While programmers in Silicon Valley are still struggling to solve LeetCode problems, three Chinese-American genius engineers have thrown out a game changer—Devin, the world's first AI software engineer capable of independently completing end-to-end programming. This thing can not only write code and fix bugs by itself but can also predict program vulnerabilities, taking over the work of 'ten-year veteran coders' completely. In just six months since its establishment, the parent company Cognition AI's valuation soared from $2 billion to $4 billion, with whispers of 'secretly using' it even within Google.
Devin's most ruthless move is to specifically target the most painful 'spaghetti code' of programmers. Those old systems with chaotic logic give human engineers headaches, but Devin can dissect them with surgical precision—automatically reconstructing code logic, optimizing performance bottlenecks, and even seamlessly migrating Java modules to Python.
Some users reported that a financial company used Devin to restructure its core system, completing a project that originally required 20 person-months in just 72 hours, with an error rate 23% lower than that of the human team. The secret lies in its simulation of a decade of experienced engineers' decision-making logic: for every line of code written, it backtracks through thousands of historical decision data, dynamically adjusting for the optimal solution.
Behind this operation are three Chinese-American geniuses who have won ten gold medals at the International Olympiad in Informatics (IOI). CEO Scott Wu developed the workplace social application Lunchclub in his early years, and after its acquisition, he led the original team into the AI field; CTO Steven Hao and CPO Walden Yan are known as 'geek madmen' in Silicon Valley, obsessed with using AI to solve engineering problems.
These people understand the pain points of programmers best: 'We created Devin not to replace humans, but to free engineers from repetitive tasks, allowing them to engage in more creative work.' But reality is harsh—one tester had Devin independently develop an e-commerce website, from writing the front end to deploying the server, completing the entire process in just 4 hours, while a human team would typically need 3 days.
Devin's business model is simple and straightforward: subscription-based + enterprise customization. The high initial price of $500 per month deterred many individual developers, but the launch of version 2.0 in April this year slashed the entry barrier to $20/month, and it supports 'parallel development'—allowing 10 Devin agents to work simultaneously, increasing efficiency by 83%.
This operation has directly ignited the market: the number of users has surged to hundreds of thousands in just six months, prompting even Amazon and Microsoft to scramble to enhance their AI coding tools, GitHub Copilot and CodeWhisperer. But Devin's trump card lies in its complete autonomy—other AI can only complete code, while it can independently handle the entire process from requirements analysis to testing and deployment.
The emergence of Devin has driven Silicon Valley into a frenzy, but it has also sparked controversy. Supporters argue that this is an 'industrial revolution in software development,' while opponents mock that it 'can't even write recursive functions properly.' In actual tests, Devin still 'crashes' when handling super complex tasks, such as applying Python's indentation logic to C language, generating a bunch of uncompileable code.
But capital has already voted with real money: top venture capital firms like 8VC and Founders Fund are betting heavily, and Cognition AI's valuation has doubled in six months, leaving competitors like Anysphere (valuation of $10 billion) and StackBlitz (valuation of $700 million) far behind. One investor stated directly: 'This is not a bubble, but the beginning of AI swallowing software development.'
The real threat of Devin lies in its breach of the 'AI replacing humans' narrative. When AI can independently complete 13.86% of programming tasks (while GPT-4 can only do 1.74%), the survival space for junior developers will inevitably be squeezed. However, senior engineers are becoming more sought after—they need to command the 'legions' of Devin to design more complex system architectures.
This transformation may resemble the time when steam engines replaced coachmen: it is not the jobs that are eliminated, but those who cannot use new tools. As one CTO who used Devin to complete an IPO project said: 'Previously, I spent 80% of my time writing code, now I spend 80% of my time teaching AI to write code—but the company's valuation has tripled, that’s the reality.'
