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L8 - Context Construction & Prompting

L8 covers system prompts, prompt templates, few-shot examples, context packing, instruction hierarchy, prompt evaluation, and runtime context assembly. It is where a task becomes a model-facing conversation or request.

L8Context Construction & Prompting
  1. Instructions
  2. Examples
  3. Context packing
  4. Prompt tests

What belongs here

L8 sits above inference and below retrieval, tool calls, and planning. It describes how the system shapes the immediate input to a model, including instructions, examples, retrieved snippets, tool schemas, and conversation state.

Representative projects

Project Why it might fit Adjacent layers
LangChain prompt templates Common abstraction for constructing model inputs from variables and templates. L8 prompting, L12 orchestration
LlamaIndex Data and context orchestration tooling that often constructs prompts from indexed knowledge. L8 context, L9 retrieval
DSPy Programming model for optimizing prompts and language model pipelines. L8 prompting, L12 planning
promptfoo Evaluation and testing workflows for prompts and model behavior. L8 prompting, L15 governance
Guidance Structured generation and prompting library for controlling model output. L8 prompting, L15 schema
Microsoft Prompt Flow Tooling for prompt and LLM workflow development and evaluation. L8 prompting, L12 orchestration
DollhouseMCP personas and skills Public Dollhouse Research examples where reusable personas, skills, and activation patterns shape model-facing context. L8 context, L16 product UX
Elemental Surveys Applied research workflow where framing, instructions, and context assembly are part of the visible product behavior. L8 context, L12 planning

Boundary questions

  • If retrieved content is assembled into a prompt, is the system doing L8 work, L9 work, or both?
  • Do tool schemas included in a prompt belong to L8 context or L10 tool invocation?
  • Should prompt testing be L8 quality assurance or L15 governance?

Signals to watch

  • Prompt construction shifting from hand-written templates to optimized programs.
  • More explicit instruction hierarchy and context provenance.
  • Evaluations becoming part of every prompt change.