@inproceedings{raptors2026-c047,
  title     = {{Beyond Stateless Prompts: Building Persistent, Context-Aware AI Agents}},
  author    = {Putta, Naga},
  booktitle = {Proceedings of the Raptors Conference},
  volume    = {1},
  year      = {2026},
  publisher = {Hackathon Raptors},
  address   = {London, United Kingdom},
  doi       = {10.68495/rc.2026.C047},
  url       = {https://doi.org/10.68495/rc.2026.C047},
  abstract  = {Most AI agents are stateless. Switch context or close the window and the agent forgets everything, which returns the person to the beginning and puts the cost of continuity back onto them. This paper sets out architectural patterns for building persistent, context-aware agents that maintain memory across task switches and update their capabilities dynamically without being re-prompted. The distinction it draws is between an agent that is given context each time and one that holds it, since only the second can be trusted with work that spans more than a single exchange. The patterns are demonstrated through an agent maintaining context across a real multi-tool workflow rather than in a single-turn example, which is where stateless designs usually appear adequate. Readers take away an implementable blueprint for moving an agent from a stateless, prompt-dependent tool to a persistent, production-ready assistant that retains what it is doing, described concretely enough to apply immediately.}
}