (skill level, dietary restrictions, available time)

What I'm Learning

• •Agent coordination is harder than agent capability
• •Clear handoffs between agents matter more than individual agent intelligence
• •Users don't care about the architecture—they care about the outcome
• •The best multi-agent systems feel like one coherent experience

Status

Working prototype exploring agent orchestration patterns and handoff mechanisms. Testing with home cooks to understand when multiple agents help vs. create confusion.