1. The Chat Is NOT Just a Chat — It's a Context Engine
New users think: type question -> get answer.
Power users know: the AI's answer quality is 90% determined by what context you provide before sending a prompt. In Accelerated Logic AI, three distinct layers of context stack together:
Folder Memory instructions and Pinned Files that apply to every single message in that thread or folder.
Temporary images, audio, code files, or documents attached specifically to your current message turn.
Your specific task instruction, question, or enhancement request written in the composer textarea.
2. Thread Management — Before You Even Type
- New Chat & Auto-Titling: Sidebar New Chat creates a blank thread. It automatically auto-titles based on your first prompt after the assistant answers, or double-click to rename manually.
- Full-Text Thread Search: Use the search bar at top of sidebar to query message content across all past threads instantly.
- Pinned Chats & Folders: Hover over any chat to click the pin icon. Create custom folders with Folder Memory (e.g., "We use React + Tailwind, no class components"). All chats inside that folder automatically inherit those rules.
- Forking Conversations: Hover under any user or assistant message and click Fork. This branches the conversation from that exact message into a new thread without modifying original history.
3. The Composer — Deep Dive
- Active Skills & Personas Bar: Active skills display as blue chips; personas as indigo chips. Click the X on any chip to disable immediately.
- Project Context Bar: Shows pinned files attached to this chat session. Click chips to preview or unpin.
- Staged Media Assets (72x72 Cards): Dragged files, screenshots, or pasted images appear inside the composer as temporary cards prior to sending.
- Enhance Prompt (Wand): Expands brief prompts into detailed, structured prompts using AI.
- Queue Response & Stop: While the assistant streams, type your next prompt and click Queue Response (indigo) to auto-send upon completion.
4. File Upload — 6 Methods & All Supported Types
- Plus button file picker
- Global window drag overlay
- Composer-specific drop zone
- Sidebar file drag to composer
- Clipboard Paste (Ctrl+V screenshots, URLs)
- ZIP archive auto-unzip import
- Images: Vision queue (SVG sent as code text)
- PDFs: Auto-extracts plain text with page markers
- Videos: Inline video data (~560 tokens)
- Code/Text: Context-optimized if >5000 chars
5. Pinned vs Staged — When to Use Which
- One-off UI screenshot reviews
- Comparing two image attachments
- Quick questions about a log snippet without cluttering context permanently
- Core schema files (
types.ts,package.json) - Project architecture rules and API documentation
- Active code files being iteratively edited across multiple turns
6. How the App Saves Tokens — Relevant Snippets
When large text or code files (>5000 characters) are attached, Accelerated Logic AI automatically optimizes context window usage:
- Splits file into 15-line chunks with 4-line overlapping boundaries.
- Scores chunks against key terms in your prompt.
- Selects highest-scoring chunks up to 5,000 characters.
- Annotates output:
[CONTEXT OPTIMIZED: Showing only relevant sections based on your query].
7. Prompting Patterns That Work Best
"Stage server.ts + prompt: Review for CORS and authentication vulnerabilities."
"Upload UI screenshot + prompt: Clone this exact dashboard component in React + Tailwind."
8. Token & Context Window UI Indicators
Monitor response telemetry under assistant messages:
TPS Badge: Displays Tokens Per Second generation throughput (~15–40 local, ~150–300 cloud).
Context % Indicator: Hover over the Context % badge to see exact token counts (e.g. 12,450 / 128,000 tokens used). When context reaches 90%+, start a New Chat inside the same folder to preserve Folder Memory while resetting token load.
9. Hardening & Edge Cases
For large repositories, use ZIP import or GitHub repository import (covered in Part 17).
SVGs are deliberately parsed as clean source text so text-only AI models can analyze the raw XML vector markup directly.