This article explores how advancements in software design, particularly through LLMs, shift the focus from using standard libraries to generating custom code. It highlights the implications for dependency management and emphasizes the need to understand the problem being solved rather than just the mechanics of coding. The author compares this shift to the evolution of 3D printing in manufacturing.

• LLMs flip the standard-library calculus: the default question becomes "is this worth a dependency?" instead of "is there a library for this?", since custom code is now cheap to generate.
• Unlike 3D printing, LLM-generated code has no inherent quality penalty versus hand-written code—if it's correct, it performs identically, unlike physical printed parts that sacrifice strength/precision.
• Design cost (understanding the actual problem/business logic) doesn't disappear even as coding cost collapses—LLMs don't grasp constraints on their own, so that burden stays on developers.
• The tradeoff shifts from dependency/version management to maintenance and vulnerability-tracking responsibility for more bespoke, less shared code.

In a podcast discussion, predictions for the tech industry in 2026 are shared, highlighting the undeniable improvement of LLMs in writing code, advancements in coding agent security, and the potential obsolescence of manual coding. Other predictions include a successful breeding season for Kākāpō parrots and the implications of AI-assisted programming on software engineering careers.

• LLMs will keep getting undeniably better at writing code through 2026, shifting more programming work to coding agents
• Security around coding agents will become a major focus as they gain more autonomy and access to systems
• Manual hand-coding may start becoming obsolete for significant portions of software engineering work, reshaping the profession
• Kākāpō parrots are predicted to have a successful breeding season in 2026

Claude Opus 4.5 is launched as a cutting-edge AI model designed for coding, research, and office tasks. It boasts significant improvements in efficiency, reasoning, and task management, making it accessible for developers and enterprises at a competitive price. The model excels at complex workflows, demonstrating advancements in self-improving abilities and safety measures.

• Claude Opus 4.5 is priced more competitively than previous Opus models, lowering the barrier for developers and enterprises to adopt it
• The model shows notable gains in coding, research, and office/agentic task performance compared to earlier Claude versions
• It demonstrates improved efficiency and reasoning on complex, multi-step workflows
• Anthropic highlights advances in self-improving capabilities alongside continued safety measures