Debunking Devin: "First AI Software Engineer" Upwork lie exposed!

Carl, a software professional with 35 years of experience, critically examines the claims surrounding Devin, an AI touted as the 'first AI software engineer.' He disputes the hype and the specific claim that Devin made money by taking on tasks from Upwork, calling it a lie as the video does not show this. Carl emphasizes the importance of truthfulness in AI capabilities, noting that false claims can mislead non-technical people and lead to problems such as increased bugs on the internet. He also discusses the actual job Devin was meant to do, which involved working with a repository on AWS, and points out that the AI failed to provide what was asked by the customer. Carl demonstrates that the task could be accomplished by running just two commands after setting up the environment, contrary to the complex process Devin allegedly used. He concludes by urging skepticism towards internet claims, especially those related to AI, and calls for responsible communication about AI's capabilities.

Takeaways

• 🚫 **Misrepresentation**: The claim that Devin, an AI, made money by taking on tasks from Upwork is false as the video does not show this happening.
• 📢 **Hype Critique**: Carl, with 35 years of experience, criticizes the hype around AI, emphasizing the importance of truthful representation.
• 🤖 **AI Capabilities**: While acknowledging AI's potential, Carl argues against exaggerating its current capabilities, which can mislead non-technical people.
• 💻 **Technical Damage**: False claims about AI's capabilities can cause harm by leading to over-reliance on AI-generated code, increasing bugs and security issues.
• 🛠️ **Software Engineering Role**: AIs are not yet capable of performing key aspects of software engineering, such as customer communication and requirement clarification.
• 🔍 **Verification Call**: Carl calls for skepticism and verification of claims made on the internet, especially those related to AI.
• 📝 **Documentation Importance**: Proper documentation and detailed instructions are crucial for cloud-based tasks, which Devin failed to provide.
• 🛑 **Error Identification**: Devin allegedly fixed errors in code it generated rather than addressing issues in the customer's repository.
• 🕒 **Time Efficiency**: Carl points out that Devin's process was inefficient, taking much longer than necessary to complete the task.
• 📈 **AI Development**: Despite its shortcomings, Devin's ability to perform certain tasks is seen as a sign of progress in AI, although it's not yet ready for practical application.
• 🗣️ **Communication Essential**: The video emphasizes that human communication and understanding remain irreplaceable in software development.

Q & A

What is the main claim that Carl is debunking in the video?

Carl is debunking the claim that Devin, an AI, is the 'first AI software engineer' and that it can make money by taking on messy Upwork tasks, which he states is a lie.

Why does Carl believe the hype around AI is problematic?

Carl believes the hype around AI is problematic because it misleads non-technical people to overestimate AI's capabilities, leading to less skepticism and potential issues like increased bugs and security vulnerabilities on the internet.

What does Carl think about generative AI tools?

Carl thinks generative AI tools are cool and he uses them regularly, such as GitHub Copilot, ChatGPT, and Stable Diffusion. However, he is against lying about what these tools can do.

What was the actual task Devin was supposed to perform on Upwork?

The actual task was to provide detailed instructions on how to make inferences with a model in a repository on an EC2 instance in AWS.

What does Carl criticize about the way Devin handled the Upwork task?

Carl criticizes that Devin did not provide the detailed instructions that were asked for by the customer. Instead, Devin generated its own code with errors and then debugged those errors, which was not the task.

How long did it take Carl to replicate what Devin did?

It took Carl 36 minutes and 55 seconds to replicate what Devin did.

What was the actual error in the repository that Devin was supposed to fix?

The actual error was in a file called dataset.py, where the module 'torch' had no attribute called '_six'. This error was not identified or fixed by Devin.

What does Carl suggest is the most important part of a software developer's job that AIs are not capable of?

Carl suggests that the most important part of a software developer's job that AIs are not capable of is communication with the customer, boss, and stakeholders to understand what needs to be done.

Why does Carl believe companies should not be allowed to lie about their AI products?

Carl believes that companies should not be allowed to lie about their AI products because it does a disservice to everyone by creating unrealistic expectations and causing damage to the software ecosystem.

What does Carl recommend for people who are using the internet and come across information about AI?

Carl recommends that people should be skeptical of everything they see on the internet or news, especially anything related to AI, and to not blindly trust headlines without doing their own research.

What is Carl's stance on the use of AI in the software industry?

Carl is not anti-AI and acknowledges that AI can do impressive things. However, he emphasizes the importance of truthfulness and transparency about AI's capabilities and limitations.

Outlines

00:00

😀 Introduction and Critique of AI Hype

Carl introduces himself humorously and clarifies that the video will be divided into three parts. He expresses his skepticism about the claim that Devin is the world's 'first AI software engineer' and criticizes the hype surrounding AI. Carl, a software professional for 35 years, is against the exaggeration of AI capabilities and the potential harm caused by such misinformation. He emphasizes the importance of truthfulness in AI representation and the negative impact of false claims on the public's perception of AI's capabilities.

05:01

🔍 Analyzing Devin's Task and the Actual Instructions

Carl discusses the specific task that Devin, an AI, was purportedly given on Upwork. He points out that the task was not randomly selected but was cherry-picked, which may imply that Devin's performance was not as versatile as claimed. The customer's actual request is detailed, emphasizing the need for detailed instructions on using a model in an EC2 instance on AWS. Carl argues that the report generated by Devin at the end of the video did not address the customer's actual needs and criticizes the lack of clarity and communication in the process.

10:03

🛠️ Devin's Approach and the Issues It Created

Carl examines Devin's actions, highlighting that it did not follow the customer's instructions accurately. Instead of providing detailed instructions, Devin generated code with errors and then attempted to fix them, which was not part of the customer's request. Carl also notes that the errors Devin encountered were not from the original repository but from files it created, which could mislead viewers into thinking Devin was fixing actual repository issues. He emphasizes the deceptive nature of such a portrayal and the importance of transparency in AI operations.

15:04

🤖 The Misunderstandings About Devin's Capabilities

Carl clarifies that Devin did not fix existing code from the internet or the customer's request but rather generated and then corrected its own code. He points out that the README file from the repository already contained a script that did what Devin was shown doing in the video. Carl also notes that Devin's methods were outdated and inefficient, and that there was an actual error in the repo that Devin overlooked. He details his own process of replicating Devin's work more efficiently and criticizes the narrative that Devin is capable of replacing human software engineers.

Keywords

💡AI Software Engineer

An 'AI Software Engineer' refers to a professional who applies artificial intelligence (AI) to the development and maintenance of software. In the context of the video, the term is used to describe Devin, which is claimed to be the world's 'first AI software engineer.' The video, however, challenges this claim, arguing that the hype around AI capabilities is misleading and that the actual work done by Devin does not live up to the title.

💡Upwork

Upwork is an online platform where businesses and individuals can find independent professionals for various jobs and tasks. In the video, it is mentioned that Devin was said to be capable of 'making money taking on messy Upwork tasks,' a claim the video aims to debunk, stating that the actual performance of Devin does not substantiate this ability.

💡Hype

The term 'hype' refers to the aggressive promotion or publicity of a product or event, often with exaggerated claims. In the video, the speaker is critical of the hype surrounding AI, particularly in the context of Devin's capabilities, arguing that such exaggeration can lead to unrealistic expectations and potential harm to the industry.

💡Generative AI

Generative AI refers to a class of AI algorithms that can create new content, such as text, images, or code. The video discusses generative AI in the context of Devin's capabilities, noting that while the speaker finds generative AI cool and uses it regularly, they take issue with the misrepresentation of its capabilities.

💡Technical Skepticism

Technical skepticism is a critical approach to evaluating the capabilities and outputs of technology, particularly AI. The video encourages viewers, especially those with a technical background, to maintain a level of skepticism towards claims made about AI to avoid falling for exaggerated or false statements.

💡Bug

In the context of software and technology, a 'bug' is an error, flaw, failure, or fault in a program or system that causes it to produce an incorrect or unexpected result. The video discusses the potential for increased bugs on the internet due to the trust in AI-generated code, which may not be thoroughly vetted or free of errors.

💡Code Quality

Code quality refers to the level of excellence of source code in terms of its structure, readability, efficiency, and maintainability. The video criticizes the code quality produced by Devin, suggesting that it is not up to the standards expected from a professional software engineer.

💡Software Development Lifecycle

The software development lifecycle (SDLC) is a process that describes the stages involved in the development of a software product. The video touches on the SDLC in the context of Devin's task, highlighting the importance of communication with customers and stakeholders, which is a part of the SDLC that AI struggles with.

💡Instance Size

In cloud computing, 'instance size' refers to the resources allocated to a virtual machine, such as CPU, memory, and storage. The video discusses the need to determine the appropriate instance size for a job on AWS, which is a critical decision in cloud-based software deployment.

💡Debugging

Debugging is the process of identifying and removing errors from a computer program. The video shows Devin engaging in debugging activities, but it questions the effectiveness and accuracy of these actions, as they involve fixing errors that Devin itself generated.

💡Requirements.txt

A 'requirements.txt' file is a common way to list the dependencies of a Python project. The video discusses how Devin had to update the 'requirements.txt' file to make the code compatible with current library versions, which is a necessary step in software maintenance.

Highlights

The video is a critique of claims made about an AI named Devin, which was introduced as the 'first AI software engineer'.

Carl, the presenter, has 35 years of experience as a software professional and is critical of the hype around AI without proper understanding.

The video aims to debunk the claim that Devin can make money by taking on tasks from Upwork, which Carl states is false.

Carl emphasizes the negative impact of exaggerating AI capabilities, as it can mislead non-technical people about the current state of AI.

The video outlines the actual job Devin was supposed to do, which involved working with a repository on AWS EC2, and how it was misrepresented.

Carl explains the importance of communication in software engineering, an aspect he believes AIs are currently incapable of handling well.

The presenter discusses the improper bidding process on Upwork and how it can lead to misunderstandings and misrepresentations of work.

Carl demonstrates that Devin did not follow the customer's instructions and instead generated its own code with errors.

The video shows that Devin's report did not contain what the customer requested, indicating a failure to meet the job requirements.

Carl points out that Devin was given a cherry-picked task that was not representative of the wide range of jobs on Upwork.

The presenter reproduces Devin's work and finds that the process was more complicated and time-consuming than necessary.

Carl identifies specific technical errors and nonsensical commands generated by Devin that a human developer would not typically make.

The video highlights that Devin did not fix an actual error in the repository but instead generated new errors to fix.

Carl contrasts Devin's approach with a simpler, more direct method that he used to achieve the same end result in less time.

The presenter criticizes the narrative that Devin is taking jobs from human workers, stating that the AI's performance was overhyped.

Carl calls for honesty and transparency from companies developing AI products and urges the media to verify claims before reporting.

The video concludes with a plea for internet users to be skeptical of claims made online, especially those related to AI.