This is a submission for the Runner H "AI Agent Prompting" Challenge
What I Built
I created an Automated Research and Insight Reporting workflow using Runner H that autonomously gathers the latest information on a specified topic from multiple trusted sources, summarizes key insights, categorizes findings, and compiles a well-structured report. The final report is automatically saved to Google Docs (or Notion) and shared with the team via Slack or email, complete with scheduled recurring updates.
This workflow solves the time-consuming and repetitive task of manual research and report generation, enabling professionals, researchers, and teams to stay informed effortlessly with up-to-date, curated insights delivered directly to their preferred platforms.
Demo
the workflow in Runner H dashboard, the generated report in Google Docs, and Slack notification.*
(If you have a video, embed it here using the markdown embed syntax)
How I Used Runner H
Runner H’s multi-agent orchestration capabilities were key to this workflow:
- Multi-step task decomposition: I defined subtasks for web scraping, API querying, summarization, categorization, document generation, and notifications.
- Integration with external tools: Connected Runner H to Google Docs for report creation, Slack for team notifications, and calendar apps for scheduling recurring reports.
- Context-aware memory: Runner H maintained context across all subtasks, ensuring coherent summaries and consistent report formatting.
- Autonomous execution: Once triggered, the workflow runs end-to-end without manual intervention, freeing users from repetitive research tasks.
Instructions to replicate:
- Set your target research topic and preferred sources within the Runner H prompt.
- Connect your Google Docs, Slack, and calendar accounts via Runner H integrations.
- Trigger the workflow manually or schedule it to run automatically on a recurring basis.
- Receive the summarized research report directly in your team’s Slack channel and Google Docs folder.
Use Case & Impact
This solution is ideal for:
- Researchers and analysts who need to monitor fast-moving fields like AI, biotech, or finance.
- Product managers and marketers seeking competitive intelligence and industry trends.
- Teams and executives who want concise, actionable insights without spending hours on manual research.
By automating the entire research-to-report process, this workflow saves hours of tedious work weekly, reduces human error in data collection, and ensures timely, consistent delivery of high-quality insights. It transforms how knowledge workers stay informed, enabling smarter decisions and faster innovation.
Core Prompt for Runner H
1. Search the internet and specific trusted sources for the latest articles, papers, blog posts, and news related to [INSERT TOPIC, e.g., "Artificial Intelligence advancements"] published within the last [time frame, e.g., 7 days].
2. Prioritize reputable sources such as TechCrunch, Wired, arXiv, Medium, GitHub Trending, and relevant RSS feeds.
3. Extract key points, trends, and breakthroughs from each source, summarizing them in 2-3 sentences.
4. Categorize the findings into logical sections (e.g., Research Papers, Industry News, Tools & Projects).
5. Compile these summaries into a single cohesive report with:
- A clear and engaging title
- An introduction outlining the report's scope
- Well-structured sections grouping related content
- Concise, reader-friendly language suitable for [target audience, e.g., tech professionals]
6. Format the final report as a Markdown or Google Doc file, ready for distribution.
7. Save the report in [Google Drive/Notion/other] and notify the team via Slack/email with the report link.
8. Schedule a recurring calendar event for weekly/monthly report delivery.
Social Love
Thank you to the Runner H team for this exciting challenge! Looking forward to seeing how the community innovates with AI agents.
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