What a model knows at the moment it answers: prompt and context engineering, retrieval and evidence grounding, ontologies and knowledge graphs, structured output, memory and persistent state, and the caching and trust rules that keep answers correct and affordable.
Context, retrieval and memory · 5 min read · with a concept loop
Valid JSON from an AI system is not proof the answer is true. The validity ladder separates format, type, domain and evidence checks before anything acts.
structured outputstool use and integrationreliabilityretrieval and grounding
Context, retrieval and memory · 5 min read · with a concept loop
Semantic caching only pays off when authority, version, freshness and equivalence checks all pass, not when a similarity score alone approves a hit.
cachingprivacy and access controlretrieval and groundingcost and unit economics
Context, retrieval and memory · 5 min read · with a concept loop
Retrieval finds relevant material. It does not prove an answer is supported. The evidence chain shows the four checks that separate the two.
retrieval and groundingcontext engineeringdata provenanceprompt injection
Context, retrieval and memory · 5 min read · with a concept loop
Automatic prompt optimization pays off only when you measure headroom first, isolate the prompt's parts, and confirm gains on a holdout.
prompt designcontext engineeringevaluation and benchmarkscost and unit economics
Context, retrieval and memory · 5 min read · with a concept loop
Knowledge graphs and ontologies improve auditability far more reliably than they improve correctness, so test the two separately before you fund one.
retrieval and groundingdata provenanceenterprise architectureaudit trails
Context, retrieval and memory · 5 min read · with a concept loop
Persistent AI memory needs governed admission, authority, correction and deletion, not just bigger storage. The memory ledger framework and what to fund.
memory and stateprivacy and access controlsecurityprompt injection
Context, retrieval and memory · 5 min read · with a concept loop
AI systems should route information through a gate that checks deletion and tenant isolation first, then let cost decide between context, memory and weights.
memory and statecontext engineeringlong contextprivacy and access control
Context, retrieval and memory · 5 min read · with a concept loop
AI agents need typed claims, four time clocks and a commit gate that separates belief from fact. The evidence core framework and what to build first.
memory and stateretrieval and groundingdata provenanceuncertainty and calibration
Context, retrieval and memory · 5 min read · with a concept loop
Context engineering decides what a model sees before it answers. The context compiler framework, why bigger windows are not the fix, and what to fund.
context engineeringretrieval and groundinglong contextprompt design
Other topics
