Magic Nalwa Khisa

Exploring the art of automation and AI-powered creativity.

Discover The Magic

Full Interview

Amazing Song

Speaker Introduction

Interview Highlights

Automation Workflows

Community Building Research Workflow

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HTTP Request (to receive community topic)

ChatGPT (for trend analysis on topic)

Google Sheets (to log trends)

Data Transformer (formatting data)

Error Handling (notify on data fetch failure)

Quality Control Node (verify data quality)

Notification Service (send summary to user)

Scheduled Trigger (daily report)

End Workflow

This workflow gathers insights on community topics and shares them with stakeholders. Pain points alleviated include time-consuming manual research and difficulty in tracking community interests.

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Content Calendar Management Workflow

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CSV File Reader (to import content ideas)

ChatGPT (generate content suggestions)

Google Calendar (add content reminders)

Data Formatter (format events)

Email Service (notify team of new content)

Error Handling (alert on calendar addition failure)

Quality Control Node (check for duplicate events)

Notification Service (confirmation of new entries)

Scheduled Trigger (monthly review)

End Workflow

This automation streamlines content planning and execution. Pain points alleviated include disorganized content scheduling and missed deadlines.

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AI Learning and Knowledge Extraction Workflow

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PDF File Reader (to upload book content)

Text Extractor (pull text from PDF)

ChatGPT (summarize key insights)

Notion (store summarized insights)

Data Formatter (structure for readability)

Error Handling (alert on PDF processing issues)

Quality Control Node (verify summary accuracy)

Notification Service (send summary to the learner)

Scheduled Trigger (weekly updates)

End Workflow

This workflow aids in consolidating knowledge from multiple books quickly. Pain points alleviated include inefficient reading and information overload.

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Community Engagement Analysis Workflow

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Social Media Monitor (track engagement metrics)

Data Aggregator (compile engagement data)

ChatGPT (analyze sentiment and feedback)

Google Sheets (log results)

Data Formatter (clean data for presentation)

Error Handling (alert on data collection failure)

Quality Control Node (evaluate analytical accuracy)

Visualization Tool (generate graphical reports)

Notification Service (send results to community leaders)

Scheduled Trigger (weekly analysis)

End Workflow

This automation provides insights into community engagement and feedback. Pain points alleviated include difficulty in tracking and interpreting user engagement trends.

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