Software development is shifting from a slow, linear process to a rapid, evolutionary one driven by AI agents. Instead of building a single application over time, developers and agents now generate, test, and iterate on multiple versions in parallelโaccelerating experimentation at an unprecedented pace.
This shift is dramatically increasing the volume of applications being created, while reducing the cost of building each one. As a result, databases need to support highly dynamic, short-lived workloads that can scale instantly when needed, without incurring constant infrastructure costs.
Lakebase is designed for this new model. It enables instant branching for experimentation, serverless compute that scales to zero when idle, and seamless growth from small prototypes to production-scale systemsโall without reconfiguration.
It also embraces open ecosystems by building on Postgres and storing data in open formats, allowing AI agents and external tools to interact with data more effectively without being constrained by proprietary systems.
As agentic development becomes the default, databases must prioritize speed, cost-efficiency, and openness. Lakebase represents this shiftโbuilt to support continuous experimentation and the unpredictable growth patterns of AI-driven applications.
