SpellVault’s evolution: Beyond LLM apps, towards the agentic future

This post details the evolution of Grab's SpellVault platform from a no-code LLM app builder to an agentic framework. Key technical contributions include: 1. Transitioning from a legacy executor system to a graph-based executor supporting branching, looping, and modularity, enabling ReAct agent behaviors. 2. Decoupling executor and prompt engineering components to allow for multiple execution pathways, including generic Deep Research and sophisticated internal workflows. 3. Consolidating scattered capabilities (Python execution, internal repository search) into "Native Tools" and rebranding user-created plugins as "Community Built Tools" under a unified "Tools" abstraction. This enables AI agents to dynamically invoke these tools for reasoning and action, shifting the platform towards more natural, discoverable, and extensible agentic behavior.
More from the AI Agent Framework trail
- Grab Bench: Evaluating AI on Grab-shaped production work
- Palana (Part 2): Architecting isolation, identity, and auditability for AI agents
- Palana (Part 1): Why Grab built a secure platform for autonomous AI Agents
- Agent platform (Part 1): How we help Grab build and run AI agents at scale
- From firefighting to building: How AI agents restored our team’s core productivity