Nina — Context Engineer
Type: Secondary Persona
Responsibilities
- Emerging role focused on optimizing context windows for agents
- Translates upstream APIs/MCP servers into efficient tool interfaces
- Evaluates which context engineering techniques work for which models
- Builds evaluation frameworks for agent-API interaction quality
Related Problem Statements
| Problem Statement | Context | Impact | Naftiko Today | Naftiko Tomorrow | Type |
|---|---|---|---|---|---|
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Need Agent Evaluation Framework
Context engineers need to evaluate whether AI agents called APIs correctly—with right parameters, in right order—not just whether the final output looks correct.
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Need to Translate Many MCP Tools
Context engineers need to consolidate many upstream APIs and MCP servers into a smaller set of efficient tools that agents can use effectively.
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Need Question Formation Embedded in MCP Workflows
MCP-enabled documentation should accelerate implementation work inside IDEs and copilots, but 'ask anything' interfaces fail when users don't know the right prompts.
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Need Minimum Agent Operational Documentation
Repositories can look documented but still fail basic agent tasks because the docs were written for humans, not for agent execution.
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Need Standardized Structures for Agent-Consumable Markdown
Markdown docs must follow predictable, machine-reliable structures so agents can consistently locate authoritative answers.
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Need Knowledge Graphs and Semantic Layers for API Context
Organizations need knowledge graphs and semantic layers to give AI agents structured, contextual understanding of API relationships, business logic, and entity models — not just flat catalogs.
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Need Context Engineering Practices Across the API Lifecycle
API teams need to adopt context engineering as a discipline — curating the optimal set of instructions, knowledge, and feedback that enables agents to effectively discover, understand, and consume APIs.
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