Agent platform (Part 1): How we help Grab build and run AI agents at scale

This post details the initial architecture of Grab's AI support bot, which served as the precursor to LLM-Kit. It describes the reasoning plane (single-agent loop) and the tool plane (integrating Glean, Kibana, GitLab, Slack). It also outlines the key pain points encountered during scaling: lack of robust evaluation strategies, the need for fast model and provider switching, the critical importance of observability, and the significant effort required for production plumbing (auth, secrets, config, etc.). These pain points directly led to the development of the LLM-Kit framework, which aims to standardize these surrounding components.