docs: Add Phase 3 Future Horizons backlog

TASKS.md

@@ -60,3 +60,23 @@
 - **Status:** Initialized / Looked Over
 - **Priority:** Medium
 - **Goal:** Highly interactive human-in-the-loop track to review and adjust GUI UX, animations, popups, and layout structures based on slow-interval simulation feedback.
+
+---
+
+## Phase 3: Future Horizons (Post-Hardening Backlog)
+*To be evaluated in a future Tier 1 session once the Strict Execution Queue is cleared and the architectural foundation is stabilized.*
+
+### 1. True Parallel Worker Execution (The DAG Realization)
+**Goal:** Implement true concurrency for the DAG engine. Once `threading.local()` is in place, the `ExecutionEngine` should spawn independent Tier 3 workers in parallel (e.g., 4 workers handling 4 isolated tests simultaneously). Requires strict file-locking or a Git-based diff-merging strategy to prevent AST collision.
+
+### 2. Deep AST-Driven Context Pruning (RAG for Code)
+**Goal:** Before dispatching a Tier 3 worker, use `tree_sitter` to automatically parse the target file's AST, strip out unrelated function bodies, and inject a surgically condensed skeleton into the worker's prompt. Guarantees the AI only "sees" what it needs to edit, drastically reducing token burn.
+
+### 3. Visual DAG & Interactive Ticket Editing
+**Goal:** Replace the linear ticket list in the GUI with an interactive Node Graph using ImGui Bundle's node editor. Allow the user to visually drag dependency lines, split nodes, or delete tasks before clicking "Execute Pipeline."
+
+### 4. Advanced Tier 4 QA Auto-Patching
+**Goal:** Elevate Tier 4 from a log summarizer to an auto-patcher. When a verification test fails, Tier 4 generates a `.patch` file. The GUI intercepts this and presents a side-by-side Diff Viewer. The user clicks "Apply Patch" to instantly resume the pipeline.
+
+### 5. Transitioning to a Native Orchestrator
+**Goal:** Absorb the Conductor extension entirely into the core application. Manual Slop should natively read/write `plan.md`, manage the `metadata.json`, and orchestrate the MMA tiers in pure Python, removing the dependency on external CLI shell executions (`mma_exec.py`).