Cognition is an applied AI lab that has created Devin, the first fully autonomous software engineer. Devin can handle complete engineering workflows, from bug fixing to submitting pull requests, and functions at the level of a junior software engineer. It integrates into tools like Slack, GitHub, and works in the local developer environment.
Devin is currently at the level of a junior engineer. Initially, it was like a high school CS student, then an intern, and now it's comparable to an entry-level junior engineer. However, it can't handle complex tasks like re-architecting an entire codebase.
Devin is priced at $500 a month for engineering teams. This is based on usage, with a unit called ACUs (agent compute units) that measure the decisions and work Devin does. The pricing reflects the value of Devin's capabilities, which can make tasks 10x cheaper to complete, compared to a more general $20 per month model for text-based tasks.
IDE assistants provide text completion and simple code suggestions, improving productivity by 10-20%. Devin, however, functions as a full co-worker, handling tasks asynchronously and end-to-end, from debugging to testing and submitting pull requests. This can save 90% of the time on routine tasks.
Scott describes programming's history as a growing abstraction layer that simplifies tasks and reduces the need for deep technical knowledge. From punch cards to assembly, BASIC, C, and modern languages like Python, each step has made programming more accessible, but the core remains about telling the computer what you want it to do.
A 10x engineer deeply understands abstractions and can effectively solve problems by thinking through customer needs and designing efficient solutions. While they only spend about 10% of their time on creative problem-solving, this quality distinguishes them from average engineers.
One of the most surprising use cases for Devin is its ability to handle large-scale migrations, modernizations, and version upgrades. These tasks are often tedious and time-consuming, but Devin can complete them much faster, saving engineers significant time and effort.
Scott believes AI will surpass the best competitive programmer, like Gennady Korotkevich from Belarus, within 1-2 years. Current AI models are already competitive with top human programmers and are rapidly improving. This milestone will be a significant moment, similar to AlphaGo, demonstrating the potential of AI in programming.
Scott predicts that in the future, AI will democratize software creation by allowing anyone to describe what they want to build in natural language. This will shift the focus from implementation to ideation, enabling rapid iteration and more personalized software solutions.
Agent-based systems like Devin are designed to make decisions and interact with the real world, unlike traditional AI tools that provide text completion or simple answers. Devin can test its own code, run commands, and navigate through a series of tasks, making it a powerful co-worker.
Cognition faces challenges in adapting model capabilities to real-world software engineering tasks, integrating with various developer tools, and maintaining machine state for efficient parallel work. The team focuses on solving these infrastructure and decision-making problems to enhance Devin's effectiveness.
The kindest thing Scott has experienced is the mentorship and guidance he received, especially from a mentor who pushed him to excel in competitive programming and math. This mentor invested significant time and effort, providing critical feedback and support that shaped Scott's career and success.
My guest today is Scott Wu). Scott is the co-founder and CEO of Cognition, which is an applied AI lab that has created the first AI software engineer, which they call Devin. In just a year since founding Cognition, Devin functions at the level of a junior software engineer, capable of handling complete engineering workflows from bug fixing to submitting pull requests. He is a former competitive programming champion and describes the field as simply “the art of telling the computer what you want it to do." Scott predicts AI will surpass the world's best competitive programmer within 1-2 years and sees this technology not as replacing programmers, but as democratizing software creation. We discuss the bottleneck in software development, the future of AI in various industries, and the challenges of leveling up Devin. Towards the end, you’ll also hear Scott do an insane card trick on me. You can find the video on our X and YouTube to grasp the madness fully. Please enjoy my conversation with Scott Wu.
For the full show notes, transcript, and links to mentioned content, check out the episode page here.)
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Show Notes:
(00:00:00) Welcome to Invest Like the Best
(00:07:00) Discussion of Devin's current capabilities as a junior engineer
(00:09:00) Early use cases and customer adoption
(00:11:00) Comparison between IDE assistants and Devin's autonomous approach
(00:14:00) History of computer programming and its evolution
(00:17:00) Scott's background in competitive programming
(00:20:00) Future predictions for AI in software engineering
(00:26:00) Explanation of AI agents and their significance
(00:29:00) Technical details of how Devin is built
(00:40:00) Impact on software engineering jobs and industry
(00:47:00) Discussion of business model and pricing
(00:52:00) Thoughts on AGI and its practical implications
(00:59:00) Commentary on the competitive landscape
(01:24:00) Future of AI adoption across industries
(01:25:00) Card trick demonstration
(01:29:00) The Kindest Thing Anyone Has Done For Scott