
Hey all, we have a quick update for everyone who participated in the GitHub "Finish-Up-A-Thon"...
Hey all, we have a quick update for everyone who participated in the GitHub "Finish-Up-A-Thon" Challenge, followed by a more general challenge timeline change.
First off — wow. Our recent challenges have really taken off, and the "Finish-Up-A-Thon" was no exception. The quality and volume of submissions have been incredible (we received over 500 submissions!), and we want to make sure our judges have the time to give every entry the thoughtful review it deserves.
As a result, we're pushing the winner announcement back to June 25. Thank you so much for your patience, and for putting so much heart into your builds. We can't wait to share the results!
Second, we know we've been updating the timelines for quite a few challenges. Here's our latest winner announcement timeline for those of you who have participated in the last few:
Finally, we will be increasing the standard judging period for our challenges moving forward. Previously, we strived to select final challenge winners the week after submissions are due, but given our current pace of participation, we are now giving ourselves at least two full weeks so we don't run into these bottlenecks the future.
Thanks again for your participation. This is one of the best problems we could ever dream of having!
In the meantime, consider joining our game challenge — it's been a while since we've gotten to host one of these :smile:
{% embed https://dev.to/devteam/join-the-june-solstice-game-jam-1000-in-prizes-3jla %}
Happy coding! 💙
aiMost of us have seen a coding agent fail to complete a task we know it can do. We just don't...
googlecloudWhen building Generative AI applications, developers often encounter a massive bottleneck: sequential...
discussI’ve been thinking about sharing some electronic circuit posts on Dev.to — small circuits, DIY...
agentsWhat nobody tells you about exporting your multi-agent prototype to a local workspace. Every...
agenticarchitectAutonomous agents are genuinely good at answering messy business questions. Give one an LLM and a set...
aiPR volume went up, ticket quality didn't, and the gap got filled with LLMs on both sides of the review: bots reviewing, bots replying, bots occasionally arguing with bots about priorities that only existed in a teammate's head. Our CEO named the actual problem, and it's bigger than code review.
Workflows from the Neura Market marketplace related to this Stable Diffusion resource