feat: Autonomy Core v1 — Lyra's evolving self-state

Give Lyra a model of *herself* (vs the profile/narrative which model Brian):

- persona: a real origin/identity — she's an AI and knows it (Bender/C-3PO
  style), with the Cortex/NeoMem lineage as her actual past, so "how were you
  made" stops falling through to generic-assistant deflection.
- memory: self_state table (JSON blob) + get/set_self_state.
- lyra/self_state.py: evolving first-person inner state (mood, valence, energy,
  confidence, curiosity, self_narrative, relationship, reflections). render_for_
  context injects it; reflect() updates it from recent activity. `lyra-reflect`.
- chat.build_messages injects her interiority right after the persona — she
  speaks from a continuous self, not a reset.

The state -> behavior -> reflection -> updated state loop is the substrate for
the emergence experiment. Verified: reflection shifted mood curious->reflective
and produced genuine first-person self-observations.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

lyra/chat.py

@@ -10,7 +10,7 @@ After replying, the session is compacted if enough new turns have accumulated.
 """
 from __future__ import annotations
 
-from lyra import config, llm, logbus, memory, persona, summary
+from lyra import config, llm, logbus, memory, persona, self_state, summary
 from lyra.llm import Backend, Message
 
 RECALL_K = 3  # raw cross-session "sharp detail" hits
@@ -39,6 +39,10 @@ def build_messages(session_id: str, user_msg: str) -> list[Message]:
     """Assemble the full, tiered message list for one turn."""
     messages: list[Message] = [{"role": "system", "content": persona.system_prompt()}]
 
+    # Autonomy Core: Lyra's own evolving interiority (mood, self-narrative). Comes
+    # right after the persona — her sense of self before her model of the world.
+    messages.append({"role": "system", "content": self_state.render_for_context(self_state.load())})
+
     # Semantic memory: the distilled profile (who Brian is) — answers identity
     # questions that raw recall can't. Always in context when it exists.
     profile = memory.get_profile()