AI tools for Forward Deployed Engineering — Vasuman Moza, Varick Agents
Varick treats enterprise agents as process-reengineering systems: capture how work really happens, encode that context, then automate only the steps whose risk permits it.
Varick’s forward-deployed team maps actual work, including exceptions and ownership, then redesigns it around AI. Its internal system has an **engagement agent**, a **workflow agent**, and a planned autonomous assistant backed by a company knowledge graph.
Builders should treat business context as product infrastructure. Capture process owners, edge cases, handoffs, and system identities before asking an agent to change workflows; explicitly divide work among autonomous, reviewed, and human-only steps.
Varick’s forward-deployed team maps actual work, including exceptions and ownership, then redesigns it around AI. Its internal system has an **engagement agent**, a **workflow agent**, and a planned autonomous assistant backed by a company knowledge graph. Builders should treat business context as product infrastructure. Capture process owners, edge cases, handoffs, and system identities before asking an agent to change workflows; explicitly divide work among autonomous, reviewed, and human-only steps. The autonomous stage is **still in development**, and the talk offers no independent evaluation of its graph traversal or workflow accuracy. Its broader claims about near-perfect execution and solved knowledge work are assertions, not demonstrated results.
This shifts forward-deployed agent work upstream from automating requests to mapping and redesigning the real process, including ownership, exceptions, handoffs, and identities. It reinforces business context as durable infrastructure and requires an explicit autonomy boundary for each step. However, the planned autonomous assistant and knowledge-graph traversal remain unvalidated, so the talk supports the workflow-design method more strongly than its broad execution claims.