AI Task Orchestration Lifecycle

Reference Model for Modern AI Systems (2025)

Component Function Why It Matters Context Engineering Responsibility Prompt/Input Engineering Responsibility
User Prompt The initial request or instruction. Starts the process. Captures user intent and relevant context (project, preferences, recent activity). N/A
Engineered Instructions System-generated clarifications and expansions of the task. Ensures precision and clarity. Adds clarifications, contextual details, and resolves ambiguities. Structures instructions or prompts in model/tool-appropriate form.
Orchestration Layer Plans, decomposes, and sequences workflow steps; manages agents/tools. Maintains process integrity and efficiency. Organizes and routes structured context for each sub-task and system. Constructs step-specific prompts or structured inputs for LLMs, APIs, or agents.
Workflow Automation Executes the planned steps and processes across systems and tools. Accomplishes tasks efficiently. Supplies tailored, step-specific context (permissions, files, configurations). Formats commands, API calls, or tool-specific input as needed.
Error Handling Detects failures, missing/conflicting information, and recovers or notifies. Ensures robust, resilient operation. Monitors and updates context to surface and address issues. Generates clarifying queries or error messages for user or system intervention.
Feedback Loop Incorporates user review, corrections, and iterative updates. Ensures accurate, user-approved outcomes. Maintains up-to-date context as changes and revisions are made. Prepares review prompts, summaries, or update queries for ongoing workflow.
Security & Privacy Manages sensitive data, permissions, and access boundaries. Ensures compliance and trust. Redacts, restricts, or limits context shared with each system or recipient. Applies relevant restrictions in crafting instructions or data payloads.
Tool/API Integration Connects with external digital tools and services. Extends workflow capabilities. Translates and maps context into formats required by target APIs or tools. Structures API calls or tool-specific input for integration steps.
Transparency & Tracking Logs actions, context changes, and decisions at each stage. Supports auditability and diagnostics. Continuously records context and workflow state for traceability. N/A
LLM Output Generates human-like communication (summaries, emails, etc.). Ensures clarity and effectiveness. Provides language models with relevant contextual background. Crafts effective prompts for natural language generation tasks.