Key Point: A new guide shows how to develop AI agents with the Agent Development Kit (ADK) that run reliably over weeks. Instead of stateless chatbots, these agents use structured persistent storage to continuously work on multi-step processes like hiring – without losing context.
Most agent tutorials end with stateless chatbots that lose all their memory on every restart. Real business processes take weeks or days. Learn how to build reliable AI agents with the Agent Development Kit that maintain context over extended periods.
Most agent tutorials present stateless chatbots – conversational loops that lose all information on restart. In practice, enterprise workflows require far more robust solutions.
Realistic business processes span extended timeframes: onboarding new employees takes two weeks, invoice disputes remain unresolved for days while waiting for manufacturer inquiries, sales campaigns encompass numerous touchpoints across an entire month. These processes are largely defined by “idle time” – extended periods when the agent is inactive and waiting for a signature, shipping confirmation, or approval.
A stateless chatbot would have no chance under these conditions. A new tutorial demonstrates how to use the Agent Development Kit (ADK) to build a reliable hiring coordinator. This agent runs flawlessly over weeks, orchestrating the entire process: it sends the welcome package, waits for days while the new hire completes paperwork, hands off IT provisioning to a specialized sub-agent, pauses again until hardware arrives, and then creates a fully personalized first-day agenda – without losing a single context point.
The process reveals three core architectural differences between production agents and simple demo chatbots: use structured, persistent storage schemas instead of loading raw JSON data into a vector database. This forms the foundation for agents that truly function over time.