GitHub Copilot is presented as an AI pair programmer, that plugs into the user's editor. It then turns natural language prompts into code, offers multi-line function suggestions, speeds up test generation, filters out common vulnerable coding patterns, and blocks suggestions matching public code.
$10
per month
Google Gemini
Score 7.4 out of 10
N/A
Google Gemini (formerly Bard) is an AI assistant, presented as a creative and helpful collaborator. Gemini for Workspace is available via two plans: a Gemini Enterprise add-on, and a Gemini Business add-on.
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.
Google Gemini AI features a Deep Research feature that helped us conduct thorough product research. We wanted to minimize the costs incurred by using SSL certificates in our organization, but we lacked knowledge on the subject. Google Gemini Deep Research did a thorough analysis and suggested ways to cut costs by switching vendors and using DV-type and/or wildcard SSL certificates. We also use Google Gemini for assistance during software development. However, Google Gemini seems to have limitations when suggesting code snippets for the Microsoft ecosystem.
Deep research for getting first business research draft from Gemini, post which i use series of prompts to improve it and use my understanding to refine it further
Canvas to produce structured business topic research and newsletter. Direct edits to the sections and making client ready reports
Learning mode to get help on step by step automation of AI workflows
Currently the document database caps out at 10, requiring us to condense some of our policies
It's large context window is a blessing and a curse. Sometimes it stops generating half way through a very ambitious request as it delivers page after page of content
There is no way to share Gems currently, so we have to publish guides to our employees on how to best configure them
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.
It is simple, has the same standard industry format, all the tools are accessible and recognizable. Whenever we are in the browser we can switch from one request to another while the first is still running. Little hallucination and the context window has no competitor on the market right now. The pricing is also the biggest advantage.
I used Cursor AI as well, along with CoPilot. Curson has its own AI editor, but Copilot works with almost every code editor. So I don't need to depend on just one editor, and I get the flexibility to choose my own editors. The billing is also good and doesn't require many coupons to write prompts.
Gemini seems very simple to use, veyr similar to ChatGPT, I wish they did have a capability such as ChatGPT projects one, so one can separate topics easily, it's very customizable, where I believe it defeats the others is that, is already very simple to use all of Google ecosystem, such as Drive, docs, sheets and else
