Human–LLM collaboration spans multiple levels of capability.
These levels do not describe intelligence, nor do they imply personhood or autonomy. They describe how language is used, how structure is introduced, and how responsibility is managed in increasingly complex forms of collaboration.
Capability progression
Tool-assisted use
Language models are used as tools: retrieval, drafting, summarization.
Interaction is transactional. Execution authority remains fully external.
Extraction and synthesis
The user actively guides the model to surface relevant information, identify salient segments, and reduce noise.
Value lies in question formulation and selective interpretation.
Structured output
Language is used to produce lists, outlines, presentations, or scripts.
Structure is imposed explicitly, and correctness is evaluated at the output level.
Modular semantic design
Tasks are decomposed into semantic units with defined inputs, outputs, and constraints.
Interaction shifts from prompts to interface-like specifications.
Narrative construction
Language is used to construct coherent long-form reasoning, institutional drafts, or policy-like structures.
Correctness depends on consistency, scope, and internal alignment.
Semantic co-construction
At advanced levels, humans and language models co-design semantic structures: tone systems, role boundaries, and reusable linguistic modules.
Here, collaboration is no longer reactive. It is architected.
Boundary note
This progression describes capability alignment, not agency transfer.
Questions of governance, authorization, and responsibility are addressed elsewhere through explicit semantic constraints.