Use python3 as the canonical command name course-wide (#104) (#105)

modules/25-autonomous-agents/README.md

@@ -256,7 +256,7 @@ out of the agent's `git add -A`, so the change you review in Part B is clean. Th
 
 ```bash
 # Simulate an agent that produces a BROKEN change, then run the gate on it:
-python agent_runner.py issue-to-pr issue-delete-command.md --simulate bad
+python3 agent_runner.py issue-to-pr issue-delete-command.md --simulate bad
 ```
 
 The orchestrator creates and switches to its own `agent/issue-delete-command` branch first (the same
@@ -270,7 +270,7 @@ reached `main`.
 ### Part B: See a good change land as a PR proposal
 
 ```bash
-python agent_runner.py issue-to-pr issue-delete-command.md --simulate good
+python3 agent_runner.py issue-to-pr issue-delete-command.md --simulate good
 ```
 
 This time the planted change is correct. The gate passes, the script commits to the branch and prints
@@ -284,7 +284,7 @@ stops at a PR; it never merges.
 ### Part C: Run the self-healing loop
 
 ```bash
-python agent_runner.py self-heal --simulate bad
+python3 agent_runner.py self-heal --simulate bad
 ```
 
 The orchestrator switches to its own `agent/self-heal` branch (again, you direct the automation, not
@@ -302,7 +302,7 @@ Two ways to go from simulation to a genuine autonomous run:
 
    ```bash
    export AGENT_CMD='your-agent-cli --print --prompt-file {prompt_file}'   # your tool's one-shot mode
-   python agent_runner.py issue-to-pr issue-delete-command.md
+   python3 agent_runner.py issue-to-pr issue-delete-command.md
    ```
 
    The script builds the prompt from the issue **and** your committed config (Module 5), runs your