What's the Difference Between Actions and Scenes?
Core Differences
| Feature | Action | Scene |
|---|---|---|
| Essence | Structured workflow | Persistent context environment |
| Role | Execution partner | Thinking partner |
| Working Method | One-time task completion | Continuous interactive environment |
| Scope | Single task processing | Entire conversation process |
| Core Value | Create new content | Provide stable context |
In one sentence:
- Action = A precise recipe, executed step by step, outputting definite results
- Scene = A professional operating room, providing roles, knowledge, and behavioral boundaries
How Actions Improve Controllability
Actions transform "vague intentions" into "precise workflows".
Process Decomposition
An Action breaks down vague user intentions (like "help me analyze competitors") into a series of specific subtasks:
- Extract core features
- Analyze target users
- Compare advantages and disadvantages
- Summarize strategic opportunities
AI will strictly follow this process rather than improvising.
Standardized Input
Actions guide users to provide the necessary, standardized information for task completion, avoiding output deviations caused by insufficient input.
Formatted Output
Actions force AI to output results in predetermined structured formats, ensuring content consistency and usability.
Analogy: Regular prompting is like telling a kitchen novice "make me dinner"—the result might be a disaster. Using an Action is like handing them a Michelin recipe precise to the gram—at least they'll make a decent dish.
How Scenes Improve Certainty
Scenes define the "boundaries" and "roles" of collaboration, like a "room" customized for specific tasks.
Role Fixation
Clearly define AI's role in the Scene, such as "You are a senior AI product strategy expert". AI's behavior and language style will be constrained by this preset role, producing more stable and professional output.
Knowledge Injection
Scenes can preload background knowledge, professional terminology, or thinking frameworks needed for specific tasks. AI will prioritize these preset knowledge rather than randomly pulling from its vast general knowledge.
Behavioral Constraints
Scenes set AI's behavioral boundaries, such as "You must answer based on provided materials and not fabricate information". This hard constraint greatly reduces the probability of AI producing "hallucinations".
Analogy: Chatting with regular AI is like talking to a stranger in a plaza—you can't predict their reactions. Using a Scene is like entering an operating room equipped with professional tools and talking to a doctor in a white coat—collaboration goals and results become clear and predictable.
Combined Usage: Building Expert-Level AI Applications
When Scenes and Actions are used together, Dessix transforms from a chat tool into a customizable AI application platform:
- Scene = The "operating system" AI runs on (defining worldview and basic capabilities)
- Action = "Applications" running on the system (defining task execution logic)
This combination lets you design and orchestrate how AI works based on professional needs. AI collaboration transforms from uncertainty-filled "artistic creation" to predictable "engineering practice".
Quick Selection Guide
Use Actions:
- ✅ Need to create new content
- ✅ Need to process specific tasks
- ✅ Need structured output
- ✅ One-time tasks
Use Scenes:
- ✅ Need ongoing dialogue
- ✅ Need deep thinking
- ✅ Need to create specific environments
- ✅ Need long-term memory support