Postgres internals, test data, and running AI agents against real databases.
A postgres backfill on a large table doubled its heap in range batches without VACUUM, while id % 10 batches at fillfactor 90 kept 96.1% of updates HOT.
Forty one-off deletes disappeared from pg_stat_statements while the same session read the schema. What the view merges, and what it never records at all.
In PgBouncer transaction mode, SET, temp tables and advisory locks stay on the backend and the next client reads them. The measured matrix of what leaks.
The Postgres role for AI agent sessions usually carries statement_timeout and a read-only default. Both are USERSET, so the session lifts them itself.
Setting session_replication_role to replica drops foreign keys and most triggers, leaving CHECK, NOT NULL, UNIQUE and RLS enforcing. The verified matrix.
A pg_dump data-only restore can break on a schema holding zero rows, and psql exits 0 while it happens. The verified failure map, with what each fix costs.
A Postgres sequence out of sync with its table breaks the first insert after a data load. Why it happens on serial and identity columns, and how to realign it.
Synthetic data vs real data has no single winner; the answer flips with the job. For application databases, Seedfast generates rows that fit the schema.
Training data for AI agents that run software is an environment, not a labeled dataset. Seedfast seeds its database with connected, realistic rows.
An AI agent empty database makes tests pass while the tables sit bare. Seedfast reads your Postgres schema and fills them with connected, realistic rows.
Generate realistic synthetic data from your database schema.Safe, coherent, and ready for local dev, demos, and CI.