Create deep technical newsletters explaining the tyingshoelaces agentic mesh architecture with Rust code walkthroughs and architecture diagrams. Build a technical audience by documenting production agentic systems.
Prerequisites
Load the Session Playbook first. Verify your session and profile before starting.
IMPORTANT: NEVER start, stop, or restart services. The API is already running.
CRITICAL: Context Management
New content = New context. ALWAYS. See the Contexts Playbook for full context management commands.
WRONG: Reusing substack-general context for multiple issues
RIGHT: substack-extension-traits, substack-mcp-architecture, substack-job-scheduling (one context per issue)
CRITICAL: One Step = One Message
| Step | Action | Separate Message? |
|---|---|---|
| Step 3 | Plan | YES |
| Step 4 | Research | YES |
| Step 5 | Create | YES |
| Step 6 | Image | YES |
Step 1: Create a FRESH Context
// MCP: systemprompt_cli
{ "command": "core contexts new --name \"substack-[topic-slug]\"" }
Step 2: Review Performance
// MCP: systemprompt_cli
{ "command": "analytics content stats --since 30d" }
Step 3: Plan the Newsletter Issue
Focus on a specific component of the agentic mesh architecture.
Step 4: Research
// MCP: systemprompt_cli
{ "command": "admin agents message substack -m \"Research this architecture component.\" --context-id \"$CONTEXT_ID\" --blocking --timeout 120" }
Step 5: Create Content
// MCP: systemprompt_cli
{ "command": "admin agents message substack -m \"Create the newsletter with Rust code walkthroughs.\" --context-id \"$CONTEXT_ID\" --blocking --timeout 300" }
Step 6: Generate Diagrams
// MCP: systemprompt_cli
{ "command": "admin agents message substack -m \"Generate architecture diagrams.\" --context-id \"$CONTEXT_ID\" --blocking --timeout 60" }
Step 7: Publish and Verify
// MCP: systemprompt_cli
{ "command": "infra jobs run blog_image_optimization" }
{ "command": "infra jobs run publish_content" }
{ "command": "cloud sync local content --direction to-disk --source substack -y" }
Step 8: Update AI Provenance (MANDATORY AFTER CRUD)
CRITICAL: After ANY content CRUD operation (Create, Read, Update, Delete), agents MUST update the AI Provenance metadata.
AI Provenance is rendered in the content template as a transparency block showing readers how the content was created.
8.1 Update Provenance via CLI
// MCP: systemprompt_cli - Set provenance fields
{ "command": "core content edit [slug] --source substack --set agent=substack --set agent_summary=\"Created newsletter: [Title] - [Why]\" --set category=\"Architecture Deep Dive\"" }
Verify provenance is set:
// MCP: systemprompt_cli
{ "command": "core content show [slug] --source substack" }
8.2 Agent Summary Guidelines
The agent_summary is displayed as "Why This Was Created". It should:
- Be concise (1-2 sentences)
- Explain the PURPOSE, not just the action
- Include the content title
- Reference the architecture component if relevant
GOOD: "Created newsletter: Extension Traits Deep Dive - explaining the trait system for building custom extensions."
BAD: "Created newsletter" (too vague)
Provenance is NOT optional. All AI-generated content MUST have complete provenance metadata.
Content Types
| Type | Length | Use Case |
|---|---|---|
substack_newsletter |
2,000-3,500 words | Technical deep dives |
Format Requirements
- Rust code examples with annotations
- Architecture diagrams
- Production context and lessons
- British English
Troubleshooting
| Issue | Solution |
|---|---|
| Content not created | Verify with core content search |
| Agent says "created" but doesn't exist | Create a NEW context |