Skip to content

Reading Group: Context Engineering for LLMs

Photo of Rob
Hosted By
Rob
Reading Group: Context Engineering for LLMs

Details

Reading Group: A Survey of Context Engineering for Large Language Models

Join us at our next meetup to discuss the paper "A Survey of Context Engineering for Large Language Models." This session will focus on understanding context engineering as a critical component in developing robust LLM applications.

The paper we will be discussing
"A Survey of Context Engineering for Large Language Models" https://arxiv.org/abs/2507.13334

Context engineering is the process of precisely populating an LLM's context window with relevant information for optimal performance. This involves integrating elements such as task descriptions, few-shot examples, retrieved data (RAG), multimodal inputs, tool definitions, and historical state. Effective context management is essential, as insufficient or irrelevant information can degrade LLM performance, while excessive context increases computational cost. This is a non-trivial aspect of LLM application development.

Context engineering is a specific, crucial part of a broader, emerging software layer designed to coordinate individual LLM calls within complete LLM applications. This layer extends far beyond simple "wrappers," encompassing problem decomposition, control flow, LLM dispatch, generation-verification, guardrails, security, and evaluation.
Please try to look at the paper before attending. This helps us have a more productive discussion as participants will have a shared foundational understanding.

Who is this meeting for?
This meetup is for individuals interested in Data Science and Machine Learning, particularly those involved in or curious about the architectural and engineering challenges of building LLM-powered applications.

The discussion will aim for an intermediate to advanced level. But we welcome attendees of all levels.

Discussion Format:
We will follow a reading group format, providing an opportunity for attendees to share their insights and ask questions. Participants are welcome to pass if they prefer to listen.

Meeting Schedule:

  • 6:00 PM - 6:30 PM: Arrive / Informal Networking
  • 6:30 PM - 6:35 PM: Introductions
  • 6:35 PM - 7:25 PM: Discussion
  • 7:25 PM - 7:30 PM: Nominate and vote for the next meeting's topic
  • 7:30 PM: Meeting Concludes

We look forward to seeing you there.

Photo of Data Science Discussion Auckland group
Data Science Discussion Auckland
See more events
Grid AKL - Tech Cafe
Ground Floor - 101 Pakenhan Street West, Wynyard Quarter · Auckland