Skip to main content

Elon Musk sent an email to the staff at Tesla with his 6 rules for productivity. Unsurprisingly, it leaked.

 Elon Musk sent an email to the staff at Tesla with his 6 rules for productivity. Unsurprisingly, it leaked.


Here they are:
1) Avoid large meetings
Large meetings waste valuable time and energy.
- They discourage debate
- People are more guarded than open
- There’s not enough time for everyone to contribute
Don’t schedule large meetings unless you’re certain they provide value to everyone.

2) Leave a meeting if you’re not contributing
If a meeting doesn’t require your:
- Input
- Value
- Decisions
Your presence is useless.
It’s not rude to leave a meeting.
But it’s rude to waste people’s time.

3) Forget the chain of command
Communicate with colleagues directly.
Not through supervisors or managers.
Fast communicators make fast decisions.
Fast decisions = competitive advantage.

4) Be clear, not clever
Avoid nonsense words and technical jargon.
It slows down communication.
Choose words that are:
- Concise
- To the point
- Easy to understand
Don’t sound smart. Be efficient.

5) Ditch frequent meetings
There’s no better way to waste everyone’s time.
Use meetings to:
- Collaborate
- Attack issues head-on
- Solve urgent problems
But once you resolve the issue, frequent meetings are no longer necessary.
You can resolve most issues without a meeting.
Instead of meetings:
- Send a text
- Send an email
- Communicate on a discord or slack channel
Don’t interrupt your team’s workflow if it’s unnecessary.

6) Use common sense
If a company rule doesn’t:
- Make sense
- Contribute to progress
- Apply to your specific situation
Avoid following the rule with your eyes closed.
Don’t follow rules. Follow principles.

Comments

Popular posts from this blog

Quality Assurance Engineer interview questions and answers

  Quality Assurance Engineer interview questions and answers   1.     Can you describe your experience with manual testing, and the methodologies you follow? Answer: "I have extensive experience with manual testing and am well-versed in various testing methodologies, such as black-box testing, grey-box testing, and white-box testing. I follow a systematic approach to testing, where I first identify the test cases, prioritize them based on the risk involved, and then execute them to ensure that the product meets the requirements." 2.     Can you describe your experience with automation testing, and the tools you have worked with? Answer: "I have experience with automation testing and have worked with various tools, such as Selenium, Appium, and TestComplete. I have also worked with programming languages, such as Java and Python, to write test scripts. I follow a data-driven approach to automation testing, where I first identify the test c...

Cloud Developer interview questions and answers

  Cloud Developer interview questions and answers   1.     Can you describe your experience working with public cloud platforms, such as AWS, Azure, or Google Cloud Platform? Answer: "I have extensive experience working with AWS, Azure, and Google Cloud Platform. I have used these platforms to build scalable and highly available cloud-native applications, leveraging services such as EC2, S3, Lambda, and Kubernetes. I have also used cloud-native development frameworks, such as serverless and microservices, to build cloud applications that can scale up and down automatically based on demand." 2.     Can you describe your experience building and deploying containers using Docker or other containerization technologies? Answer: "Containerization technologies, such as Docker, have become increasingly popular in recent years as a way to streamline application deployment and management. In my experience, I have built and deployed containers usin...

AI/ML Developer interview questions and answers

  AI/ML Developer interview questions and answers 1.     Can you describe your experience with AI/ML algorithms and techniques, such as deep learning, reinforcement learning, and supervised/unsupervised learning? Answer: "As an AI/ML developer, I have extensive experience with a variety of AI/ML algorithms and techniques, including deep learning, reinforcement learning, and supervised/unsupervised learning. I have used these techniques to build predictive models for a variety of applications, such as image and speech recognition, natural language processing, and recommender systems." 2.     Can you describe your experience with data preprocessing and feature engineering techniques, such as normalization, dimensionality reduction, and feature selection? Answer: "Data preprocessing and feature engineering are critical steps in the AI/ML pipeline, as they can significantly impact the accuracy and effectiveness of the final model. In my experienc...