Role transitions
Reimagine a role: from current role to target role.
A finance specialist may configure an invoice workflow. A developer may build a testing agent. An AI engineer may build or fine-tune a model for an agreed task. The starting point is the work the enterprise needs, then the capabilities, responsibilities and evidence required of the person doing it. An existing role can change, or a person can prepare for a new one.
Project Readiness connects those responsibilities to enterprise-specific simulations. Build on current capability, approved tools and your existing enablement. Define what people must produce and check, then choose the environment and assessment that help them demonstrate it.
Selected workflow: Cruise discovery and booking-related customer assistance
Use this context to discuss the transition. It is not an analysis or readiness decision.
Transition review
Current role → Forward Deployed Engineer
Works within the customer's workflow to connect a business problem to a working technical solution. Responsibilities can include stakeholder discovery, bounded building, testing, integration and operating handoff. Scope and overlap with adjacent engineering roles vary by employer.
This is a review to discuss, not a skills match, suitability decision or readiness assessment. It compares task wording, so treat the lists as a starting point for your role owner.
2. The target role: Forward Deployed Engineer
28 tasks captured from job descriptions and research, classified for review.
- AutomatePotential agent execution, subject to review8
- AugmentAI assists, a person decides10
- Human-onlyNeeds human judgment10
Classifications are proposals for review, not decisions about any one person or workflow.
Preparation follows the responsibilities you need to take on
Transforming work can deepen an existing role or create a new one. Start with the enterprise's actual workflow, the team's experience and a reviewable work product. Agree relevant projects, approved tools and assessment with the role owner. Functional teams can configure and build with suitable tools; technical teams bring the engineering depth the work requires.
Existing-role preparation
A developer working with Claude and Claude Code
Build on programming, API and terminal skills. Practise with domain projects: create reusable AI capabilities, connect tools and data, then use Claude Code to extend and review a codebase.
- Set up an approved environment and learn the selected model and tool.
- Build projects around real work, such as a customer-service application or a document-processing workflow.
- Check outputs, test exceptions and review generated changes and integration boundaries.
- Bring code, tests, review findings and a documented capstone together as assessment evidence.
Discuss Claude-based role preparation →New-role preparation
An enterprise engineer preparing for FDE responsibilities
Build on enterprise engineering experience and review the gaps. Technical practice and client judgment develop together as the engineer prepares to connect a business problem to a demonstrated solution.
- Bridge required programming skills, then build and evaluate retrieval and agent workflows.
- Practise client problem framing and choosing between AI, retrieval and agents.
- Defend architecture and integration choices, human controls, security and supportability.
- Verify a deployment in the practice environment and defend a capstone with its constraints and operating handoff.
Review FDE preparation and assessment →These examples describe practice and evidence to review. A completed project or assessment does not replace the role owner's readiness decision or approval for operating use.
Current role → target role → practice → readiness evidence
Illustrative transition paths, not automatic role matches, customer results or guarantees of qualification.
Software developer → AI Engineer
- Starting capability
- Software implementation, testing and debugging experience can be relevant starting capabilities.
- Target responsibilities and gaps
- Review the target role's model and tool integration, evaluation, data handling, output verification and operational handoff responsibilities.
- Practice and readiness evidence
- Practise a bounded AI implementation. Review source checks, tests, failures, implementation choices and the handoff against agreed target-role criteria.
Discuss transition to AI Engineer →Solutions or implementation engineer → Forward Deployed Engineer
- Starting capability
- Technical implementation and customer-facing delivery experience can be relevant starting capabilities.
- Target responsibilities and gaps
- Review stakeholder discovery, problem framing, domain constraints, bounded building and demonstration responsibilities for the FDE role.
- Practice and readiness evidence
- Practise discovery with a simulated stakeholder, agree a problem, build with the scenario's data and tools, then explain the result and its limits.
Discuss transition to Forward Deployed Engineer →Changed work within the same role
Illustrative transitions to discuss, not customer results or a prescribed redesign for your organization.
Software developer
- Current responsibilities
- Implement a requirement, test the change and hand it over for review.
- Changed responsibilities with AI
- Work with AI-generated code and tests, verify assumptions and dependencies, debug failures and explain the implementation to its reviewer.
- Practice and readiness evidence
- Review a plausible change that fails an important requirement. Demonstrate tests, corrections and a clear technical handoff.
Business analyst
- Current responsibilities
- Gather requirements, describe the process and agree changes with stakeholders.
- Changed responsibilities with AI
- Map the actual workflow, specify rules and exceptions, configure or help build an agent workflow with the appropriate technical support, then verify the proposed change with its owner.
- Practice and readiness evidence
- Produce a bounded workflow prototype, an agreed problem statement and checks for incomplete evidence, decision authority and handoffs.
From role transition to preparation
Define current and target roles
Bring the current role or job description and the target role. Review their workflows, responsibilities, decisions, systems and handoffs. Confirm the destination with the learner and accountable role owner.
Review transferable work and gaps
Compare existing capability with target responsibilities. Use Task Intelligence to examine tasks, what transfers, what must be learned and where people must verify, approve or handle exceptions.
Prepare for the transition
Agree a scenario problem with the role and workflow owners, then select practice for it: discovery conversations, realistic projects, output review, exception handling or technical handoffs. Build on existing enablement and approved tools; confirm access and licences for any additional practice environment.
Review readiness evidence
Agree observable assessment criteria and review the work produced, decisions, corrections and explanations. Human capability, agent behaviour and acceptance of the operating workflow require separate evidence and owners.
Choose practice once the target role needs are understood
Review Project Readiness products for the responsibilities you agreed: Simulations, hands-on practice and Skill Validation Assessments. The AI Bootcamp runs for 6–8 weeks with roles, scenarios, tools and assessment criteria agreed before delivery. Operating acceptance and business impact require the customer's review and evidence.
Shape projects around the enterprise conditions that matter: approved source records for invoice generation, CRM fields and outreach approval for sales, or the repository, fixtures and test interfaces for a QA agent. Simulations and evaluations run within that agreed context. Human readiness evidence, agent performance and acceptance of the shared workflow remain separate, with criteria and owners agreed for each.
Public role data and previews can inform your discussion. Customers save organization-specific plans in their signed-in workspace at nuvepro.ai.
Discuss a role transition →