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| 🔗 Stories, Tutorials & Articles |
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| The Software Factory: Why Your Team Will Never Work the Same Again |
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The current models and tooling are enough to build software factories. In a software factory, developers stop writing code by hand, and AI coding agents implement features and fix bugs while developers design and improve the factory. Tools like Claude Code and Gas Town enable this shift towards a more efficient and streamlined production workflow.
System shift: Today, implementations are pivoting to agent-driven factories. Teams are shrinking. Investment is narrowing to skills, architecture, and CI backpressure. |
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| 5 Suggestions to Upgrade your OpenTofu/Terraform & AWS Development Experience |
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| The article covers tools and scripts to reclaim focus and improve workflow for OpenTofu, Terraform, and AWS CLI users. Suggestions include tools for easily swapping between versions, summarizing plans, linting code, switching AWS profiles, and customizing prompts. Bonus recommendation includes Task for automating bulk operations across multiple projects. |
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| Software engineer interviews for the age of AI |
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| AI is becoming more prevalent in coding interviews, sparking interest from experienced candidates tired of traditional methods. Hiring great engineers is crucial for maintaining reliable services, especially in the era of AI-generated code. System design interviews help identify candidates with hands-on experience and the ability to navigate unknown codebases. |
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| How I Use LLMs for Security Work |
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| The writer shared their experience of using LLM tools like Claude, Cursor, and ChatGPT in security and engineering work. They emphasized the importance of specific and role-stacking prompts when using these tools, and highlighted the need to provide context and constraints for more accurate responses. Additionally, they discussed techniques for optimizing the use of LLMs in security work, and encouraged sharing effective prompting patterns within the community. |
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| Why system architects now default to Arm in AI data centers |
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| AI is reshaping infrastructure needs, exposing the limits of legacy architectures. As AI workloads demand more efficient platforms, design is shifting towards purpose-built rack-level systems. Arm-based architectures are being chosen to address constraints shaping modern AI platforms, with a focus on system-level harmony and CPU performance. |
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