Forward-deployed engineering brings delivery into real work: understand the judgments, connect methods and tools, evaluate on real tasks, and retain what works.
A real task → A working method → A reusable capability packIterate on evidence, not a mechanical checklist
BEFORE BUILDING / DEFINE THE GOAL
Turn “we want AI” into work you can evaluate.
Choose a primary problem in time, errors, waiting or service quality. A goal brief should identify who uses the result, what should improve and the evidence needed to decide.
TEACHING EXAMPLE / WEEKLY REPORT ASSISTANCE
Who uses it, and when
An operations owner reviews regional exceptions each week and decides which issues need follow-up.
What the first pilot does
Summarize approved reporting inputs, check key figures and create a sourced draft for review. No automatic system changes or customer messages.
How the work is done today
Record retrieval, preparation, review and rework time across existing tasks. Retain error examples to establish a baseline.
What improvement means
Use the baseline to agree time, accuracy, source coverage and rework targets. Set thresholds, an observation period, reviewers and stop conditions before the pilot.
This is a goal-setting example, not a completed client engagement or a promised improvement rate. Resolve missing inputs, measures or ownership, or narrow the scope.
Assess the system, adoption and business outcomes separately.
A successful demo is a starting point. System readiness, adoption and business improvement need separate evidence, pass criteria, ownership and responses when they fail.
01 / A usable, controlled system
Check facts, sources and actions on normal, edge and failure tasks, including held-out examples. Test permissions, timeouts, duplicate requests, takeover and rollback.
Evidence: review examples, test and runtime records, recovery drills and operating guidance.
02 / Adoption in real work
Have users complete agreed tasks. Record adoption, completed actions and rework. After handoff, the team should know how to operate the workflow and where to get help.
Evidence: usage, adoption and rejection records, user feedback and handoff confirmation.
03 / Better business outcomes
During an agreed observation period, compare time including review, errors, rework and tool costs, then check the agreed outcome measures. Explain concurrent changes in processes, people or markets.
Evidence: baseline and pilot comparisons, user feedback and the owner’s conclusion.
If a gate is missed, narrow the scope, retain human review, retest or stop. Recheck critical tasks when models or data change.
These are responsibilities, not mandatory new job titles. One person may cover several roles, but each decision needs an owner. Agree participation and time commitments during scoping.
Business owner
Set priorities and available resources, resolve scope tradeoffs and decide whether results justify continuing.
Bring: the task, current process, decision makers and constraints.
Users and domain experts
Demonstrate real work, explain exceptions, review samples and record errors, rework and adoption obstacles.
Bring: typical inputs, good and bad examples, rules and feedback.
Data, IT and relevant control owners
Confirm permitted data, interfaces, access and approval points; review technical readiness before release.
Bring: authorization, system limits, integration and release requirements.
Operations and maintenance owner
Join handoff and recovery practice; own issues, versions and regular checks, with a route to engineering support.
Bring: maintenance arrangements, escalation contacts and improvement priorities.
The FDE connects requirements, implementation and evaluation evidence and makes limits explicit. Agree business decisions, data authorization and release ownership together before work begins.
WHAT FIELDWORK TEACHES US
Where the hard work happens is where the difference shows.
01 / FIELDNOTE
Align the meaning first
Matching names may hide different entities. Cumulative data may not be additive. Resolve identity, grain, time and definitions before automating analysis.
Retain: definition cards and test cases02 / FIELDNOTE
Unpack “looks promising”
High potential is not high confidence. Retain evidence, disagreement and unknowns so the business knows what to pursue and what to verify.
Retain: judgment rules and an evidence index03 / FIELDNOTE
Evaluate the complete job
Generation does not prove sending, adoption or resolution. Include human corrections, waiting, tool costs and actual use.
Retain: comparisons and improvements
THE COMPOUNDING OUTPUT
Solve the task now. Keep the method for next time.
01 Business outputs
Briefs, shortlists, drafts, analysis and options
02 Method assets
Skills, templates, counterexamples and test cases
03 Working capability
Role Agents, tool configurations and entry points
04 Maintenance
Sources, dependencies, versions and ownership
Manage shared methods separately from client-specific data, configuration and commercial information. Reuse does not mean taking or publishing client material.
START WITH ONE REAL PROBLEM
Bring a real problem. Make the first step concrete.
You do not need a complete AI strategy. Start with a recurring problem, one existing example and someone who will actually use the result.