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 strengthens the process-first case for enterprise agents: map real ownership, exceptions, handoffs, and identities before selecting automation boundaries. Against the candidates, its workflow method is credible and reusable, but its autonomous assistant and graph-backed execution remain proposals rather than evidence; the practical takeaway is staged redesign with explicit human authority, not confidence in near-perfect end-to-end execution.