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Welcome to Product Monk, a 3x/week newsletter where we share the case studies of the most exciting tech products.

We wrote these three stories last week, hope you love them ❤️:

• What Paddle boarding, Chess, and Haiku Can Teach Us About Building Great Products?

• Why did Google Jamboard Fail?

• WhatsApp Channel's Product Marketing Technique

Why Everyone's doing "Co-Pilot"?

Recently, several products have launched their co-pilot versions. Co-pilots are generally used to automate tasks, identify patterns, and predict future trends.

So, does this mean the actual product isn’t good enough? Or, if it’s really so worth it, why isn’t the co-pilot itself the main product? So many questions!

Today’s piece is going to uncover if this strategy of co-piloting products is really worth it. Is this going to help products of today, stay current, and a lot more…

Time to dive in 🤿 

What on Earth is a Product Co-pilot?

A product co-pilot is a software tool that is designed to assist users with the development and maintenance of products. Product co-pilots can be used to automate tasks, identify patterns, and predict future trends. This can lead to products that are more efficient, effective, and personalized.

Product co-pilots are often powered by artificial intelligence (AI). AI allows product co-pilots to learn from user behavior and to adapt to changing needs. This makes them more useful and valuable over time.

Some examples of product co-pilots include:

• GitHub Copilot is a code completion tool that helps programmers to write code faster and more accurately.

• Microsoft Copilot is a platform that provides users with real-time assistance with tasks such as writing documents, creating presentations, and sending emails.

• Google AI Test Kitchen is a platform that helps developers write and run automated tests more efficiently.

• Amazon SageMaker Canvas is a no-code machine learning platform that helps businesses build and deploy machine learning models without having to write any code.

So, What’s the Difference?

The main difference between a product's co-pilot and its normal version is that the co-pilot version has additional features that are designed to assist users with the development and maintenance of products. These features can include:

Code completion and generation: Product co-pilots can help users write code faster and more accurately by suggesting code completions and by generating code from natural language descriptions. This can be especially helpful for new programmers or for programmers who are working on a new language or framework.

Example: A product co-pilot might suggest code completions for functions, methods, variables, and other programming constructs. It might also be able to generate code from natural language descriptions, such as "write a function that takes a list of numbers and returns the average."

Error detection and correction: Product co-pilots can help users to identify and correct errors in their code before they are published or released. This can be done by checking for syntax errors, type errors, and other common errors.

Example: A product co-pilot might warn a user about a potential syntax error or about a variable that is being used but not declared. It might also be able to suggest fixes for these errors.

Pattern identification and prediction: Product co-pilots can help users to identify patterns in their data and to predict future trends. This information can be used to make better decisions about product development and maintenance.

Example: A product co-pilot might be able to identify patterns in customer behavior or in product usage. It might also be able to predict future trends, such as which products are likely to be popular in the future.

Personalization: Product co-pilots can be personalized to the individual needs of each user. This makes them more useful and valuable over time.

Example: A product co-pilot might be able to learn a user's coding style and preferences. It might also be able to learn about the specific products and projects that a user is working on.

In addition to these features, product co-pilots may also include other features that are specific to the product. For example, a product co-pilot for a software development tool might include features for debugging, testing and deploying code. A product co-pilot for a design tool might include features for prototyping, wireframing, and creating user interfaces.

Are Co-Pilots the New Normal?

Product co-pilots are the new normal because they offer a number of benefits that can help businesses to be more competitive and successful. These benefits include:

• Increased productivity and efficiency: Product co-pilots can automate many tasks that are currently performed by humans, such as code completion, error detection, and pattern identification. This can free up human workers to focus on more creative and strategic tasks.

  A study by GitHub found that developers using GitHub Copilot were able to write code up to 65% faster and with 32% fewer errors. A similar study by Microsoft found that developers using Microsoft Copilot were able to write code up to 30% faster and with 20% fewer errors.

• Improved quality and accuracy: Product co-pilots can help to improve the quality and accuracy of products by identifying and correcting errors before they are published or released. They can also help to ensure that products are consistent with best practices and standards.

  A study by Google found that AI-powered code completion tools can detect and correct up to 90% of common coding errors. A similar study by Amazon found that AI-powered code review tools can identify up to 80% of security vulnerabilities.

• Reduced costs: Product co-pilots can help to reduce the costs of developing and maintaining products by automating tasks and improving quality. This can lead to significant savings in terms of time and money.

  A study by McKinsey found that AI can automate up to 50% of all tasks in the software development process. This can lead to significant savings in terms of time and money.

• Enhanced user experience: Product co-pilots can help to personalize the user experience and to make products more engaging and satisfying for users. This can lead to higher customer satisfaction and loyalty.

  A study by Forrester found that companies that use AI to personalize the user experience see, on average, a 15% increase in customer satisfaction and a 10% increase in revenue.

In addition to these benefits, product co-pilots are also becoming increasingly popular because they are becoming more affordable and accessible. As a result, businesses of all sizes are now able to take advantage of the benefits that product co-pilots have to offer.

🧃Juicy reads to check out

This section includes some relevant articles/videos, people to check out, and links you might find interesting from around Product management.

👉🏻 The Product Operating Model by Marty Cagan. (Link)

👉🏻 Empowering Growth through Product Metrics. (Link).

👉🏻 Merge’s Path to Product-Market Fit: The Importance of Founder-led Sales (Even for a Self-Serve Product). (Link)

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