Open-source software (OSS) projects rely on effec- tive newcomer onboarding to sustain their communities. Many projects use “good first issue” (GFI) labels to highlight beginner- friendly tasks. The widespread adoption of AI-assisted devel- opment tools shows a significant change within this ecosystem, potentially altering how newcomers contribute and how projects manage simple tasks. This shift necessitates a timely investigation into recent trends in GFI label usage, newcomer engagement, and the success of GFI contributions. This study analyzes 43,906 newcomer pull requests and 1,117 PRs addressing GFIs across 37 popular GitHub repositories from July 2021 to June 2025, examining trends before and after November 2022 when ChatGPT was released. We find that the median proportion of issues with GFI labels declined from 0.90% to 0.74%, yet the proportion of GFIs addressed by newcomers increased from 27.5% to 32.2%. Furthermore, GFI usage varies substantially across projects: 51.7% showed declining trends, 24.1% remained stable, and 24.1% showed increasing trends. This heterogeneity was not explained by repository age or primary programming language. Additionally, merge rates for newcomer contributions to GFIs declined by 24%, while PR description length increased by 47% from 319 to 470 characters. An analysis of factors associated with merge success reveals that review count strongly correlates with merge success, while description length and code size metrics show no significant association. Our findings suggest that GFI trends are driven by project-specific strategic decisions, and successful GFI contributions depend more on maintainer engagement than initial PR characteristics. These results under- score the importance of human-centric onboarding strategies in increasingly AI-augmented OSS ecosystems, providing actionable insights for maintainers and newcomers.