CASE STUDIES·REPRODUCIBLE WALKTHROUGHS

REAL QUESTIONS.
RUNNABLE ANSWERS.

WordPress core — ~619k lines — security-audited by an AI agent for ~26,000 tokens: that is the one study measured on real code. The other two are functional proofs on small synthetic corpora — they show the shape works, not how fast. Three engineering questions, answered end to end with published code and recorded output. The questions came from calltree.ai and daily.dev; neither is a customer. Every number traces to a walkthrough in the repo.

01
WORDPRESS
SECURITY
AUDIT.

WordPress core is ~619k lines — ~26× a 200k-token context window. An agent indexed it as a queryable code graph and read only what queries surfaced. Yellow is the whole audit's token bill; blue is what it costs just to load the code once.

~26K TOKENS INSTEAD OF ~5.2M
SECURITY ENGINEERS · AI-AGENT BUILDERS · PLATFORM TEAMS
FULL CASE STUDY →
MEASURED · WORDPRESS CORE · 1,492 FILES / ~619K LINES
XERJ-ASSISTED AUDIT READ EVERY FILE
Tokens, entire audit ~26,000 ~5,200,000 ~199×

TOKEN ACCOUNTING, NOT A LATENCY BENCHMARK · SOURCES IN docs/case-studies/wordpress-security-audit →

02
SEMANTIC
ANALYTICS IN
ONE REQUEST.

"Of calls about wifi issues, how many are 2.4GHz vs 5GHz, and what are the key issues?" — asked by calltree.ai. Half retrieval, half analytics: normally two stores and an ETL. One XERJ POST /_search returns the slice, the breakdown, the metrics, and the evidence.

1 REQUEST · 1 STORE — WAS 2 + ETL
AI-OVER-SUPPORT TEAMS · DATA PLATFORM ENGINEERS
FULL CASE STUDY →
GENERATED CORPUS · NOT A BENCHMARK · 130 SYNTHETIC CONVERSATIONS
XERJ SPLIT STACK
Requests per question 1 2
Stores to operate 1 2
ONE RESPONSE CARRIES
01SEMANTIC SLICEk=80 nearest conversations
02BREAKDOWNterms buckets: band, key issues
03METRICScsat p50 · handle-time avg, per bucket
04EVIDENCE3 example hits → LLM narrative

SPLIT STACK = OLAP + VECTOR STORE + ETL, OR TWO ROUND TRIPS IN ONE ENGINE · AGGS-BEARING kNN RUNS THE EXACT SCAN, NO SPEED CLAIM · BUCKETS COUNT THE RETRIEVED SLICE · k=80 IS THE REQUEST PARAMETER, NOT A MATCH COUNT · SOURCES IN docs/case-studies/calltree-analytics →

03
POSTGRES CDC +
HYBRID SEARCH.

daily.dev's founder asked: can XERJ replicate automatically from Postgres? A logical-replication slot streams every INSERT, UPDATE, and DELETE into XERJ — no reindex jobs — and one hybrid query fuses BM25 + vector rankings server-side, replacing the tsvector + pgvector two-query app merge.

3/3 MUTATION TYPES REPLICATED · 0 CHANGES LOST
POSTGRES TEAMS · SEARCH ENGINEERS · PLATFORM TEAMS
FULL CASE STUDY →
FUNCTIONAL PROOF·SYNTHETIC 8-ROW CORPUS·NOT A BENCHMARK
XERJ POSTGRES TSVECTOR + PGVECTOR
Queries per hybrid search 1 fused query 2 queries + app-side merge
App-side score merges 0 · RRF fuses server-side 1 · across two score scales

ARCHITECTURAL COUNT FROM THE RECORDED RUN · SOURCES IN docs/case-studies/daily-dev-postgres-cdc →

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