diff --git a/DECISIONS.md b/DECISIONS.md
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--- a/DECISIONS.md
+++ b/DECISIONS.md
@@ -44,6 +44,29 @@ Record *why* things are the way they are. Future-you will thank present-you.
 
 **Consequences**: More operational complexity than Chroma, but isolation is non-negotiable for client work.
 
+## 2026-04-22 — Hyperguild scope reset: drop parametric learning, simplify brain
+
+**Context**: After shipping Phases 1–4 (MCP server, 6 skills, model orchestration, session logging, CD pipeline), we critically reviewed what was theater vs genuinely useful.
+
+**Decisions**:
+
+1. **Drop the parametric learning pipeline.** SFT/DPO/RL extraction, `brain/training-data/` directory structure, Axolotl/LLaMA-Factory fine-tuning loop — all cut. The loop requires thousands of high-quality examples to move the needle, which a solo consultant won't generate. Better base models ship faster than any fine-tuning effort could keep up with. This is a research project, not a productivity tool.
+
+2. **Simplify the brain to plain markdown.** `brain/knowledge/` replaces `brain/wiki/ + brain/raw/ + brain/training-data/`. The trainer and retrospective workers write markdown entries. `brain_query` searches markdown. No ingestion pipeline, no tagging for significance review, no structured JSONL formats.
+
+3. **Measure the escalation chain before assuming it's useful.** Local model (phi4) only belongs in a skill's chain if it passes Claude verification at a meaningful rate. Where it fails >70% of the time, it adds cost not value. Per-skill hit rate logging is the prerequisite to honest chain configuration.
+
+4. **Keep what's real**: MCP tool surface, session logging with attempt records, tier detection, CD pipeline, bridge to Claude Code.
+
+**What to build next** (in priority order):
+- `brain_query` injection into skill handlers before spawning workers — this makes the declarative brain actually function
+- `protocols.md` — behavioral contract injected into every worker prompt
+- Per-skill pass rate logging and chain tuning
+
+**Consequences**: Simpler system with a shorter feedback loop. The brain becomes real only when skill handlers query it. Training data ambitions deferred indefinitely — revisit if local model capabilities improve enough that fine-tuning becomes worthwhile.
+
+---
+
 ## 2026-04-08 — Mistral Vibe gets its own adapter
 
 **Context**: Vibe doesn't read `AGENTS.md` — it uses `~/.vibe/prompts/` and `~/.vibe/agents/` with TOML config.