Release v1.3.0

CHANGELOG.md

@@ -6,6 +6,27 @@ Versioning follows [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
 ---
 
+## [v1.2.8] — 2026-03-27
+
+### Added
+
+- **Multi-Channel CRM Simulation (`src/crm_system.py`, `src/external_email_ingest.py`)**: introduced native integrations for **Salesforce** and **Zendesk**. The simulation now tracks CRM account ownership, flags "at-risk" opportunities during incidents, and automatically escalates customer support tickets based on system health.
+- **High-Fidelity Meeting Transcripts (`src/normal_day.py`, `src/day_planner.py`)**: Added **Zoom** as a meeting medium for design discussions. Unlike Slack threads, Zoom produces verbatim Markdown transcripts that capture undocumented verbal decisions, creating intentional "knowledge gaps" for RAG evaluation.
+- **Synthetic Business Telemetry (`src/post_sim_artifacts.py`)**: Introduced a post-processing suite that generates deterministic **Datadog** metrics (latency/error spikes), **NPS surveys**, and **customer invoices** featuring SLA credits calculated directly from simulation incident duration.
+
+### Changed
+
+- **State Machine Grounding (`src/flow.py`, `src/memory.py`)**: Expanded the `SimEvent` bus to include CRM and meeting events. LLMs now receive `crm_summary` context during daily planning to ensure outbound sales emails and support responses align with the global organizational state.
+- **Advanced Social Graph Dynamics (`src/org_lifecycle.py`)**: Enhanced the employee departure logic. When an engineer leaves, the system now deterministically handles **CRM ownership lapses** alongside ticket reassignment and Dijkstra-based incident handoffs.
+- **Simulation Parameters (`config/config.yaml`)**: Updated default simulation length to 30 days and adjusted hire schedules for Janice (Day 7) and Reese (Day 20) to better stress-test mid-sprint transitions.
+
+### Fixed
+
+- **Email Signal Accuracy (`src/external_email_ingest.py`)**: Improved the external contact generator to pull from a larger pool of 14 sources (up from 7) and corrected account name resolution to favor active Salesforce records over static config defaults.
+- **PR Review Context (`src/memory.py`)**: Fixed a lack of historical depth in code reviews by implementing `context_for_pr_review`, which deterministically pulls prior comments and linked Jira updates into the LLM prompt.
+
+---
+
 ## [v1.2.7] — 2026-03-25
 
 ### Added

config/config.yaml

@@ -47,10 +47,10 @@ simulation:
   domain: "apexathletics.io"
   output_dir: "./export"
   db_name: "orgforge"
-  max_days: 60
+  max_days: 30
   start_date: "2026-03-02"
 
-  adhoc_confluence_prob: 0.3
+  adhoc_confluence_prob: 0.2
   aws_alert_prob: 0.4
   snyk_alert_prob: 0.2
   sprint_tickets_per_planning: 4
@@ -174,7 +174,7 @@ org_lifecycle:
   # events naturally once the roster context shows them as "still warming up".
   scheduled_hires:
     - name: "Janice"
-      day: 15
+      day: 7
       dept: "Engineering_Backend"
       role: "Backend Engineer"
       expertise: ["Python", "FastAPI", "PostgreSQL", "TitanDB"]
@@ -187,7 +187,7 @@ org_lifecycle:
       tenure: "new"
 
     - name: "Reese"
-      day: 35
+      day: 20
       dept: "Engineering_Backend"
       role: "DevOps Engineer"
       expertise: ["Kubernetes", "Terraform", "AWS", "Infrastructure"]
@@ -487,26 +487,15 @@ default_persona:
     opinions. Do not let it develop a strong voice or override the tone of named personas
     in the same scene.
 
-# ── EXTERNAL PERSONAS ─────────────────────────────────────────
-
-external_contacts:
-  - name: "AWS_Support"
-    display_name: "AWS Support"
-    org: "AWS"
-    role: "Support Engineer"
-    trigger_events: ["incident_opened", "fix_in_progress"]
-    trigger_health_threshold: 70 # only contacts AWS if system_health drops below this
-    internal_liaison: "Engineering" # which dept's lead gets the summary
-    summary_tone: "technical and reassuring, but noncommittal about SLA"
-
-  - name: "CustomerSuccess_Acme"
-    display_name: "Acme Corp (Customer)"
-    org: "Acme Corp"
-    role: "IT Director"
-    trigger_events: ["incident_opened"]
-    trigger_health_threshold: 60 # only surfaces for severe incidents
-    internal_liaison: "Sales"
-    summary_tone: "concerned about uptime, asking for ETA and root cause"
+# ── CRM ───────────────────────────────────────────────────────
+
+crm:
+  salesforce:
+    enabled: true
+    seed_accounts: true
+  zendesk:
+    enabled: true
+    link_to_incidents: true
 
 # ── INSIDER THREAT ────────────────────────────────────────────
 

src/confluence_writer.py

@@ -53,6 +53,7 @@
 from crewai import Task, Crew
 from memory import Memory, SimEvent
 from artifact_registry import ArtifactRegistry, ConfluencePage
+from utils.persona_utils import get_voice_card
 
 if TYPE_CHECKING:
     from graph_dynamics import GraphDynamics
@@ -295,7 +296,9 @@ def write_postmortem(
         artifact_time, _ = self._clock.advance_actor(on_call, hours=pm_hours)
         timestamp = artifact_time.isoformat()
 
-        backstory = self._persona(on_call, mem=self._mem, graph_dynamics=self._gd)
+        backstory = get_voice_card(
+            on_call, "design", mem=self._mem, graph_dynamics=self._gd
+        )
         related = self._registry.related_context(topic=root_cause, n=3)
         _qa_lead = next(
             (name for name, p in PERSONAS.items() if "QA" in p.get("expertise", [])),
@@ -393,16 +396,14 @@ def write_design_doc(
         chat_log = "\n".join(f"{m['user']}: {m['text']}" for m in slack_transcript)
         ctx = self._mem.recall_with_rewrite(raw_query=topic, n=3, as_of_time=timestamp)
         related = self._registry.related_context(topic=topic, n=3)
+        backstory = get_voice_card(
+            author, "design", mem=self._mem, graph_dynamics=self._gd
+        )
 
         agent = make_agent(
             role="Technical Lead",
             goal="Document technical decisions and extract an actionable ticket.",
-            backstory=self._persona(
-                author,
-                mem=self._mem,
-                graph_dynamics=self._gd,
-                extra="You just finished a Slack discussion and need to document decisions and assign follow-up work.",
-            ),
+            backstory=backstory,
             llm=self._planner,
         )
         task = Task(
@@ -596,28 +597,19 @@ def write_adhoc_page(
         expertise_str = ", ".join(expertise_list)
 
         seed_query = f"{resolved_author} {expertise_str} {daily_theme}"
-        # Tier 3: LLM-generated seed query benefits from HyDE rewrite.
-        # recall_with_rewrite degrades to context_for_prompt if no llm_callable
-        # is passed, so this is safe to land before the callable is wired in.
         topic_ctx = self._mem.recall_with_rewrite(
             raw_query=seed_query,
             n=3,
             as_of_time=self._clock.now(resolved_author).isoformat(),
         )
+        backstory = get_voice_card(
+            resolved_author, "design", mem=self._mem, graph_dynamics=self._gd
+        )
 
         topic_agent = make_agent(
             role="Content Planner",
             goal="Identify a unique documentation gap based on your expertise and org history.",
-            backstory=self._persona(
-                resolved_author,
-                mem=self._mem,
-                graph_dynamics=self._gd,
-                extra=(
-                    f"You are {resolved_author} from the {dept} department. "
-                    f"Your expertise includes: {expertise_str}. "
-                    f"You are deciding what to document today to provide the most value to the team."
-                ),
-            ),
+            backstory=backstory,
             llm=self._worker,
         )
 
@@ -662,19 +654,14 @@ def write_adhoc_page(
 
         ctx = self._mem.context_for_prompt(title, n=3, as_of_time=timestamp)
         related = self._registry.related_context(topic=title, n=4)
+        backstory = get_voice_card(
+            resolved_author, "design", mem=self._mem, graph_dynamics=self._gd
+        )
 
         writer_agent = make_agent(
             role="Corporate Writer",
             goal=f"Draft a {title} Confluence page.",
-            backstory=self._persona(
-                resolved_author,
-                mem=self._mem,
-                graph_dynamics=self._gd,
-                extra=(
-                    f"You are {resolved_author} from the {dept} department. "
-                    f"Your expertise includes: {expertise_str}. "
-                ),
-            ),
+            backstory=backstory,
             llm=self._planner,
         )
         task = Task(