01
Boundary brief
Defines workflow, data, access, runtime, and handoff limits before build work begins.
Engagement Patterns
How FDE collaboration works.
Random Walk works directly with customer teams to define the boundary, build the first working private AI system, keep evidence close, and leave a clear handoff path.
direct collaboration / boundary brief / first working system / evidence pack / operator handoff
02
First working system
Lands a scoped private AI path inside the customer environment.
03
Evidence pack
Keeps examples, run notes, known limits, and review material visible.
04
Operator handoff
Leaves activation, rollback, ownership, and maintenance assumptions clear.
05
Follow-up scope
Separates future changes from the first delivery and review pass.
Collaboration
Direct technical collaboration
The work happens close to the customer team that understands the workflow and will operate the system.
- Engineer-to-customer communication
- Workflow details discussed directly
- Implementation decisions kept visible
- Delivery shaped by the real environment
Scope
Scope the boundary
Every engagement starts by defining where the system can run, what it can touch, and who can operate it.
- Customer workflow and target behavior
- Data movement and access limits
- Runtime and resource assumptions
- First milestone and review owners
Build
Build the first working system
The first delivery is a scoped implementation path, not a detached recommendation.
- Private runtime or deployment path
- Data, model, or adapter packaging
- Environment-specific constraints
- Customer review during implementation
Evidence
Review evidence
Evidence stays close to the system so behavior, limits, and decisions can be inspected before handoff.
- Task examples and review cases
- Run notes or configuration summaries
- Known limits and weak cases
- Accepted and unresolved items
Handoff
Make handoff understandable
Delivery includes the operating assumptions needed for the customer team to understand the system after first launch.
- Activation notes
- Rollback assumptions
- Operator actions and admin surfaces
- Ownership and maintenance expectations
Mode
Remote and on-site collaboration
Support mode depends on environment access, implementation speed, and the customer team's operating needs.
- Remote scoping and review
- On-site support when useful
- Direct access to technical context
- Delivery mode scoped by project
Patterns
Engagement patterns
Typical projects are scoped around a real workflow, a private environment, and a concrete first system.
- Private AI adaptation sprint
- Local runtime setup and handoff
- Data package and evaluation pass
- Deployment boundary review
Boundaries
What this is not
This collaboration model is direct implementation support for private AI systems, not a detached business exercise.
- Not generic AI advice
- Not rented engineering capacity
- Not ticket-based delivery work
- Not hands-off SaaS onboarding
Ledger
Engagement ledger
A good engagement leaves a compact record of scope, build decisions, evidence, handoff, and next steps.
- Boundary definition
- Build scope
- Evidence material
- Follow-up decision
Boundary check
Work with the team that will operate it.
Random Walk fits projects where a private AI system must be scoped, built, reviewed, and handed over with technical clarity.
Bring the workflow, target environment, boundary constraints, review needs, and handoff expectations.
System signals
- You have a real workflow and customer-controlled environment constraints.
- You need direct technical implementation support.
- You want evidence and handoff, not only advice.
Boundary limits
- You only need general AI positioning.
- You want temporary ticket execution.
- You expect a fully hands-off hosted product.