Codespell.ai vs. GitHub Copilot

Any project development or optimisation scenarios

Copilit is fantastic at the following: 1. Solving simple, well-defined problems, such as implementing an algorithm, manipulating a data structure, or string manipulation and regex. 2. Implementing simple APIs that are mainly CRUD in nature, with moderate business logic inside them, which may involve some processing or passing the data through an algorithm. 3. Implementation of well-defined activities, such as implementing a connection to an Oracle DB using Hibernate or JDBC, or implementing boilerplate code for a backend service to listen to Kafka events. It is not that great when it comes to understanding and implementing code in a proprietary DSL. It struggles when implementing a major feature across a complex codebase. I believe developers should also adopt the trust-but-verify paradigm when expecting highly secure or regulated code from GitHub Copilot.

Incentivized

• Codespell.ai explains code with simplicity
• Codespell.ai gives function documentation
• Codespell.ai reads the current file and responses based on the type/tech of the file

• Make code development faster and quicker.
• Helps write better code standards for projects.
• Provide the latest functions from the technology.
• Notifies about the deprecated functions.

Incentivized

• From my experience, I noticed a couple of areas that could be improved. For instance, if we make a small mistake while the response is generating, it would be helpful to have an option to pause or stop it midway, similar to ChatGPT
• Second, sometimes while explaining or giving alternate/better solutions, it ends up writing the same code as its reading from the current file.

• The only issue I faced is the context token size, it can be increase.
• Sometime with agent mode it takes too much time, which can be reduced but I understand it also depends on the complexity of the given task.

Incentivized

Easy to integrate and response almost don't need manual changes

Easy to integrate and easy to implement

I feel that GitHub Copilot's overall usability is good due to its tight integration with Visual Studio and the workspace. However, developers expect greater ease of use, as there is a learning curve to realize productivity gains with the tool fully. I think there is room for improvement in GitHub Copilot's UI integration within Visual Studio.

Incentivized

Its ease of use and flexibility across documentation, code understanding

I attended the training

Details in response is in full details

It is useful that copilot integrates so well with vscode, which is a very common IDE. I used Tabnine for a little while but it was not that intuitive, and did not seem as helpful as GitHub copilot was. I have enjoyed GitHub copilot a lot, especially the ease of hitting the tab key and seeing quick progress in my tasks.

Incentivized

• Writing code time has reduced.
• Different technologies have different coding standards, and it manages them.

• Our ROI of the purchase of Copilot was met in less than a day. The timesave cannot be overstated
• Programmer boredom/dissatisfaction is down because of less repetetive crud work.

Incentivized