- Issue 2: replace raw 50-char threshold with is_genuine_continuation() that
checks for explicit follow-up phrases and mid-sentence capitalization (proper
nouns signal a new topic, not a continuation)
- Issue 3/8: build_activation_seed() scans back to find the prior USER turn as
the topic anchor instead of using the last assistant reply (hist_len-1)
- Issue 4: engram_compile_multi() fans out across three seeds — enriched primary,
raw message (entity queries), and emotion query — merging non-redundant results
- Issue 5: agent workspace_root appended to ag_seed so agentic activation is
workspace-aware; previously ignored despite being available in state
- Issue 6: distill_transcript() extracts salient tail+question content from full
transcripts before passing to engram_compile in dharma room handlers
- Issue 7: dist/soul-with-nlg.el handle_chat and handle_chat_agentic now load
history and use build_activation_seed() — the raw message path is eliminated
- Issue 9: topic_snip_from_entry() takes the TAIL 200 chars of a long reply and
finds the last sentence boundary — captures end-of-reply named concepts
- Issue 10: multi_turn_topic() pulls up to 3 prior user turns into the non-
continuation seed so earlier thread context re-activates high-salience nodes
elp-input.el: replace broken engram_search_json with engram_activate_json
as Layer 1. Layer 2 suppress/filter keeps nodes with non-zero salience/
importance. Reason step extracts patient from top activated node content.
ELP grammar realizes the response via generate().
routes.el: add 'elp' event_type to handle_dharma_recv so the studio can
route ELP requests through dharma.
will.anderson
Will Anderson