What is Ask? Your AI Assistant Marketplace
While Fabrics are purpose-built tools for specific tasks, sometimes you need a conversation. That's where Ask comes in.
Ask is Promptha's AI assistant platform—a marketplace of specialized chatbots, each designed for different purposes. Instead of one generic AI that tries to do everything, you get access to focused assistants that excel at specific domains.
Think of it as the difference between calling a general helpline versus talking to a specialist. Both can help, but the specialist understands your context better.
Table of Contents
- Ask vs Traditional Chatbots
- How Ask Works
- The 12-Layer Architecture
- Browsing Ask Categories
- Model Switching
- Creating Your Own Ask
- Ask vs Fabric: When to Use Each
Ask vs Traditional Chatbots
When you use ChatGPT, Claude, or Gemini directly, you're talking to a general-purpose AI. It can help with almost anything, but it doesn't know your specific context, preferences, or domain constraints.
Traditional chatbot experience:
- You explain your context every conversation
- The AI doesn't know your preferences
- Responses are generic, requiring multiple follow-ups
- No specialization for your domain
Ask experience:
- Context is pre-loaded into the assistant
- Your preferences are remembered
- Responses are tailored to the domain
- Specialized knowledge for specific use cases
An Ask can be configured with:
- Domain expertise (coding, marketing, legal, etc.)
- Personality and communication style
- Knowledge sources and documents
- Specific capabilities and constraints
- Output formats and preferences
The result is a conversation that feels like talking to a specialist, not a generalist.
How Ask Works
Each Ask is a standalone AI assistant with its own configuration. When you start a conversation:
- Context Loading: The Ask's pre-configured context is loaded
- Model Selection: The appropriate AI model is selected (or you choose)
- Conversation Flow: You chat naturally, with the Ask understanding domain context
- Memory: The conversation history informs subsequent responses
- Output Formatting: Responses follow the Ask's configured format
Behind the scenes, an Ask can:
- Route to different AI models based on the query
- Access knowledge bases for domain information
- Apply skills for specialized capabilities
- Validate outputs against configured constraints
- Teach concepts with explanations and examples
The 12-Layer Architecture
Asks are built on a sophisticated 12-layer system that gives creators fine-grained control:
Layer 1: Models
Which AI models to use and when. An Ask can:
- Designate primary, supporting, and fallback models
- Route queries to different models based on content
- Balance cost and quality
Layer 2: Knowledge
What the Ask knows beyond general AI training:
- RAG (Retrieval-Augmented Generation) sources
- Document embeddings
- Few-shot examples
- Static reference data
Layer 3: Skills
Specialized capabilities the Ask can invoke:
- Translation rules
- Decision trees
- Domain-specific optimizations
- Custom workflows
Layer 4: Output
How responses are formatted:
- 22+ output types (text, code, tables, charts, etc.)
- Display preferences
- Formatting rules
Layer 5: Validation
Quality checks on responses:
- Syntactic validation
- Domain correctness
- Performance requirements
- Completeness checks
Layer 6: Workflow
Multi-step process handling:
- Progressive interactions
- Branching conversations
- Decision gates
- Stage transitions
Layer 7: Teaching
Educational capabilities:
- Explanation modes
- Concept definitions
- Anti-pattern warnings
- Comparison examples
Layer 8: Constraints
Guardrails and limits:
- Platform constraints
- Performance bounds
- Accessibility requirements
- Domain restrictions
Layers 9-12: Advanced
Context, integration, memory, and preference management.
Most users never need to think about these layers—they just work. But for creators building sophisticated Asks, this architecture enables powerful customization.
Deep dive: The 12-Layer Ask Architecture
Browsing Ask Categories
Asks are organized into categories to help you find the right assistant:
Design
Assistants for visual work:
- Design feedback and critique
- Color theory guidance
- Layout suggestions
- Brand consistency checking
Creative
Assistants for creative projects:
- Brainstorming partners
- Creative writing collaborators
- Ideation facilitators
- Story development helpers
Productivity
Assistants for getting things done:
- Task planning
- Meeting preparation
- Email drafting
- Document organization
Education
Assistants for learning:
- Subject tutors
- Concept explainers
- Study guides
- Quiz generators
Coding
Assistants for developers:
- Code review partners
- Debugging helpers
- Architecture advisors
- Documentation writers
Writing
Assistants for writers:
- Editing companions
- Style coaches
- Research assistants
- Outline builders
Research
Assistants for investigation:
- Literature reviewers
- Data analysts
- Fact checkers
- Synthesis helpers
Lifestyle
Assistants for personal use:
- Recipe advisors
- Travel planners
- Fitness coaches
- Personal finance helpers
Image
Assistants for image work:
- Prompt engineering for image generation
- Image description and analysis
- Style guidance
Audio
Assistants for audio work:
- Podcast planning
- Audio script writing
- Sound design guidance
Each category contains Asks created by the community, sorted by popularity, quality, and relevance.
Model Switching
One of Ask's most powerful features is dynamic model selection.
Use Any LLM
Asks can access multiple LLM models:
- Claude (Anthropic) - Excellent for nuanced writing and analysis
- GPT-4o (OpenAI) - Strong all-around performance
- Gemini (Google) - Great for research and long context
- DeepSeek - Specialized for coding and math
Switch Mid-Conversation
Unlike traditional chatbots locked to one model, Ask lets you:
- Switch models at any point in the conversation
- Compare responses from different models
- Use the best model for each query type
For example, you might start a conversation with Claude for its writing quality, then switch to DeepSeek when you need help with code.
Intelligent Routing
Some Asks automatically route queries to the best model:
- Writing questions → Claude
- Code questions → DeepSeek or GPT-4
- Research questions → Gemini (for long context)
- Quick questions → Faster, cheaper models
This happens transparently—you just ask your question, and the Ask picks the best model.
Fallback Handling
If a model is unavailable or overloaded, Asks can automatically fall back to alternatives, ensuring you're never stuck.
Compare the leading models: Claude vs GPT-4 vs Gemini
Creating Your Own Ask
Anyone can create an Ask. Here's what you configure:
Basic Setup
- Name and description: What your Ask does
- Category: Where it appears in the marketplace
- Avatar and branding: Visual identity
Context Configuration
- System prompt: The core instructions and personality
- Domain knowledge: Specific information the Ask should know
- Examples: Sample interactions showing desired behavior
Model Settings
- Primary model: Default model for responses
- Routing rules: When to use different models
- Fallbacks: Backup models if primary is unavailable
Knowledge Integration
- Documents: Upload files for the Ask to reference
- Knowledge base: Connect to Knowledge Bases
- Web access: Allow real-time information retrieval
Output Preferences
- Response format: How answers should be structured
- Length guidelines: Typical response length
- Tone: Communication style
Advanced Options
- Skills: Attach reusable capabilities
- Validation: Quality checks on responses
- Constraints: What the Ask should avoid
Once published, your Ask appears in the marketplace for others to discover and use.
Ask vs Fabric: When to Use Each
Both Ask and Fabric are AI tools on Promptha, but they serve different purposes:
| Aspect | Ask | Fabric |
|---|---|---|
| Interaction | Conversational, multi-turn | Form-based, single execution |
| Input | Natural language messages | Structured typed fields |
| Output | Chat responses | Formatted results (40+ types) |
| Best for | Exploration, iteration, learning | Defined tasks, production workflows |
| Context | Builds over conversation | Fresh each run |
| Refinement | Through follow-up messages | Through refinement controls |
Use Ask When:
- You need to explore a topic through conversation
- Requirements aren't fully defined yet
- You want back-and-forth iteration
- Learning or brainstorming
- Complex questions requiring clarification
Use Fabric When:
- You have a specific, defined task
- Inputs are known and structured
- You want consistent, reproducible outputs
- Production workflows
- Batch processing
Use Both Together
The best workflows often combine both:
- Start with Ask: Explore your needs, brainstorm, gather requirements
- Move to Fabric: Execute the defined task with structured inputs
- Return to Ask: Discuss results, plan next steps
For example:
- Use a Marketing Ask to brainstorm campaign ideas
- Use a Content Fabric to generate the actual assets
- Use the Ask to review and plan distribution
Read more: Ask vs Fabric: When to Use Each
Comparing Ask to ChatGPT
Many people wonder how Ask compares to ChatGPT. Here's the breakdown:
What's Similar
- Conversational AI interface
- Natural language interaction
- Multi-turn conversations
- General AI capabilities
What's Different
Model flexibility: ChatGPT uses OpenAI models only. Ask lets you use Claude, GPT-4, Gemini, DeepSeek, and more—switching anytime.
Specialization: ChatGPT is one general assistant. Ask is a marketplace of specialized assistants for different purposes.
Knowledge integration: ChatGPT relies on training data. Asks can connect to custom knowledge bases and documents.
Customization: Creating custom GPTs requires ChatGPT Plus. Anyone can create and share Asks.
Integration: Ask connects with the broader Promptha ecosystem—Fabrics, Skills, Knowledge Bases, and 50+ AI models.
Full comparison: Ask vs ChatGPT
Getting Started with Ask
Ready to try Ask? Here's your path:
1. Browse the Marketplace
Explore Asks by category. Try a few in areas that interest you. Notice how each has its own personality and expertise.
2. Start a Conversation
Pick an Ask and start chatting. Unlike Fabrics where you fill forms, Asks understand natural language. Just explain what you need.
3. Try Model Switching
If an Ask supports multiple models, try switching mid-conversation. Notice how different models handle the same query.
4. Create Your Own
Once you understand how Asks work, create one for your specific needs. Start simple—a good system prompt goes a long way.
What's Next?
Now that you understand Ask, explore further:
- The 12-Layer Ask Architecture - Technical deep dive
- Ask vs ChatGPT - Detailed comparison
- Ask vs Fabric - When to use each
- LLM Models on Promptha - Available models
- What is Knowledge Base? - Connect documents to Ask
Ask represents a new way to interact with AI—not a single generic assistant, but a marketplace of specialists. Find the right Ask for your needs, or create one perfectly tailored to your workflow.