fix(voice/consistency): vary stock formulas, vendor-balance orient.py, unify the loop

- Vary 11 instances of two boilerplate openers ("A generic X course…" /
  "Strip away X…") across 10 modules so they read as distinct, concrete prose;
  kept the few deliberate, voice-distinct uses; locked exemplars untouched.
- M23 orient.py: detect a vendor-balanced set of AI-instruction filenames
  (AGENTS.md/CLAUDE.md/GEMINI.md/.cursorrules/.cursor/rules/copilot-instructions)
  instead of singling out one vendor. Still runs.
- Render the collaboration loop consistently as seven stations
  (issue->branch->implementation->PR->review->merge->closed) in M25/M26 to match
  M11 and the syllabus.

Closes #48
Closes #49
Closes #51

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TfzV5QvtPDz8LJS3Pu5VLT

modules/25-autonomous-agents/README.md

@@ -17,8 +17,8 @@ purpose — each piece is a wall the autonomous agent has to land behind.
 - **Module 9** — issues as an agent's task specification, including the `ready` label and the idea of
   an agent as an *assignee*. An issue is the agent's input here.
 - **Module 6** — branches. The agent's work goes on a branch, never straight onto `main`.
-- **Modules 10 and 11** — the PR review gate and the full issue → branch → PR → review → merge → close
-  loop. The PR *is* the unit of supervision in this module.
+- **Modules 10 and 11** — the PR review gate and the full issue → branch → implementation → PR →
+  review → merge → close loop. The PR *is* the unit of supervision in this module.
 - **Modules 13 and 14** — tests and CI. The automated gate that runs on the agent's PR.
 - **Module 15** — security scanning as another gate on the same pushes. Autonomy makes this
   non-optional, not optional.
@@ -177,9 +177,8 @@ ask you to trust the model more. It asks you to trust your gates more, and to ha
 
 ## The AI angle
 
-A generic automation lesson would teach you to script a runner job. What's specific to AI here is
-that **the actor inside the job is non-deterministic and persuasive**, and that changes what
-"automation" has to mean:
+Scripting a runner job is ordinary automation. What's specific to AI here is that **the actor inside
+the job is non-deterministic and persuasive**, and that changes what "automation" has to mean:
 
 - **The output is a proposal, not a result.** A normal scheduled job (back up the database, rotate
   logs) you trust to *complete*. An agent job you trust only to *propose* — because its output is a