Step-by-step tutorials on building voice and chat AI agents using OpenAI Agents SDK, Realtime API, function calling, multi-agent orchestration, and production deployment patterns.
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Build type-safe AI agent APIs with Prisma ORM covering schema design for conversations and messages, client generation, relational queries, transactions, and migration workflows in TypeScript.
Learn how to store and analyze AI agent time-series data including token costs, latency, and throughput using TimescaleDB, partitioning, retention policies, and aggregation queries.
Implement full-text search for AI agent knowledge bases using PostgreSQL tsvector, trigram similarity, and GIN indexes with ranking, fuzzy matching, and hybrid search strategies.
Master database migration workflows for AI agent systems using Alembic and Prisma Migrate including data migrations, rollback strategies, zero-downtime deployments, and CI integration patterns.
Configure and optimize database connection pooling for AI agent applications comparing PgBouncer, pgpool-II, and application-level pools with monitoring strategies and troubleshooting guides.
Implement soft deletes, data retention policies, GDPR-compliant deletion, and conversation archival for AI agent systems with PostgreSQL patterns, automated cleanup, and audit trails.
Optimize database performance for AI agent systems with EXPLAIN ANALYZE, strategic indexing, query rewriting, materialized views, and caching patterns that reduce latency and database load.
Explore the tradeoffs between edge and cloud AI agent deployment, including latency benefits, privacy advantages, cost reduction strategies, and decision frameworks for choosing the right approach.
