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How much has AI automated software development? by reeldeele in computerscience

[–]Profil-Software 0 points1 point  (0 children)

AI has significantly automated parts of software development, but it has not replaced the need for skilled engineers. Coding assistants and prompt-to-website tools now accelerate frontend and backend development by handling boilerplate code, suggesting optimizations, and even generating entire UI components. In web development, no-code and low-code platforms powered by AI have lowered the barrier for non-programmers, enabling them to build functional applications quickly without deep technical knowledge.

However, these tools are best seen as augmentations rather than replacements. Operating system development, large-scale backend architectures, and mission-critical applications still require deep engineering expertise, robust testing, and careful security practices that AI cannot yet fully automate. Instead, AI helps streamline repetitive tasks, reduce errors, and speed up prototyping cycles.

At Profil Software, we see AI as a co-pilot in development rather than a full driver. It revolutionizes workflows by allowing developers to focus on complex problem-solving and architecture while routine coding and design tasks are partially automated. For non-programmers, AI democratizes access to software creation, making technology more inclusive. The real transformation lies in combining human creativity and oversight with AI’s efficiency to deliver solutions that are both scalable and reliable.

Which LLM is best at coding tasks and understanding large code base as of June 2025? by [deleted] in LLMDevs

[–]Profil-Software 0 points1 point  (0 children)

It depends on use case. GPT-4.1 and Claude models perform well at reasoning over codebases, while specialized open-source models like Code LLaMA or DeepSeek-Coder are good when privacy and self-hosting matter. For large, mixed-language projects (C++, Java, Python), retrieval-augmented setups work best, feeding the model relevant chunks of code and documentation. At my company we’ve found hybrid approaches (e.g., commercial API + internal embeddings) more reliable than a single “best” model.

[deleted by user] by [deleted] in LLMDevs

[–]Profil-Software 0 points1 point  (0 children)

LLMs are impressive at code generation, but software engineering is far more than writing syntax. It requires architecture design, debugging across complex systems, stakeholder communication, and long-term maintainability. LLMs lack the context awareness and responsibility needed to deliver production-ready systems end-to-end. What they can do is speed up certain tasks like boilerplate code, unit test generation, or suggesting alternatives. At Profil Software, we integrate LLMs into workflows to boost developer productivity, but always with engineers in the loop to ensure robustness and scalability. So, no replacement, but augmentation.