How do generics in Go 1.18+ enable better system design and what are the trade-offs?

Go generics allow writing type-safe, reusable data structures and algorithms without code duplication or losing type information through interfaces. The key use cases: generic data structures, result/option types, and typed collections.

// Generic Result type — eliminates panic-or-nil patterns
type Result[T any] struct {
    value T
    err   error
}

func Ok[T any](v T) Result[T]    { return Result[T]{value: v} }
func Err[T any](e error) Result[T] { return Result[T]{err: e} }

func (r Result[T]) Unwrap() (T, error) { return r.value, r.err }
func (r Result[T]) IsOk() bool         { return r.err == nil }

// Generic ordered set
type Set[T comparable] struct {
    items map[T]struct{}
}

func NewSet[T comparable]() *Set[T] {
    return &Set[T]{items: make(map[T]struct{})}
}
func (s *Set[T]) Add(v T) { s.items[v] = struct{}{} }
func (s *Set[T]) Has(v T) bool { _, ok := s.items[v]; return ok }
func (s *Set[T]) Len() int { return len(s.items) }

// Generic Map/Filter/Reduce — functional pipeline without reflect
func Map[T, U any](slice []T, fn func(T) U) []U {
    result := make([]U, len(slice))
    for i, v := range slice { result[i] = fn(v) }
    return result
}

func Filter[T any](slice []T, pred func(T) bool) []T {
    var result []T
    for _, v := range slice {
        if pred(v) { result = append(result, v) }
    }
    return result
}

// Usage
users := []User{{ID: 1, Active: true}, {ID: 2, Active: false}}
activeIDs := Map(
    Filter(users, func(u User) bool { return u.Active }),
    func(u User) int { return u.ID },
)
// [1]  — type-safe, zero reflect, zero allocation overhead

Trade-offs: generics increase code readability but slightly increase compile time. The Go implementation uses GCShape monomorphisation — types with the same memory layout share one instantiation, reducing binary size compared to full C++ monomorphisation. Avoid generics for simple cases — if a plain interface satisfies the requirement, prefer it.

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