And how do you measure the outcomes that you want to drive with this agentic AI and software engineering. The northstar here is like how much faster can you actually ship to broad right so like what I've seen both from my past experience and also for from like you know companies that we work with it's it's pretty easy to spin up like a prototype and a v1 and then it just takes so long to actually deploy that to production right and then when you do like your planning cycles and your retrospectives you're li ...

Anthropic's Claude Sonnet 4.5 now scores 77% on a key software engineering benchmark and can work autonomously for over 30 hours on complex tasks. We put it to a first test. https://t.co/ElsHIqH2FL ...

RT Tetsuo (@tetsuoai)Grok 4 prompt for optimizing your Python code.(NOTE: after phase 1, the Model will pause to ask you if any changes need to be made before it continues)>>> promptYou are a collaborative AI panel of four senior software engineers speaking with one voice. Your mission: analyze, refactor, and harden code to production standards across security, performance, maintainability, and quality, keeping outputs concise and decision-oriented.Personas (combine insights into one answer)1. Senior Archit ...

In 5 years time will you have more or less engineers. I think more and the reason is that engineering is such an elastic role. Say we make engineers 10 times more efficient we would probably build 100 times more software right in so far as maybe not unique platforms but the amount of features those people would ship and the iterations on every ranking algorithm etc. And so I'm a huge believer in the fact that AI, especially in domains like software engineering, will be an amplifier in making people more pro ...

之前刷到：《 趣图："软件工程，毁了我的儿子" 》 今天刷到下面这版： 趣图: 后端开发 vs 前端开发 往期趣图 （点击下方图片可跳转阅读） 趣图: 敢动遗留代码的实习生 趣图: 程序员修 Bug 的六种方式 ...

Core Insights - Cognition is reshaping the software engineering landscape with a rigorous hiring process that includes an 8-hour task to build a product similar to their AI tool Devin, reflecting a high-intensity work culture [2][3] - The company emphasizes the importance of high-level decision-making, deep technical understanding, and strong self-motivation in its hiring criteria, favoring candidates with entrepreneurial backgrounds [3][60] - Cognition's AI tool Devin is designed to function as an asynchronous software engineer, capable of handling repetitive tasks and improving efficiency in software development [23][28][30] Group 1 - Cognition's CEO Scott Wu describes the company's culture as one that does not prioritize work-life balance, with expectations of over 80 hours of work per week [2][3] - The initial team of 35 members included 21 former founders, indicating a strong entrepreneurial spirit within the company [3][60] - The hiring process involves candidates creating their own version of Devin, showcasing their ability to build and innovate under pressure [57][60] Group 2 - Devin is positioned as a "junior engineer," excelling in tasks like fact-checking and handling mundane tasks, which allows human engineers to focus on more complex decision-making [28][30] - The tool has been deployed in thousands of companies, including major banks like Goldman Sachs and Citigroup, demonstrating its broad applicability [30] - Cognition measures Devin's success by the percentage of pull requests it completes, with successful teams seeing Devin handle 30% to 40% of these requests [31] Group 3 - The company recently acquired Windsurf, completing the deal in just three days to ensure continuity for clients and employees [71][72] - This acquisition is expected to enhance Cognition's product offerings and market reach, as Windsurf's capabilities complement those of Devin [80] - The integration of Windsurf's team is seen as a strategic move to bolster Cognition's operational functions, which had previously lagged [78][80] Group 4 - The future of software engineering is anticipated to shift away from traditional coding towards guiding AI in decision-making processes, increasing the demand for engineers who can make high-level architectural decisions [62][66] - The company believes that despite the rise of AI tools, the need for skilled software engineers will persist, as understanding computer models and decision-making will remain crucial [62][66] - Cognition's approach reflects a broader trend in the industry where AI tools are expected to handle more routine tasks, allowing human engineers to focus on strategic aspects of software development [66][70]

AI Coding Impact on Software Engineering - The speaker believes predictions of massive software engineer job losses due to AI coding are likely wrong, not because AI coding isn't important, but because those making predictions haven't worked on production systems recently [2] - AI code generation at 30% in very large codebases may not be as impactful as perceived due to existing architectural constraints [3] - The industry believes software engineers will still be needed to fix, examine, and understand the nuances of code in complex systems, even with AI assistance [6] - The speaker draws a parallel to the DevOps transformation, suggesting AI will abstract work, not eliminate jobs, similar to how tractors changed farming [7] Production Software Considerations - Production code requires "four nines" availability, handling thousands of users and gigabytes of data, which "vibe coding" (AI-generated code without examination) cannot achieve [10] - The speaker emphasizes that code is an artifact of software development, not the job itself, which involves making decisions about software architecture and dependencies [11] - The best code is no code, as every line of code introduces maintenance and debugging burdens [12] - AI's text generation capabilities do not equate to decision-making required for complex software architectures like monoliths vs microservices [15] - Changing software safely is the core job of a software engineer, ensuring functionality, security, and data integrity [18] AI Adoption and Best Practices - Professional software engineers are observed to be slower in adopting AI compared to previous technological shifts [20] - The speaker suggests documenting standards, practices, and reproducible environments to facilitate AI code generation [22][23] - Code review is highlighted as a critical skill, especially with AI-generated code, but current code review tools are inadequate [27][28] - The speaker advises distrusting AI's human-like communication, as it may generate text that doesn't accurately reflect its actions [32] - The speaker recommends a "create, refine" loop for AI-assisted coding: create a plan, have AI generate code, then refine it [35][36][37]

AI Agent Development & Management - AI agents require mentorship similar to interns to ensure effective deployment [1] - Treating AI agents as a tech lead would, rather than just a user, maximizes their leverage [1] - Effective use of AI agents impacts software engineering at both micro and macro levels [1] Software Development Lifecycle (SDLC) - The report previews how AI agents can change the calculus of software engineering [1] - Practical advice for working with AI agents in the SDLC will be provided [1]

AI in Software Engineering - AI excels at generating code, translating languages, creating UIs, fixing bugs, and repetitive tasks [4][5] - AI has limitations, lacking understanding of context, long-term goals, and reliability, sometimes providing incorrect answers [6][7] - 55% of developers are using AI co-pilots, but only 30% accept the output without changes [7] The Evolving Role of Software Engineers - Software engineering involves understanding user needs, collaboration, and making empathetic decisions, not just coding [11] - The best engineers think deeply and guide machines towards structured outcomes [12] - Software engineers are essential because they understand AI, use it to build production-ready software, and improve AI itself [14][15][16] - Software engineers are building the future of intelligence by training and directing AI [17] Software Engineering Education for the AI Era - Software engineering education should focus on mastering foundations, system architecture, full-stack development, communication, and AI tools [19][20][21][22] - Future software engineers should be visionaries, bridge builders, and leaders who can lead both humans and AI [24]

Industry Development & Investment - A $1.3 million endowment fund is being launched to support aspiring software engineers in Nigeria [1] - The fund aims to provide training access for Nigerian software engineers [1] - SuiHub Lagos is established as a resource for builders in Nigeria [1]