Insights to Inspire / AI
Did you know about Devin, the AI that can act as an autonomous AI software engineer?
Natalie Golffed
Cognition AI has recently introduced Devin, the world’s premier autonomous AI agent that can independently write entire software projects from scratch based on simple text prompts. Devin is an autonomous AI software engineer designed to collaborate seamlessly with human engineers. Its advanced long-term reasoning and planning capabilities allow engineering teams to tackle complex tasks autonomously, […]
Did you know about Devin, the AI that can act as an autonomous AI software engineer?
Cognition AI has recently introduced Devin, the world’s premier autonomous AI agent that can independently write entire software projects from scratch based on simple text prompts.
Devin is an autonomous AI software engineer designed to collaborate seamlessly with human engineers. Its advanced long-term reasoning and planning capabilities allow engineering teams to tackle complex tasks autonomously, by simply instructing the model to perform it.
The user interface is quite simple. A chat window in which the engineer talks with the model about what’s the plan, and where Devin replies by explaining its thoughts about it and what it believes it should be done. The model takes the engineer’s thoughts and instructions, and executes a series of development tasks to accomplish the underlying goal. To do so, Devin is equipped with developer tools such as a shell, code editor, and a browser, all within a sandboxed compute environment. Through this simple environment, Devin can actively collaborate with users, providing real-time progress updates and accepting feedback from them.
The capabilities of this tool are immense. It is able to learn unfamiliar technologies, build and deploy apps autonomously, train AI models by itself, and even find and fix bugs and feature requests in open-source repositories.
While other tools like Github Copilot and CodeGPT have already shown programming capabilities, Devin revealed more accuracy on standard coding benchmarks, solving 13.86% of real-world GitHub issues end-to-end, almost 10 times the performance of previous approaches. Furthermore, the collaboration environment defines a whole new experience compared to these other tools: it is not a VS Code plugin but a complete playground. We’re excited to see the actual adoption of this new experience in the upcoming months.
These models are emerging as a whole new way of doing software engineering. However, they still have limitations. 13% of accuracy, although impressive, is still far from optimal. Furthermore, using these tools through APIs offers no guarantees about the privacy of the code. Past incidents like the Samsung leak involving ChatGPT are a gentle reminder of what might happen when code or valuable data assets are filtered.
At Arionkoder, our engineers use a wide array of AI tools for our work, from product development to staff augmentation and internal projects, in order to increase accuracy and efficiency and generate more value for you. We’re addressing AI adoption challenges by deploying a coding assistant in our on-premise facilities, leveraging copilot capabilities to accelerate our engineering processes in every project with secure sandbox conditions.
We are committed to delivering innovative AI solutions that our clients can leverage everywhere, including the use of AI for standard software development. Contact us today at [email protected] to explore how our AI implementation services can transform your projects and learn more about our coding strategy!