Core Insights - The article discusses the transformative impact of large language models (LLMs) on software development processes, emphasizing the shift from AI as an auxiliary tool to a core productivity driver [2][3] - It highlights the current state of AI in development as being at a "halfway point," indicating that while significant advancements have been made, a true paradigm shift has not yet occurred [5][9] Group 1: AI's Role in Development - AI is primarily seen as a tool for efficiency in testing rather than a replacement for human roles, with the industry still far from a "native development era" [9][10] - The emergence of various AI programming products indicates a growing integration of AI in code production, with some teams reporting over 50% of their code being AI-generated [6][10] - The effectiveness of AI varies significantly among users, with some leveraging it for simple tasks while others utilize it for more complex processes [6][7] Group 2: Challenges and Limitations - AI's current capabilities are limited in handling complex tasks, particularly in existing codebases, where it often struggles with intricate logic and dependencies [5][10] - The stability and reliability of AI outputs remain significant concerns, impacting its adoption in real-world applications [20][21] - AI's role in testing is still largely supportive, with challenges in fully automating complex testing scenarios due to the need for human judgment [9][10] Group 3: Future Directions - The evolution from AI assistants to intelligent agents capable of executing complete development cycles is seen as a key future trend [28][31] - The integration of AI into existing workflows is expected to be gradual, with a focus on plugin-based ecosystems rather than monolithic platforms [32][33] - The article suggests that the future of software development will require professionals to adapt by enhancing their skills in prompt engineering and knowledge management to effectively collaborate with AI [23][24][39]

大模型正在深刻改变研发流程的各个环节，推动自动化与智能化。辅助编程、Coding Agent……AI 是如何从"辅助工具"变成核心生产力的？大模型原生开发时代到来了吗？ 近日 InfoQ《极客有约》X AICon 直播栏目特别邀请了平安科技高级产品经理吴朝雄、百度 资深架构师颜志杰和汽车之家客户端架构师杜沛，在 AICon 全球人工智能开发与应用大会 2025 北京站（12 月）即将召开之际，共同探讨 LLM 时代的软件研发新范式。 部分精彩观点如下： 以下内容基于直播速记整理，经 InfoQ 删减。 1 LLM 原生开发时代 吴朝雄：很多观点还是认为"AI 写代码"只是更高级的自动补全、不算范式变革。你们怎么看？ 颜志杰："一半是火焰，一半是海水"。我们看到各种新闻时，会惊叹于 AI 的不断进化，它能完成越来 越多任务、击败专业人士、甚至带来可观收益。然而，作为程序员，在实际开发中，尤其是在多年积累 的代码基础上进行开发时，常常会发现 AI 并没有想象中那么"神"，有时甚至显得笨拙。所谓"火焰"的 部分，是指 AI 在一些相对独立、结构清晰的小任务或 0 到 1 的创新场景中表现突出；而"海水"的部 分，则 ...