First Conversations in Strings
Start conversations with your AI character in Strings — persistent memory, awareness control, and advanced reasoning features.
Objective
Open Strings, start a conversation with the character you built, and understand how semantic memory, the awareness slider, and advanced input controls work.
What Strings Are
Strings are smart conversation containers — not just chat windows. Each String is:
- Persistent — messages are saved and semantically indexed for later retrieval
- Multi-character — you can add multiple AI characters to one conversation
- Channel-bridged — messages from Telegram, Slack, Discord, WhatsApp, and Email can appear in the same thread
- Memory-aware — every message is stored as a semantic memory, searchable by meaning
Creating Your First String
- Open Strings from the QUI Core dashboard or system tray
- Click [+] in the sidebar to create a new String
- Name it (e.g., "My First Conversation")
- Select the character you built in the previous lesson
- Type a message and press Enter
Your character responds using its full context — identity, personality, system prompts, and any memories it has from previous conversations.
[Screenshot: Strings interface showing a conversation with a character]
The Awareness Slider
The awareness slider controls how much memory context is included with each message. Find it in the input controls area.
| Level | Range | What Happens | When to Use |
|---|---|---|---|
| Low | 0-30 | Fewer memories retrieved. Faster, cheaper responses. | Casual chat, simple questions |
| Medium | 30-70 | Balanced context retrieval. | General use |
| High | 70-100 | Rich memory context. More tokens used, more expensive. | Complex tasks needing full context |
Try it now:
- Have a conversation about a specific topic
- Set awareness to 10 and ask a follow-up — notice the response may lack context
- Set awareness to 90 and ask the same question — notice richer, more contextual response
The awareness slider is a cost/quality tradeoff. Higher awareness means the character draws on more of its memories, but uses more tokens per request.
Advanced Input Controls
Below the chat input, you'll see several controls. These become important in Week 2, but let's introduce them:
ThoughtChain (0-10)
Sets how many explicit reasoning steps the character takes before responding. At 0, it responds directly. At higher values, it thinks step-by-step before answering.
Autothink Strategy
A dropdown with 14 reasoning approaches (First Principles, Red Team, Systems Thinking, etc.). When selected, the character applies that thinking strategy to your message. We'll use these extensively in Week 2.
Send Raw
Bypasses all enrichment (memory, consciousness, strategies) and sends your message directly to the LLM. Useful for debugging — you can see how the character responds without any QUI enhancements.
For now: Leave ThoughtChain at 0 and Autothink off. Focus on understanding basic conversations and memory. We'll unlock these in Week 2.
How Memory Works — The Basics
Every message in a String is automatically:
- Stored in the memory database
- Indexed with vector embeddings for semantic search
- Categorized by type: fact (permanent), event (moderate decay), general, or fleeting (fast decay)
- Scored by importance — higher importance memories are retained longer
When your character receives a new message, it searches its memories for semantically relevant content and includes it as context. This isn't keyword matching — it's meaning-based. A question about "database performance" will surface memories about "query optimization" and "index tuning" even if those exact words were never used together.
Star Important Messages
Click the star icon on any message to boost its importance. Starred messages:
- Are retained longer (resist memory decay)
- Rank higher in retrieval
- Are more likely to be included in context
Testing Memory Across Sessions
Let's verify that memory works:
- Tell your character something specific: "My favourite programming language is Rust and I prefer functional patterns"
- Have a short unrelated conversation
- Close the String
- Wait a moment, then reopen it
- Ask: "What do you know about my coding preferences?"
The character should recall your Rust preference — this is semantic memory, not chat history. The message was indexed by meaning and retrieved when your question was semantically similar.
Key Takeaways
- Strings are persistent, semantically indexed conversation containers
- The awareness slider controls memory depth — balance between context quality and cost
- Every message is automatically stored as a searchable semantic memory
- Star messages to boost their importance and retention
- Advanced controls (ThoughtChain, Autothink) add reasoning depth — covered in Week 2
- Memory works by meaning, not keywords — "coding preferences" matches "favourite language"
Next: Exercise 1A — build a specialist Research Assistant and test it.
