Haskell's lazy evaluation means the order of operations is not guaranteed, making side effects like `print` statements unpredictable. This forced the language to be pure by default. Conversely, OCaml's strict, predictable evaluation order made it easy to incorporate I/O and side effects, allowing it to be impure by default.

The dream of hardware optimized for functional programming (e.g., dataflow or SK combinator machines) proved to be a mistake. These machines were essentially hardware-based interpreters. The better approach is to build a sophisticated compiler that translates functional code into efficient instructions for general-purpose CPUs.

OCaml's success lies in its dual nature. It offers the elegance of a fine functional language while also providing the imperative power and predictable execution cost model of a systems language. This rare combination is highly valuable for applications like high-frequency trading and network programming.

Manual memory management can be slower than garbage collection. Programmers, unsure of data ownership in languages like C++, often defensively copy data. This leads to performance degradation and memory bloat, whereas a garbage collector handles data sharing safely and more efficiently.

While Moore's Law continued adding transistors, the failure of Dennard scaling around 2005 meant they no longer became more power-efficient. This created a "power wall," making single cores too hot and forcing the industry to use multiple, simpler cores to continue performance gains.

The creation of the Rust programming language was a direct response to fundamental weaknesses in C++. Mozilla needed a way to eliminate entire classes of security vulnerabilities (memory safety) and safely leverage multi-core processors (concurrency), which were intractable problems in its massive C++ codebase.

Bjarne Stroustrup advises against being "too clever." Manual optimizations from the 1990s are often "pessimizations" today because they constrain modern compilers, preventing them from applying more sophisticated optimizations tailored to new CPU architectures, caches, and memory access patterns.

Unlike languages like C which started as useful but unsafe, Haskell began with extreme safety and theoretical purity, even lacking I/O initially. This forced its designers to invent new, principled ways to handle side effects (like monads), ensuring the language evolved towards usefulness without sacrificing its core value of safety.

Go's garbage collector led to unpredictable memory usage. In Dropbox's storage system, a node OOMing would trigger a massive re-replication workload, which could cause other nodes to OOM, leading to a system-wide "congestion collapse". Rust's memory management provided the predictability needed to prevent these catastrophic failures.