Practical FDO guide
How a Forward-Deployed Operator builds an agentic research system
An operator works with the team to turn a recurring research question into a documented workflow with approved sources, focused agent tasks, and human review.
By AI Agentship · Published · Updated
Choose a question worth answering repeatedly
Start with work the firm already does: a market landscape, client opportunity brief, diligence question, or recurring performance explanation. Name the expert who will use the answer. Collect a few real examples, the current turnaround and review effort, and what an accepted result must contain. A single valued workflow creates a useful first milestone and keeps implementation scope visible.
The FDO sits with the team to learn the decisions behind the work: which sources are trusted, how conflicting figures are resolved, which claims need direct evidence, and when a reviewer must step in. Those choices become the research method. They cannot be inferred reliably from a folder of documents alone.
Design source access and an evidence trail
Inventory internal documents, structured data, and external sources for the first question. Record owners, freshness, permissions, and client boundaries. Connect only what the workflow needs, often with read-only access at first. The system should preserve a link or document reference, date, and relevant excerpt for material findings so a reviewer can follow the evidence.
Set rules for missing, stale, and contradictory sources. An agent should mark an unresolved point and ask for review instead of filling the gap with a plausible statement. The FDO tests these exceptions early because research credibility depends on how the system behaves when evidence is thin.
Give agents focused research jobs
Define the input question, source boundaries, expected evidence record, brief format, and stopping conditions. An agent can search approved sources, extract relevant facts, compare competing evidence, and draft a brief. A human remains responsible for interpreting the evidence and approving consequential conclusions.
Use the simplest architecture that works. Predictable questions may need a repeatable sequence of retrieval, extraction, drafting, and review. Open-ended questions spanning independent source sets may benefit from a lead researcher coordinating focused search agents. Multi-agent research can improve breadth, but it increases cost and coordination work; the FDO chooses it only when the task justifies that complexity.
Test the brief with the experts who will use it
Run representative questions, including hard cases with missing data or conflicting sources. Check whether each material claim has suitable evidence, whether the brief answers the question, what uncertainty remains, and how much expert correction it needs. Save the failures and corrections as evaluation cases before changing instructions or tools.
Measure elapsed time from agreed kickoff to the first research output accepted by its named reviewer. Record actual use separately. Track preparation and review effort, quality, and total delivery cost; acceptance alone does not prove business impact.
Make the system usable after the first brief
Document the source list, research steps, agent permissions, review rules, and exception path. Train the people who will request, review, and maintain research. Decide who updates sources and methods when the firm changes how it works.
Expand to new questions only after the first workflow works repeatedly. Reuse the evidence and review structure while adjusting the source set, method, and acceptance checks for each new topic. The FDO helps the team own the system; any continuing operator role is agreed separately.
Implementation checklist
- Pick one recurring question and name its expert owner.
- Capture current turnaround, review effort, and acceptance standard.
- List approved sources, owners, freshness, and access limits.
- Define agent tasks, evidence records, brief format, and exception rules.
- Test real questions and hard cases with expert reviewers.
- Measure kickoff to reviewer acceptance, then track actual use separately.
- Document operation, train the team, and retest changes before expansion.