# Technical guides built for AI

Benchmarks, implementation details, and reproducible pipelines for building with Deeplake.

## [Spin up Postgres in a second: How We Built Serverless PG for Agents.](https://deeplake.ai/blog/serverless-pg)

We built a serverless, PostgreSQL-compatible database. Not a modified PostgreSQL deployment. PostgreSQL provides the interface. Deeplake provides the storage engine. DuckDB provides the query execution.

**Author:** Sasun Hambardzumyan  
**Tags:** PostgreSQL, Serverless, AI Agents, Deep Lake, DuckDB

## [Your Agents Are Drowning in Quicksand. Give Their Data a Sandbox.](https://deeplake.ai/blog/agent-sandbox)

Databases were built for applications. Deeplake is built for agents. A sandboxed, serverless Postgres instance that spins up with every agent, scales with the swarm, and dies when the job is done.

**Author:** Davit Buniatyan  
**Tags:** AI Agents, Deep Lake, Databases, Serverless, Multimodal

## [Software Factory Ran Autonomously for 15h, 2x Speed Up on TPC-H, ASAN-verified, Cost $160](https://deeplake.ai/blog/coding-agent-15h)

An autonomous agentic workflow achieved a 2x speedup on TPC-H benchmarks by optimizing a large C++ codebase over 15 hours for just $160.

**Author:** Davit Buniatyan  
**Tags:** AI Agents, Performance Optimization, C++, Deep Lake