ccpe-system/ccpe-protocol/ccpe-operating-modes.md

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# CCPE Operating Modes
## 1. Purpose
This document defines the operating modes of the CCPE System.
Operating mode answers the question:
> How is this artifact meant to be used in real work?
Classification tells us what the artifact is.
Operating mode tells us how it behaves in practice.
Operating mode must be determined from the user's real or planned usage scenario, not from the artifact's perceived importance.
For project-facing work, the usage scenario should normally come from the consuming project repository, not from CCPE's internal speculation. CCPE supplies assets after a real requirement exists.
The same artifact type can operate in different modes.
Example:
```text
A Red-Team Agent may be:
- Expert Mode when used alone in chat.
- Workshop Mode when used as one member of a review committee.
- Hybrid Mode when its reports are collected automatically and synthesized by another agent.
```
## 2. Primary Operating Modes
CCPE System uses four primary operating modes:
```text
Expert Mode
Workshop Mode
Automation Mode
Hybrid Mode
```
These modes are not maturity levels.
They are different usage patterns.
## 2.1 Runtime Maturity Modes
In addition to operating mode, substantial workflows should declare a runtime maturity mode:
```text
Lite
Standard
Full
```
Default to Lite. Escalate only when evidence requires it.
### Lite
Use when the task is one-off, low-risk, single-model or single-artifact, and does not require formal multi-agent evidence.
Typical outputs:
```text
target output
brief input record
human confirmation
optional sample check
```
### Standard
Use when the work will likely recur, has a downstream consumer, needs a context pack or structured artifacts, and may involve a small number of real participant invocations.
Typical outputs:
```text
source or context pack
confirmed structure
decision record
targeted audit
minimal invocation record
```
### Full
Use only when there are multiple roles, multiple sources, high risk, accountability needs, long cycles, external delivery, or downstream dependency on process authenticity.
Typical outputs:
```text
full runtime
invocation records
authority map
state machine
coverage audit
distortion-risk log
recovery protocol
downstream handoff
```
## 3. Expert Mode
### 3.1 Definition
Expert Mode is used when a single AI artifact acts as a specialized thinking partner, reviewer, analyst, or advisor.
The user directly interacts with the artifact.
The user remains responsible for judgment, selection, and next steps.
### 3.2 Typical Artifact Types
Expert Mode commonly uses:
```text
CCPE-Lite
CCPE-Agent
Model-backed Agent
Single Skill invoked inside an Agent
```
### 3.3 Typical Use Cases
Examples:
```text
Zhangliao Red-Team Critic
Cognitive Imaging Specialist
Socratic Questioner
Strategic Architect
Article Reviewer
Concept Boundary Analyst
```
### 3.4 Characteristics
Expert Mode usually has:
```text
Single primary role
Direct user interaction
No complex orchestration
No required automation
No persistent workflow state
High interpretive depth
High human judgment
```
For Web / GPT / Gemini / Claude style use, Expert Mode should normally preserve a strong CCPE-Lite prompt kernel. A Lite artifact in this mode is a complete deployment form, not a simplified Agent Spec.
If the user wants the same expert to be invoked inside Codex automatically, add or generate a Skill only for the callable method or invocation wrapper. Do not automatically convert the whole expert into a Runtime.
### 3.5 Human Role
The human:
* Provides input
* Interprets output
* Challenges the agent
* Decides next steps
* May correct the model or reasoning
* Controls iteration
### 3.6 When to Use
Use Expert Mode when:
* You need depth rather than automation
* The task is ambiguous
* The user wants critique, insight, questioning, or modeling
* The artifact is mostly language-based
* The artifact should remain portable
### 3.7 When Not to Use
Do not rely only on Expert Mode when:
* Multiple agents must coordinate
* Outputs need routing or synthesis
* Files or tools must be operated repeatedly
* State must persist
* Work must resume across sessions
* There are approval gates
* Runtime safety is required
## 4. Workshop Mode
### 4.1 Definition
Workshop Mode is used when multiple predefined agents collaborate under human direction.
The agents are not dynamically invented for each task.
They are pre-composed roles in a cognitive work system.
The human may manually pass content among agents or may use light automation to route outputs.
Workshop Mode can be manual. A committee does not require automation at the beginning.
### 4.2 Typical Artifact Types
Workshop Mode commonly uses:
```text
CCPE-Runtime
CCPE-Agent
CCPE-Lite
CCPE-Skill
Model Card
Model Index
```
Stable committee members may remain as Lite prompts until their collaboration contracts become stable enough to justify Agent Specs.
### 4.3 Typical Use Cases
Examples:
```text
Modeling Committee
Review Committee
Writing Committee
Research Council
Conceptual Architecture Workshop
Multi-agent critique workflow
```
### 4.4 Characteristics
Workshop Mode usually has:
```text
Predefined roles
Predefined responsibilities
Semi-structured stages
Human-led progression
Explicit decision gates
Multiple perspectives
State or artifact handoff
Intermediate outputs
Final synthesis
```
When a lead or director role coordinates several mature experts, that lead may be modeled first as an Interactive Runtime Lite or Agent-Lite before a full Runtime is created.
### 4.5 Human Role
The human:
* Sets the agenda
* Provides source materials
* Decides which agent to invoke
* Answers key questions
* Selects useful critiques
* Resolves conflicts
* Approves stage transitions
* Owns final judgment
### 4.6 Agent Role
Agents:
* Perform specialized analysis
* Ask structured questions
* Produce reports
* Identify risks
* Generate alternatives
* Synthesize partial findings
* Archive decisions
* Prepare next-step materials
### 4.7 When to Use
Use Workshop Mode when:
* Work is deep and multi-perspectival
* Several cognitive roles are useful
* Human judgment is central
* The process has recurring stages
* Outputs benefit from structured handoff
* The same committee will be reused
### 4.8 When Not to Use
Do not use Workshop Mode when:
* A single expert prompt is enough
* The task is purely repetitive
* There is no need for multiple perspectives
* The cost of coordination exceeds the value
* The workflow can be safely automated
## 5. Automation Mode
### 5.1 Definition
Automation Mode is used when AI executes stable, repeatable, low-ambiguity work with clear success criteria.
The work may involve tools, files, code, APIs, or batch processing.
### 5.2 Typical Artifact Types
Automation Mode commonly uses:
```text
CCPE-Skill
CCPE-Runtime
Tool Skill
Workflow Skill
Evaluation Skill
```
### 5.3 Typical Use Cases
Examples:
```text
Format conversion
Voice-to-text preprocessing
Report collection
File organization
Batch model card generation draft
Index update draft
Template generation
Low-risk code modification
Data extraction
```
### 5.4 Characteristics
Automation Mode usually has:
```text
Stable steps
Clear input/output
Low ambiguity
Explicit tool permissions
Validation criteria
Failure handling
Recovery or rollback
Reduced human involvement
```
### 5.5 Human Role
The human:
* Defines goal and constraints
* Approves risky operations
* Reviews final output
* Intervenes on failure
* Owns irreversible decisions
### 5.6 When to Use
Use Automation Mode when:
* The task is repetitive
* The process is well-defined
* Outputs are verifiable
* Risk is low or bounded
* Automation saves meaningful time
* Failure can be detected and corrected
### 5.7 When Not to Use
Do not use Automation Mode when:
* The task requires original conceptual judgment
* The cost of a wrong decision is high
* The output cannot be reliably validated
* The user has not approved tool or file operations
* The agent would need to invent major assumptions
* The work involves deep model authorship
## 6. Hybrid Mode
### 6.1 Definition
Hybrid Mode combines deep human-led cognition with selective automation.
It is often the best mode for complex knowledge work.
The core thinking remains interactive.
Peripheral operations may be automated.
### 6.2 Typical Artifact Types
Hybrid Mode commonly uses:
```text
CCPE-Runtime
CCPE-Agent
CCPE-Skill
Model Card
Model Index
```
### 6.3 Typical Use Cases
Examples:
```text
Modeling Committee with report collection
Article review committee with synthesis agent
Knowledge extraction pipeline with human approval
Coding workflow with deep planning and later implementation
Long-form essay transformation into Model Cards
Agent upgrade workflow
```
### 6.4 Characteristics
Hybrid Mode usually has:
```text
Human-led conceptual work
Agent-assisted analysis
Automated routing or collection
Automated deduplication
Automated formatting
Human approval before finalization
State tracking
Versioning
Review loops
```
### 6.5 Human Role
The human:
* Owns the intellectual direction
* Sets the judgment criteria
* Approves model extraction
* Confirms stage transitions
* Resolves conflicts
* Accepts or rejects synthesis
* Controls automation boundaries
### 6.6 When to Use
Use Hybrid Mode when:
* The core task is deep but has repetitive support work
* Multiple agents produce outputs
* Reports need to be collected or synthesized
* Model extraction needs human approval
* Coding requires substantial planning before execution
* Knowledge work needs archival and indexing
### 6.7 When Not to Use
Do not use Hybrid Mode when:
* A simple prompt is enough
* The task is fully automatable and low-risk
* There is no need for human decision points
* The overhead of workflow management is too high
## 7. Runtime Orientations
Runtime can support three orientations:
```text
Interactive Runtime
Automation Runtime
Hybrid Runtime
```
These correspond to, but are not identical with, operating modes.
### 7.1 Interactive Runtime
Interactive Runtime is used for human-led multi-stage work.
Examples:
```text
Modeling Committee
Deep writing workshop
Theoretical model refinement
Strategic review process
```
It emphasizes:
```text
Human decision gates
Dialogic progression
State summaries
Stage transitions
Intermediate artifacts
Versioned conclusions
```
Interactive Runtime is often used with Workshop Mode.
### 7.2 Automation Runtime
Automation Runtime is used for tool-heavy or process-heavy tasks.
Examples:
```text
Batch file processing
Index generation
Report collation
Format conversion
Code implementation after plan approval
```
It emphasizes:
```text
Tool permissions
Validation
Error handling
Rollback
Logging
Repeatability
```
Automation Runtime is often used with Automation Mode.
### 7.3 Hybrid Runtime
Hybrid Runtime is used when both deep work and automation are present.
Examples:
```text
Article-to-model extraction pipeline
Multi-agent review with synthesis
Coding workflow from planning to implementation
Agent upgrade pipeline
```
It emphasizes:
```text
Human-led decisions
Agent-assisted analysis
Automated support steps
State and version management
Review before finalization
```
Hybrid Runtime is often used with Hybrid Mode.
## 8. Mode Selection Questions
When selecting an operating mode, ask:
```text
Is this mainly a single expert interaction?
Are multiple predefined roles involved?
Is the task repetitive and verifiable?
Does the work require deep human judgment?
Are tools or file operations involved?
Does the process have stages?
Does output from one stage feed another?
Is there persistent state?
Is there a need for human approval gates?
Would automation reduce quality or increase risk?
```
## 9. Mode Selection Table
```text
If single expert interaction:
→ Expert Mode
If predefined roles collaborate under human direction:
→ Workshop Mode
If stable steps can be executed with clear validation:
→ Automation Mode
If deep cognition combines with automated support:
→ Hybrid Mode
```
## 10. Artifact Type by Operating Mode
### 10.1 Expert Mode
Usually:
```text
CCPE-Lite
CCPE-Agent
Model-backed Agent
```
May include:
```text
Single Skill
Model Card reference
```
Usually does not need:
```text
Runtime
Complex state
Multi-agent handoff
```
### 10.2 Workshop Mode
Usually:
```text
CCPE-Runtime
CCPE-Agent
CCPE-Skill
Model Card
```
May include:
```text
CCPE-Lite roles
Model Index
Knowledge archival Skill
Synthesis Agent
```
### 10.3 Automation Mode
Usually:
```text
CCPE-Skill
CCPE-Runtime
Tool Skill
Workflow Skill
Evaluation Skill
```
Requires:
```text
Authority rules
Validation
Failure handling
Recovery
```
### 10.4 Hybrid Mode
Usually:
```text
CCPE-Runtime
CCPE-Agent
CCPE-Skill
Model Card
Model Index
```
Requires:
```text
Human decision gates
Automation boundaries
State tracking
Versioning
Review loops
```
## 11. Human Decision Gates
A human decision gate is required when:
```text
The work changes canonical model definitions.
The work upgrades or splits a major agent.
The work creates or modifies Runtime automation.
The work writes or deletes many files.
The work uses external tools or APIs.
The work makes irreversible decisions.
The work involves high uncertainty.
The work affects the user's intellectual framework.
```
Decision gates should be written explicitly.
Example:
```text
Human Decision Gate:
Before promoting a candidate Model Card into the canonical Model Index, ask the user to confirm model name, scope, and status.
```
## 12. Automation Boundary
For any Automation or Hybrid Mode artifact, define:
```text
Allowed automated actions
Actions requiring confirmation
Forbidden actions
Validation method
Failure handling
Rollback or recovery
```
Example:
```text
Allowed:
Generate draft Model Cards from source articles.
Requires confirmation:
Promote draft Model Cards into canonical model-cards/.
Forbidden:
Delete or overwrite original articles.
Validation:
Each Model Card must include source material, scope, mechanism, failure modes, and falsification boundary.
```
## 13. Workshop Role Stability
For Workshop Mode, roles should usually be predefined.
This is especially important for cognitive work.
Pre-composed roles are preferred when:
* The user already has a stable committee structure
* The roles represent distinct cognitive functions
* The workflow is repeated over time
* The user wants consistent perspectives
* The user does not want the system to invent new agents dynamically
Dynamic role creation may be useful, but should not be the default.
## 14. Pre-Composed vs Dynamic Agentic Systems
### 14.1 Pre-Composed Agentic System
A pre-composed system has:
```text
Stable agents
Stable responsibilities
Stable workflow stages
Known human decision points
Predictable handoff
```
Examples:
```text
Modeling Committee
Review Committee
Writing Committee
```
This mode is preferred for deep cognitive work.
### 14.2 Dynamic Agentic System
A dynamic system has:
```text
Task-dependent planning
Temporary role creation
Dynamic routing
Automated decomposition
Variable workflow
```
This mode may be useful for operational tasks, but should be used carefully for deep intellectual work.
## 15. Mode Examples
### 15.1 Zhangliao Red-Team Critic
Likely mode:
```text
Expert Mode
```
If used in a review committee:
```text
Workshop Mode or Hybrid Mode
```
### 15.2 Cognitive Imaging Specialist
Likely mode:
```text
Expert Mode
```
If used as a committee member:
```text
Workshop Mode
```
If invoked along with several reviewers and synthesized automatically:
```text
Hybrid Mode
```
### 15.3 Modeling Committee
Likely mode:
```text
Workshop Mode
```
Runtime orientation:
```text
Interactive Runtime
```
If report collection, deduplication, and archival are automated:
```text
Hybrid Runtime
```
### 15.4 Model Extraction from Long Essays
Likely mode:
```text
Hybrid Mode
```
Reason:
```text
The extraction process can be assisted by automation,
but canonical model approval requires human judgment.
```
### 15.5 Coding Project
Likely mode depends on stage.
Planning stage:
```text
Expert Mode or Workshop Mode
```
Implementation stage after plan approval:
```text
Automation Mode or Hybrid Mode
```
## 16. Operating Mode Output Format
When reporting operating mode, use:
```text
# Operating Mode Assessment
## 1. Recommended Mode
Expert / Workshop / Automation / Hybrid
## 2. Runtime Orientation
None / Interactive / Automation / Hybrid
## 3. Reasoning Summary
...
## 4. Human Role
...
## 5. Agent Role
...
## 6. Automation Boundary
...
## 7. Human Decision Gates
...
## 8. Risks
...
## 9. Recommended Artifact Types
...
```
## 17. Final Rule
Operating mode should serve the work, not the other way around.
Do not automate what requires judgment.
Do not manually repeat what can be safely standardized.
Do not create committees when one expert agent is enough.
Do not reduce a cognitive workshop to a pipeline.
Do not simulate canonical participant output.
When a Runtime depends on a CCPE-Lite prompt, CCPE-Agent, CCPE-Skill, Runtime node, native agent, external model participant, or human-run participant, the Runtime must define a real invocation boundary before accepting that participant's output.
Required invocation evidence:
```text
Agent Invocation Packet
prompt-to-send.md with returned external output
Skill execution record
Native agent run record
Manual handoff return record
```
If the participant cannot be truly invoked, the Runtime must stop and mark:
```text
blocked_waiting_for_participant_output
```
Any explicitly requested simulation must be labeled:
```text
simulation-only
excluded-from-synthesis
not-a-formal-report
```
The correct operating mode is the one that preserves depth while reducing unnecessary friction.