Uploaded July 2026 | Updated September 2026, 3 weeks ago
A customer spent five million dollars and five years migrating to SAP, and has zero appetite to rip anything out again. That constraint is the whole design at Varick Agents: instead of asking an enterprise to migrate, you drop forward deployed agents on top of the systems they already run. Vasuman Moza's version of the role maps how a department actually works today, the reconciliations between a purchase order and an invoice, the handoffs nobody documented, and then automates those processes end to end. It answers the stat everyone cites, that most AI projects never reach production, by starting from the customer's real workflow instead of a generic tool.
Making one forward deployed engineer that productive takes tooling of its own. Varick builds a spec from the raw material of an engagement, the granola notes and Slack threads, then lets the engineer shape the workflow with Claude or Codex against a single source of truth that can just live in Postgres. The harder problem is context: frontier models are surprisingly bad at traversing a messy enterprise and knowing that person A and person B are the same entity, so Varick post trains its own models to extract the right context and strip the redundancy, and only then does the agent run autonomously. Every engagement starts by finding the bottleneck and grows out from there.
Speaker info:
- https://x.com/vasuman
- linkedin.com/in/vasumanmoza
Timestamps:
0:00 - Introduction: forward deployed agents
1:55 - The question: what can an agent actually do?
3:27 - What a forward deployed agent is
4:44 - Automating a department end to end
6:14 - Why enterprises need deployed engineers, no migrations
8:30 - Hiring the top 1 percent
10:51 - The platform and department wide ROI
11:53 - Demo: tools for forward deployed engineers
13:07 - Turning notes into a workflow spec
14:22 - Engineering workflows with a source of truth
16:53 - Post training models to extract context
18:37 - Where this leaves us
A customer spent five million dollars and five years migrating to SAP, and has zero appetite to rip anything out again. That constraint is the whole design at Varick Agents: instead of asking an enterprise to migrate, you drop forward deployed agents on top of the systems they already run. Vasuman Moza's version of the role maps how a department actually works today, the reconciliations between a purchase order and an invoice, the handoffs nobody documented, and then automates those processes end to end. It answers the stat everyone cites, that most AI projects never reach production, by starting from the customer's real workflow instead of a generic tool.
Making one forward deployed engineer that productive takes tooling of its own. Varick builds a spec from the raw material of an engagement, the granola notes and Slack threads, then lets the engineer shape the workflow with Claude or Codex against a single source of truth that can just live in Postgres. The harder problem is context: frontier models are surprisingly bad at traversing a messy enterprise and knowing that person A and person B are the same entity, so Varick post trains its own models to extract the right context and strip the redundancy, and only then does the agent run autonomously. Every engagement starts by finding the bottleneck and grows out from there.
Speaker info:
- https://x.com/vasuman
- linkedin.com/in/vasumanmoza
Timestamps:
0:00 - Introduction: forward deployed agents
1:55 - The question: what can an agent actually do?
3:27 - What a forward deployed agent is
4:44 - Automating a department end to end
6:14 - Why enterprises need deployed engineers, no migrations
8:30 - Hiring the top 1 percent
10:51 - The platform and department wide ROI
11:53 - Demo: tools for forward deployed engineers
13:07 - Turning notes into a workflow spec
14:22 - Engineering workflows with a source of truth
16:53 - Post training models to extract context
18:37 - Where this leaves us
