Since its release, Anthropic’s Claude 3 has been shaking the tech industry upside down with its groundbreaking features and unlimited potential. The tool is being highly talked about, and tech enthusiasts worldwide can’t help but appreciate how Claude 3 has proven useful to them in various ways.
So, how can Software Developers make the most out of Claude 3? We tested Claude 3 for ourselves and will explore everything we found in-depth in this article. Please note that we tested the free Sonnet version, as it’s widely available to the public. So, let’s get right into it!
1) Claude 3 Solving a DSA Problem
We tested Claude 3’s Sonnet version and asked it to solve a difficult DSA question regarding the in-order successor in a binary tree. This was the question input that we gave: “Write an iterator class for finding the in-order successor in a Binary Tree.“
To our surprise, Claude 3 Sonnet did an excellent job in solving the problem. Not only did it provide us with a Python version of the code solution, but it even provided us with an explanation of the implementation along with an example of usage.
Asked Claude 3 Sonnet to write an iterator class for finding the inorder successor in a Binary Tree. The results are astonishing.#Claude3 #DSA #AI pic.twitter.com/lFvpmW6tdM
— Xenesis26 (@xenesis26) April 1, 2024
It also showed us what the output would be if we ran the code. We decided to run the code and the output completely matched with what Claude 3 Sonnet had stated.
So, Claude 3 is highly capable when it comes to solving DSA questions using Python and a Dynamic Programming approach. Software Developers and aspiring programmers can highly make use of Claude 3 when they encounter difficult questions.
Till now programmers had a hard time solving and debugging such questions but Claude 3 is here to change the scene completely.
2) Providing Optimized Solutions
We continued to ask Claude 3 Sonnet, to provide a better solution to the iterator class problem. Sonnet surprisingly provided us with a better alternative, even stating how this approach was better than the previous approach, and also going into details about the differences in the time complexities.
Just like before Claude also explained the code implementation and also provided an example of usage. Interestingly, the output was also the same as before.
Claude 3 is even efficient in providing optimized code solutions.#Claude3 #DSA pic.twitter.com/10EFRAgMfo
— Xenesis26 (@xenesis26) April 1, 2024
In the world of coding, it is important to constantly improve and get optimized codes for better results in shorter complexities and shorter amounts of time. Claude 3 is highly capable of doing that.
3) Debugging Code
We wanted to test Claude 3 Sonnet’s debugging capabilities. We gave it a messed up version of the n-queens problem in Python where the diagonal check functions were not valid, there were unnecessary print statements, and several other issues.
Claude identified all possible errors in the code, explaining how each error heavily impacted the code’s functionality, and most importantly it provided the debugged code snippets wherever necessary.
We ran both the error version and the debugged version to test it for ourselves. Claude 3 indeed did a wonderful job in fixing the issue.
Claude 3 can also be used for debugging. Gave it a messed up N-Queens code and asked it to debug it. Great results.#Claude3 #DSA #debugging pic.twitter.com/BEnrn6GqxN
— Xenesis26 (@xenesis26) April 1, 2024
This is a wonderful blessing for the Software Developer community as Claude 3 is now capable of fixing code errors, which often takes up a lot of time for Software Developers to fix and analyze, making it heavily cumbersome for them.
4) Deploying A Website
Can web developers make anything out of Claude 3? We put this to the test as well. We asked Claude 3 Sonnet to write code to deploy a website with a user login interface using simple HTML, CSS, and Javascript. We also asked it to employ a bit of bootstrap design.
To our surprise, Claude did an amazing task in providing all three HTML, CSS, and JS codes separately. It also referenced the Bootstrap link in the HTML file properly so that the website could have a proper base design.
It even explained all three file codes in detail and also added how to run the codes to deploy the website successfully.
We ran the codes in Visual Studio Code and deployed the website. Claude did an excellent job in encapsulating the necessities of the website.
Just tried to run a simple HTML, CSS, and JS code with Bootstrap template, for a front-end user login interface website. The codes were generated by Claude 3's Sonnet. This is simple yet amazing#Claude3 #webdevelopment pic.twitter.com/bh8CBvq7WC
— Xenesis26 (@xenesis26) April 1, 2024
Although the website seems quite simple, it is still quite impressive for a Chatbot to deploy a basic website instantly with ease. This can be highly useful for Web Developers who can use Claude 3 as a reference to deploy websites and save time in doing so.
5) Documentation Skills
How good are Claude 3’s documentation skills? To put this to the test we gave Claude 3 a vast document on a Real Estate Price Prediction project report.
We asked Claude to analyze the document in detail and also provide ways how to deploy the project model. This is the exact prompt that we gave: “Analyze my research paper and explain the project in detail. Also, provide me with a model deployment for my project.”
Claude 3 analyzed the document line by line and it provided us with a summary of the document which included the objectives, methodology, and various training aspects included in the project document. It also did well in providing the project deployment measures similarly as they were stated in the document we provided.
Lastly, we also asked Claude to provide us with any existing similar project links to our project.
Claude did a handy in fetching multiple Real Estate Price Prediction project links. The links were distributed across multiple research papers, GitHub repositories, blog posts, Kaggle notebooks, and articles related to the document’s project topic.
Claude 3’s documentation skills can highly come in handy for the software developer community. Analyzing large documents and having the relevant facts and figures extracted from them is something that is in high demand in today’s world. Claude can highly benefit developers by taking the workload off such hectic documentation tasks so that more attention can be given to technical ones.
6) Creating Flowcharts
Claude 3 can also be used to create flowcharts across any relevant topic. We asked Claude 3 Sonnet to create a flowchart for supervised and non-supervised machine learning models.
Claude 3 responded extremely well in providing us with a detailed flowchart of both the models’ workflow and operating process. It also explained the flowchart step by step and elaborated on how the model operates.
Since the flow charts generated by Claude 3 are in the form of a mermaid code, here’s what you can do:
- Copy the mermaid code flow chart generated by Claude 3.
- Go to this website (Mermaid Live Editor), remove the code on the left side to paste yours
- Now your code has been turned into a complete flowchart!
Creating flowcharts is a very important process in automating workflows and having an overview of the entire process, but sometimes it becomes hectic and complex to design accurate flowcharts that capture every workflow step by step in the correct hierarchy. Claude 3 does well in designing such flowcharts, easing the task at hand for the software developer community.
7) Training Machine Learning Models
Claude 3’s Sonnet model can also be used to train machine learning models on any relevant machine learning algorithm.
We took a few lines of code from a Keras Image Classification Machine Learning Model that had been trained and tested on Random Forest Classifiers, Naïve Bayes, and Support Vector Machines. We asked Claude to train the model on the CNN algorithm.
Claude 3 did well in first analyzing that the code didn’t include any lines related to CNN. It continued to provide us with detailed information as to how we can train a Keras Image Classification Model on CNN using Deep Learning Libraries.
Then it continued to provide us with a new code in which the model has been trained on the CNN algorithm.
Claude explains the code again, even going into details about the model’s architecture.
Training machine learning models is a crucial task in today’s rapidly evolving AI world and it is quite an advancement from tools like Claude 3 to simplify the machine learning models’ training task.
This can be highly beneficial not only to the software developer community but also to highly passionate AI enthusiasts who are looking to design and employ new algorithms to fit into real-time models every day.
Conclusion
Software development and generative AI can help level up both! Tools like Claude 3 have immense potential to transform the full scale of software development upside down. Here is a complete guide on Claude 3 prompts to check as well!