context engineering
19 Articles
AI Tool Output Verification: Did It Establish a Fact?
A 2026 guide to AI tool output verification: distinguish successful calls from supported facts, classify incomplete observations, and evaluate claims with independent fixtures and provenance.
Negation in Information Retrieval: Recall vs. Violations
A 2026 research report on negation in information retrieval: NevIR and ExcluIR evidence, recall versus exclusion metrics, and a reproducible collection-level release protocol for retrievers and rerankers.
Context Engineering for AI Agents: A Practical Guide
What context engineering is, how it differs from prompt engineering, and how to budget an agent's context by origin, provenance and keep/compress/drop.
AI Agent Handoff Testing: Did the Evidence Reach the Agent?
A 2026 research report on AI agent handoff testing: source-span obligations, verified fault injection, recipient-visible evidence, paired scoring and independent recovery before accepting downstream claims.
RAG citation provenance: did generated context become evidence?
A 2026 evaluation report on RAG citation provenance: distinguish HyDE hypotheses and generated prefixes from original evidence, build paired exposure tests, and validate retained source spans.
Data Provenance Privacy: A Recipient Disclosure Test
A 2026 guide to data provenance privacy: evaluate recipient permissions, redact citation metadata, count exposed graph paths, and decide when evidence is too limited to justify sharing a value.
RAG chunking sensitivity: can boundaries reverse answers?
A 2026 research report on RAG chunking sensitivity, with a paired boundary-phase protocol, complete-support annotations, fixed-token comparisons and evidence-based release criteria.
Entity Resolution Human Review: Which Decisions Need It?
A 2026 guide to entity resolution human review: accept, review, or hold unresolved. Includes a decision card, fixed-capacity harm calculations, reviewer disagreement, and audit uncertainty.
AI Agent Memory Deletion Verification: Counterfactual Tests
A 2026 protocol for verifying AI agent memory deletion with never-exposed controls, multi-channel disclosure probes, behavioral residuals, retained utility and explicit evidence boundaries.
Permission-aware RAG evaluation: Can you defend the answer?
A 2026 evaluation protocol for reader-eligible RAG evidence, with matched permission cases, claim-level provenance cards, and separate utility, disclosure, and citation-support measurements.
Knowledge graph identifier versioning after corrections
A 2026 guide to knowledge graph identifier versioning: stable referents, correction responses, retirement and custody transfer, with a lifecycle matrix, historical replay tests and a proposed registry schedule.
How to evaluate data sources for a knowledge graph
A 2026 guide to knowledge graph source admission: permission, provenance, versioning, sampled coverage and freshness, with an evidence card and accept, defer or reject decisions tied to a named question.
Long context LLM robustness: Does evidence position matter?
A 2026 research report on long context LLM robustness: evidence-position tests, separate answer and citation verdicts, frozen source versions, and paired bootstrap uncertainty for context engineers.
OWL vs SHACL: Entailment or Constraint? A Test Card
OWL vs SHACL in 2026: classify requirements by entailment or graph acceptance, test missing and inconsistent values, and preserve a reproducible packet with explicit inference settings and expected reports.
Multi-Hop RAG Citation Completeness: An Evidence-Set Test
A 2026 evidence-set test for multi-hop RAG citation completeness: distinguish answer correctness, joint support and missing hops, preserve source versions, and audit alternative evidence routes.
SKOS Concept vs OWL Class: A Modeling Decision Test
A 2026 modeling test for SKOS concepts versus OWL classes, covering hierarchy semantics, punning, RDF fixtures, validation obligations and migration boundaries for context engineers.
RAG data poisoning: can poisoned sources become facts?
A 2026 integrity protocol for RAG data poisoning: versioned source fixtures, separate retrieval and citation scores, paired controls, confidence intervals, and correction replay. No executed enterprise test is claimed.
How to Validate Knowledge Graph Embedding Predictions
A 2026 protocol for validating knowledge graph embedding predictions against original source spans, identity and time boundaries, then measuring supported-value precision and downstream answer support.
LLM Context Compression Evidence Loss: An Acceptance Test
A 2026 guide to testing LLM context compression for evidence loss, with paired source bundles, exact-span scoring, citation-grounding data, and release rules for defensible answers.