The Situation

With the platform model defined and the design tenets established, the next step was mapping how a developer actually moves through the experience. This was completed after conducting cross-functional workshops, developer interviews, competitive benchmarking, and defining jobs-to-be-done across the lifecycle.

The agent-forward journey spans three phases (building, deploying, and managing), each supported by a distinct set of agents scoped to the jobs a developer needs to accomplish at that stage. The diagram also surfaces the handoffs and gaps between phases: where context transfers cleanly, and where the current system potentially falls short.

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My Outcomes

Agent-Assisted Developer Journey Map

This diagram organizes the full developer lifecycle into phases that contain agents to assist in job completion. Each agent is framed as a job-to-be-done, expressed in the developers’ own words.

Integration Experience Definition

Integration is the first step of the developer journey. Based on the integration path, the agent performs different tasks, and developers have different decisions and tradeoffs to consider.

• API Integration: “I have a service. I want Alexa+ to call it.” The developer submits an API URL and supporting assets. The agent detects the service, routes capabilities, and generates the integration.
• MCP (Model Context Protocol): “I have capabilities. I want Alexa+ to discover them.” The developer submits a tool manifest. The agent reads it, infers what the tools do, and surfaces a structured summary for developer confirmation.
• Agent Relay: “I have an agent. I want Alexa+ to hand off to it.” The developer defines scope boundaries (hand-off and hand-back conditions). The agent infers scope boundaries as a starting point. The developer must approve or negotiate direction before proceeding.

This flowchart illustrates these three integration paths in parallel, and shows where the experience converges again in the build phase. This visual asset helped parallel technical teams understand their impact during the integration experience. It also highlighted design complexities between them, which helped manage scope expectations.

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My Approach

• Interviewed Alexa developers and solutions architects to understand where the journey created friction, confusion, or unnecessary overhead
• Collaborated closely with solutions architects and technical writers to ensure that technical requirements were reflected accurately in the task flows
• Attached measurable outcomes to each Job-to-be-Done, creating Developer Experience Outcomes (DXOs) that gave the team a concrete definition of success at every stage
• Defined the distinct roles of agents, judges, and the orchestrator across the journey, establishing accountability for what the system handles autonomously and what requires human oversight
• Identified where AI could meaningfully reduce cognitive load through scaffolding and anticipation, and where human judgment needed to remain in the loop

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Key Decisions

• Initial design work should focus on API and MCP integration
• Collaborate with the solutions architect teams to define an internal agent-relay tool
• Incorporate DXOs into org vision and product requirements docs