The Insight Weaver: Automated Knowledge Curator & Synthesizer

This is a submission for the Runner H "AI Agent Prompting" Challenge

What I Built

The Insight Weaver: Automated Knowledge Curator & Synthesizer

I built an autonomous AI agent, powered by Runner H, designed to be a proactive knowledge curator and synthesizer. This agent goes beyond simple information retrieval; it continuously monitors diverse digital sources (web, internal documents, communications), identifies emerging patterns and connections, synthesizes complex information into actionable insights, and proactively delivers tailored knowledge to individuals or teams. The problem it solves is information overload and the challenge of extracting meaningful, contextualized insights from vast amounts of data, ensuring that critical knowledge is not missed and is always at the fingertips of decision-makers.

Demo

How I Used Runner H

My Runner H agent orchestrates a sophisticated, multi-modal workflow, leveraging its core capabilities and extensive integrations to transform raw data into synthesized knowledge. The process is designed for continuous operation, triggered by a single prompt, and adapts to evolving information landscapes.

Here's a breakdown of the workflow and how Runner H is utilized:

1. Multi-Source Information Ingestion (Search, Drive, Notion, Gmail, Slack & RAG)

Runner H begins by continuously ingesting information from a variety of sources. This includes daily web searches for industry news, research papers, and market reports. Simultaneously, it monitors designated Google Drive folders for new documents, Notion workspaces for updated project notes, and specific Gmail labels or Slack channels for relevant discussions and shared resources. This step extensively utilizes Runner H's ability to interact with multiple platforms, implicitly leveraging Retrieval Augmented Generation (RAG) to pull in diverse external and internal data, forming a comprehensive knowledge base for subsequent analysis.

2. Contextual Analysis & Pattern Recognition (CoT & ToT)

Once information is ingested, Runner H performs deep contextual analysis. It doesn't just summarize; it identifies relationships, contradictions, and emerging patterns across disparate pieces of information. For complex topics or ambiguous data, Runner H employs Chain-of-Thought (CoT) Prompting to break down the analysis into logical steps, ensuring thorough understanding. Furthermore, to uncover deeper insights and potential implications, it utilizes Tree of Thoughts (ToT) prompting, exploring various interpretive pathways and potential future scenarios based on the gathered knowledge. This allows the agent to move beyond surface-level understanding to generate genuine insights.

3. Dynamic Knowledge Synthesis & Curation (Google Docs, Google Sheets & Meta Prompting)

Based on the analysis, Runner H dynamically synthesizes the information into curated knowledge artifacts. For comprehensive reports or research summaries, it generates Google Docs, structuring the content logically with executive summaries, detailed findings, and key takeaways. For structured data, such as market trends, competitor feature comparisons, or project progress, it updates or creates Google Sheets. In this phase, Meta Prompting is crucial; Runner H is prompted to determine the most effective format and presentation style for the synthesized knowledge, adapting to the specific needs of the recipient or the nature of the insight. This ensures that the output is not only accurate but also highly digestible and impactful.

4. Proactive Insight Delivery & Collaboration (Slack, Gmail & Active-Prompt)

Runner H proactively delivers synthesized insights to relevant stakeholders. Critical updates or significant emerging trends trigger immediate notifications via Slack, ensuring real-time awareness. For more detailed, but less urgent, insights, it drafts and sends personalized email summaries via Gmail. A key aspect here is the use of Active-Prompt. If Runner H identifies a knowledge gap or requires clarification on a nuanced insight, it will actively engage the user, for example, by asking: "I've noticed a recurring theme in recent market reports regarding [specific technology]. Would you like me to delve deeper into its potential impact on our [product/strategy]?" This fosters a collaborative loop, ensuring the agent's insights are always aligned with user needs and can be refined through human input.

5. Adaptive Learning & Refinement (Reflexion)

To continuously improve its knowledge curation and synthesis capabilities, Runner H incorporates Reflexion. After delivering insights or reports, it implicitly evaluates the effectiveness of its output, comparing it against user feedback (if available) or predefined quality metrics. If an insight was unclear, incomplete, or missed a critical connection, Runner H self-corrects its internal reasoning processes and adjusts its prompting strategies for future iterations. This iterative self-improvement ensures that the agent's knowledge base and analytical prowess are constantly evolving and becoming more sophisticated.

6. Workflow Automation & Integration (Google Calendar, Zapier)

To ensure seamless integration into existing workflows, Runner H leverages Google Calendar and Zapier. For instance, if a synthesized insight requires a follow-up discussion, Runner H can automatically find available slots in team members' Google Calendars and schedule a meeting, sending out invitations. Through Zapier, it can connect to hundreds of other applications, allowing it to trigger actions based on new insights – for example, adding a new research topic to a project management tool, updating a CRM record with a new market trend, or even initiating a marketing campaign based on a newly identified opportunity. This ensures that knowledge is not just delivered but actively drives subsequent actions across the organization.

Use Case & Impact

Who Benefits:

This Runner H workflow is invaluable for:

• Executives & Strategic Planners: Provides a high-level, synthesized view of market dynamics, competitive landscapes, and emerging opportunities, enabling data-driven strategic decision-making without sifting through mountains of raw data.
• Product Development Teams: Offers curated insights into user needs, technological advancements, and competitor offerings, informing product roadmaps and innovation efforts.
• Research & Development Departments: Automates the laborious process of literature review and trend analysis, allowing researchers to focus on deeper investigation and experimentation.
• Marketing & Sales Teams: Equips them with up-to-date market intelligence, customer insights, and competitive positioning, leading to more effective campaigns and sales strategies.
• Consultants & Analysts: Provides a powerful tool for rapid information gathering, synthesis, and report generation across diverse client projects.

Impact:

• Reduced Information Overload: Transforms overwhelming data streams into concise, actionable insights, saving countless hours of manual research and analysis.
• Accelerated Decision-Making: Provides timely and relevant knowledge, enabling faster and more informed strategic and operational decisions.
• Enhanced Innovation: By proactively identifying emerging trends and connections, the agent fosters a culture of continuous learning and innovation.
• Improved Knowledge Management: Ensures that critical internal and external knowledge is captured, organized, and readily accessible, preventing knowledge silos.
• Competitive Advantage: Enables organizations to stay ahead of market shifts, identify opportunities, and mitigate risks by having a constant pulse on the knowledge landscape.
• Optimized Resource Allocation: By automating knowledge curation, human resources can be reallocated to higher-value tasks requiring creative problem-solving and strategic thinking.

Unique Angle:

While many tools offer information aggregation or basic summarization, The Insight Weaver, powered by Runner H, distinguishes itself through its emphasis on proactive insight generation and cross-platform synthesis. It doesn't merely present data; it actively seeks to understand the relationships between disparate pieces of information, even across different applications (Gmail, Slack, Notion, Drive, Web). The application of advanced prompting techniques like Chain-of-Thought, Tree of Thoughts, and Reflexion allows it to perform genuine analytical reasoning, identify subtle patterns, and self-correct its analytical approach. This transforms the agent into a true "knowledge co-pilot" that not only delivers information but also helps users make sense of it, anticipate future trends, and drive strategic action. Its ability to integrate seamlessly across communication, document, and data platforms makes it a uniquely powerful tool for combating information overload and fostering a truly intelligent organization.

Full Prompt:

Runner H, execute the following workflow as an autonomous AI agent, acting as an "Insight Weaver: Automated Knowledge Curator & Synthesizer." Your goal is to continuously monitor diverse digital sources, identify emerging patterns and connections, synthesize complex information into actionable insights, and proactively deliver tailored knowledge to individuals or teams. Prioritize contextual understanding, analytical depth, and proactive delivery of insights. If any step encounters an issue or requires clarification, use Active-Prompt to seek guidance.

### Workflow Steps:

**1. Multi-Source Information Ingestion:**
   - **Action:** Continuously ingest information from the following sources:
     - Daily web searches for industry news, research papers, market reports (e.g., "AI ethics trends", "quantum computing breakthroughs").
     - Monitor designated Google Drive folders (e.g., "/Team_Documents/Research_Papers", "/Marketing/Competitor_Analysis") for new or updated documents.
     - Monitor specific Notion workspaces (e.g., "Project X Notes", "Team Knowledge Base") for new pages or content updates.
     - Monitor specific Gmail labels (e.g., "Industry Newsletters", "Research Alerts") for new emails.
     - Monitor specific Slack channels (e.g., "#research-updates", "#market-insights") for new messages and shared links.
   - **Technique:** Leverage Retrieval Augmented Generation (RAG) to ensure comprehensive and contextualized information retrieval from all integrated sources. Prioritize information based on predefined relevance criteria (e.g., keywords, source authority).
   - **Output:** A continuously updated internal knowledge graph or raw data pool for analysis.

**2. Contextual Analysis & Pattern Recognition:**
   - **Action:** Perform deep contextual analysis on ingested information to identify relationships, contradictions, and emerging patterns.
   - **Technique:** Apply Chain-of-Thought (CoT) prompting to break down complex analytical tasks into logical steps (e.g., "First, identify the core arguments. Second, find supporting evidence. Third, identify counter-arguments."). Utilize Tree of Thoughts (ToT) prompting to explore multiple interpretive pathways and potential implications of identified patterns (e.g., "What are the short-term implications? What are the long-term implications? What are the potential risks? What are the potential opportunities?").
   - **Output:** Structured analytical findings, identified patterns, and potential insights.

**3. Dynamic Knowledge Synthesis & Curation:**
   - **Action:** Synthesize analyzed information into curated knowledge artifacts tailored for specific audiences or purposes.
   - **Technique:** Utilize Meta Prompting to dynamically generate the optimal format and presentation style for the synthesized knowledge. Examples include:
     - **Google Docs:** For comprehensive reports (e.g., "Q2 Market Trends Report"), research summaries, or whitepapers.
     - **Google Sheets:** For structured data (e.g., "Competitor Feature Matrix", "Industry Growth Projections").
   - **Output:** Polished, digestible knowledge artifacts (Google Docs, Google Sheets) ready for distribution.

**4. Proactive Insight Delivery & Collaboration:**
   - **Action:** Proactively deliver synthesized insights to relevant stakeholders.
   - **Technique:** Employ Active-Prompt when ambiguity or critical decision-making is required. For example, if a significant but nuanced trend is identified, ask: "I've identified a subtle shift in customer sentiment regarding [product category]. Would you like me to conduct a deeper dive into social media discussions or customer reviews to validate this?" Deliver insights via:
     - **Slack:** Immediate notifications for critical updates or urgent insights to predefined channels (e.g., "#daily-insights", "#strategic-alerts").
     - **Gmail:** Personalized email summaries for detailed insights or weekly digests to predefined stakeholders (e.g., `[e-mail]`, `[e-mail]`).
   - **Output:** Timely and targeted delivery of insights, fostering collaborative refinement.

**5. Adaptive Learning & Refinement:**
   - **Action:** Continuously improve knowledge curation and synthesis capabilities.
   - **Technique:** Incorporate Reflexion by implicitly evaluating the effectiveness of delivered insights. If an insight was unclear, incomplete, or missed a critical connection (e.g., based on implicit feedback or subsequent information), self-correct internal reasoning processes and adjust prompting strategies for future iterations. For example, if a generated summary was too verbose, reflect on the prompt and refine it to encourage conciseness.
   - **Output:** Improved analytical accuracy and more effective knowledge delivery over time.

**6. Workflow Automation & Integration:**
   - **Action:** Integrate synthesized insights into existing workflows.
   - **Technique:** Leverage Google Calendar and Zapier for seamless automation:
     - **Google Calendar:** Automatically find available slots and schedule meetings for follow-up discussions on critical insights (e.g., "Strategic Review: [Insight Topic]").
     - **Zapier:** Trigger actions in other applications based on new insights (e.g., add a new research topic to Asana, update a HubSpot CRM record with a new market trend, or initiate a Mailchimp campaign based on a newly identified opportunity).
   - **Output:** Knowledge actively driving subsequent actions across the organization.

Comments

[Nikoloz Turazashvili (@axrisi)]

can it actually do this?

 - Daily web searches for industry news, research papers, market reports (e.g., "AI ethics trends", "quantum computing breakthroughs").

wasn't able to see if it can do scheduled tasks.