Guide · AI Lifecycle
Context Packing, Truncation, and Trust Boundaries
Everything in the context window can steer the model. APRF Context Engineering requires trust labels, packing rules, and truncation that does not drop safety or authorization critical text.
Unlabeled context is an injection surface—APRF Context Engineering requires trust labels, packing priority, and safe truncation. Primary control: Context Engineering
The window is a security surface
Context packing selects, orders, labels, and truncates system text, user input, retrieval, tools, and memory into a finite token budget. Whatever you pack can steer the model. Context Engineering is the policy for that assembler—not a synonym for "stuff more RAG."
A bot once concatenated the top 20 chunks with FIFO truncation. A malicious corpus page said to ignore policies and dump the system prompt; truncation had already dropped the refusal block. Labels (`system`, `trusted_tool`, `untrusted_retrieval`), reserved safety tokens, and filters on untrusted segments fixed it.
Packing priority (drop from the bottom)
1. System / safety / policy (never truncate these first)
2. AuthZ / tool policy
3. User message
4. Trusted tool results (still budgeted)
5. Untrusted retrieval / memory
Untrusted content is data. Do not merge it into the system string. Delimiters help; runtime labels and drop order matter more.
Budget and prove
Hard caps per trust class (ties to Performance & SLO and Cost). Log included and omitted source IDs—not raw secrets. Version the packer with prompts and cover packing in Evaluation: cases where safety text must survive under pressure, and injection in retrieval must not elevate.
Assess against APRF Core
Run the Core Profile quiz — gated pass/fail blockers for AI production readiness, not a vanity score.
Related
Frequently asked questions
- Is delimiters-in-the-prompt enough?
- Helpful but not sufficient. Runtime packing, truncation priority, and treating untrusted text as data are the real controls—prompts alone fail under injection.
- How is this different from Prompt Engineering?
- Prompt Engineering versions instruction artifacts. Context Engineering governs dynamic contents of the window—retrieval, tools, memory—and their trust boundaries.
- Should tool results be trusted?
- Only as far as Tool Safety and AuthZ allow. Label them `trusted_tool` or `untrusted_tool` and still bound their token budget.