Why Software Continues to Be Slow Despite Modern Capabilities

The Economic Penalty of Speed

Modern hardware is faster than ever, yet everyday applications routinely crawl.

Despite having advanced profiling tools at their disposal, developers watch software remain sluggish because current incentive structures reward rapid feature delivery over millisecond-level speed improvements, according to Santiago Fuentes.

Market Pressures and the Cost of Lag

The persistent sluggishness of modern applications stems from a fundamental mismatch between technical possibility and market incentives. Tech optimists routinely argue that software has no excuse to run slowly given current compiler sophistication and hardware speeds.

Yet the reality on the ground looks entirely different. Software companies prioritizing user acquisition face zero market pressure to optimize performance until lag turns into a full retention crisis. By that point, complete rewrites often cost more than initial development.

Fuentes points out a stark economic calculation: slow software successfully generates revenue if it hits the market fast enough. Consequently, performance neglect operates as a rational response to venture capital metrics rather than a simple engineering failure.

The AI Factor in Compilation and Search

The debate over software speed evolved following recent commentary by Dan Luu regarding large language models. As outlined on bittide.aicompass.dev, Luu examined how AI lowers the cost of building specialized solutions like just-in-time compilers and custom search indexes.

While Luu argues that reduced expenses will lead developers to pursue property optimization more frequently, a counter-analysis points out that premises of economic rationality rarely hold up under real-world engineering constraints.

Accepting Unacceptable Latency

Theory and practice often diverge sharply on engineering teams. According to analysis cited on bittide.aicompass.dev, while highly experienced domain experts may ship more optimizations, everyday development often sees tolerance for latency increase rather than decrease.

Consider the daily friction of modern engineering environments. The latency introduced by agentic loop iterations and monorepo version control workflows forces developers to accept performance metrics that would have seemed unacceptable years prior.