The Overlooked Cost of AI Integration: Neglecting Core Features in Modern Applications

In recent years, the rapid proliferation of Artificial Intelligence (AI) has transformed the landscape of software development. Virtually every major application—ranging from developer tools to database systems—has announced or begun implementing AI-powered features. While this technological advancement holds significant promise, a concerning trend is emerging: the sidelining of fundamental core features of these applications in favor of AI integration.

The Surge of AI in Software Development

It’s impossible to ignore the pervasive push towards incorporating AI across software platforms. For instance, popular code editors like Visual Studio Code are now heavily focused on language model (LLM) integrations, with updates often centered around AI capabilities. Similarly, platforms such as Postman are investing heavily in their Multi-Chain Processing (MCP) features, aiming to streamline API workflows through AI-enhanced operations.

Database management systems like Neo4j are exploring solutions like GraphRAG to leverage AI for more intelligent data retrieval. Even frontend frameworks such as Angular are promoting AI-assisted development features, touted under initiatives like “Build with AI.” This widespread adoption underscores a significant shift in priorities—placing AI at the forefront of product evolution.

The Hidden Drawback: Neglect of Core Features

Despite the excitement surrounding AI, a less discussed but critical issue is the neglect of the applications’ foundational functionalities. Many of these platforms have extensive open issue lists, feature requests, and bug reports that remain unaddressed, as resources and development focus increasingly pivot toward AI-driven features. In some cases, the integration of AI offers minimal tangible benefit to the end-user, making the neglect of core features all the more perplexing.

This trade-off can lead to a degraded user experience, where essential functionalities become outdated, buggy, or under-supported. For developers and enterprises reliant on these tools, such neglect can translate into decreased productivity, increased frustration, and potential stability issues.

Striking a Balance

While embracing innovative AI features is undoubtedly valuable—especially when they solve genuine pain points—the core functionalities that underpin these applications must not be overlooked. Robustness, usability, and feature-completeness remain the bedrock of reliable software. Prioritizing AI integration at the expense of these essentials risks undermining the long-term value and trustworthiness of these tools.

Your Perspective

As technology enthusiasts, developers, or business stakeholders, it’s crucial to reflect on this balance. Are we genuinely benefiting from AI enhancements, or