FlowTree is MyanFlow's mind-mapping learning workspace. It turns one keyword into a structured learning map, then lets you grow branches and load detailed lessons for each node.

Use it when you want a clearer path from first breakdown to deeper lesson detail before writing, researching, or planning.

1. Enter a keyword.
2. Select a learning level, output language, and Initial Map Mode.
3. Generate your first FlowTree overview.
4. Use Details to inspect a node and Expand or Expand More to deepen only the branches you need.
5. Open Node Details and click Load Lesson for deeper learning, then Refresh if you want another pass.

Fast mode builds a quicker shallow map. Full mode costs more but starts with a deeper initial structure.

• Basic: Definitions, core concepts, and beginner-friendly understanding.
• Intermediate: Building patterns, applied workflows, and practical implementation.
• Pro: Internals, optimization, failure modes, and architecture-level thinking.
• Comprehensive: A fuller learning path that spans foundations, practical implementation, and advanced internals.

• Fast (Progressive): Builds a shallow first map more quickly so you can decide which branches deserve more depth.
• Full Initial Map: Costs more credits and usually takes longer, but returns a deeper starting structure.
• If credits are tight while Full mode is selected, FlowTree can suggest falling back to Fast mode.

Node lessons can use live grounding. When grounding evidence is available, FlowTree marks the lesson as grounded and shows source links so you can verify claims quickly.

• Grounding status is visible in the lesson panel.
• The lesson panel shows evidence status, trust coverage, and suggested next steps.
• Source links are shown when evidence is detected from live search.
• If grounding is unavailable, or your plan does not include it, FlowTree still generates standard structured lessons.
• If evidence is limited, language is conservative and you can refresh the lesson.
• Grounded lesson generation is currently a Pro feature.

• Lessons can include structured code examples with language tags.
• Lessons can include claim evidence mappings to help verify key statements quickly.
• Node Details can also include learning objectives, prerequisites, checkpoints, next steps, and spotlight sections.
• Markdown rendering supports richer headings, tables, and code blocks for better readability.
• Use Refresh on a node to regenerate richer lesson details when needed.

• FlowTree enforces output-language targeting for node labels and explanations.
• Burmese output follows a developer-friendly mixed style: natural Burmese with core technical terms kept in English when appropriate.
• Code identifiers, package names, commands, and tool/framework names remain in English for clarity.

FlowTree uses your shared AI credits wallet with transparent billing.

FlowTree integrates with My Stuff so you can restore both map structure and saved node lessons.

• FlowTree snapshots are manual. Use Save Snapshot to write your current map to source flowtree.
• After more changes, the button becomes Save Snapshot Changes.
• Use Save Lesson Snapshot when node lessons are loaded and you want those lesson payloads preserved.
• FlowTree warns before navigation when map or lesson snapshots have unsaved changes.
• Open My Stuff with source filter: FlowTree My Stuff

• Start broad with overview, then expand one branch at a time instead of expanding everything at once.
• Use Fast mode for a first pass, and switch to Full only when you want a deeper starting map immediately.
• Load grounded lessons only on nodes you actually need to study in depth.
• Save snapshots at meaningful milestones (e.g., after finishing one major branch).
• Save a lesson snapshot after loading high-value node explanations so claim evidence and code examples can be restored later.
• Send strong node context into Content Generator or Brand DNA when you are ready to turn the map into a draft.
• Use Pro for internals/optimization topics, Basic for first-pass learning, and Comprehensive when you want the widest learning path.