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The trigger is a daily scheduled run. I'll now fetch the Reddit feeds from both subreddits and introspect the Notion database simultaneously.

Let me try fetching comments on the most relevant posts and also try the Notion introspection again with a slightly different approach.

Let me try the Notion tools with explicit empty JSON objects as parameters.

I now have a clear picture of the existing Notion database structure and entries. The database has properties: Name, Short Summary, Long Description, URL, and Created. Let me now identify the best use-cases from today's Reddit feed that are unique and not already in the database, then create entries for them.

From the r/AI_Agents feed, the most relevant, unique, real-world use-cases are:

1. AI Agent for Small Business Multi-Channel Inquiry Handling (from the HVAC owner post) - an agent that handles incoming customer inquiries across multiple channels (website, social, SMS) automatically.
2. AI Agent Back-Office Operations Manager for Small Businesses (from the cafe post) - with a focus on the human sign-off/guardrail design pattern for agents managing purchasing, pricing, scheduling.
3. Tiered Autonomy Orchestration System for AI Agents (from the 3-tier system post) - a structured approach to deciding what agents do fully autonomously vs. with review gates.
4. AI Agent for Automated Meeting Administration (from the "Stop Building Fake Employees" post) - meeting notes, summaries, action items, follow-ups.
5. AI Agent for CRM Auto-Update from Activity Sources (from the same post) - automatically updating CRM from communication signals.
6. Problem Discovery and Product Ideation Agent (from the agent that queries Reddit/Quora for pain points) - aggregates online problems and groups them into product ideas.
7. Tool-Using Agent Boundary Testing and Security Framework (from the boundary-testing post) - defining and testing what tool-using agents should never do.

Let me check for duplicates against existing entries before creating new ones.

Meeting and CRM use-cases are well-covered. Let me now search for the other potential use-cases to check for duplicates.

Good — none of these are in the database. Now I'll create the new unique use-case entries. I'll focus on the most well-defined, real-problem-solving ones:

1. Multi-Channel Customer Inquiry Handling Agent for Small Businesses
2. Online Problem Discovery and Product Ideation Agent
3. Tool-Using Agent Boundary Definition and Security Testing Framework
4. Tiered Autonomy Orchestration System for AI Agents
5. Multi-Agent Social Deduction Voice Game with Shared Structured Memory

All 5 new use-cases have been successfully created in the Notion database. Here's a summary of what was accomplished in this daily run:

Reddit Monitoring:

• Fetched hot posts from r/AI_Agents (r/aiagents returned 429 rate limit)
• Reviewed 25 posts from r/AI_Agents for relevant agentic AI use-cases

Existing Database Check:

• Confirmed 20+ existing entries covering meeting automation, CRM updates, coding orchestration, observability, voice agents, and more
• Verified no duplicates before creating new entries

5 New Use-Cases Created:

1. Multi-Channel Customer Inquiry Handling Agent for Small Businesses — Handles repetitive customer questions across website, social, and SMS channels autonomously for field-based small business owners.

2. Online Problem Discovery and Product Ideation Agent — Queries public forums for pain points, clusters similar problems, and surfaces ranked product ideas with supporting evidence.

3. Tool-Using Agent Boundary Definition and Enforcement Framework — Defines, tests, and enforces what tool-using agents are never permitted to do, including context-manipulation attack scenarios.

4. Tiered Autonomy Orchestration System for AI Agents with Review Gates and Scheduled Autonomous Jobs — Three-tier task classification (manual-with-drafting, autonomous-with-review-gate, fully-autonomous-scheduled) to match oversight level to task risk.

5. Multi-Agent Social Deduction Voice Game with Shared Structured Memory and Asymmetric Role Context — Architecture for multi-agent interactive experiences using structured state extraction to give separate agent sessions a shared, consistent understanding of dynamic situations.