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#weeklyretro
What was your win this week!?
👋👋👋👋 Looking back on your week -- what was something you're proud of? All wins count -- big or small...
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Insights, Ideas & Innovation
Explore the latest insights, development trends, practical guides, and technology stories from the global developer community.
Disappeared Since March: Taking a Long Break Was My Best Decision Yet
If you checked my profile recently, you probably noticed my page has been completely quiet since...
#eventsinyourcity#claude
Claude on Google Cloud workshop | NYC | 9/30
On Wednesday, September 30, Anthropic and Google Cloud are co-hosting a hands-on developer workshop...
#ai#claude
This video is about how this video was made
This video (the script, the voice timings, the source code, the storyboard, the briefs the subagents...
#buildinpublic#webdev
I Turned DEV.to Into a Walkable 3D Library — Debugging It Has Been a Nightmare
DEV Library is my idea of first-person 3D reimagining of DEV.to. Not a themed scene with some...
#devchallenge#bugsmash
Congrats to the Summer Bug Smash Winners!
We are thrilled to announce the winners of DEV's Big Summer Bug Smash powered by Sentry! This...
#opensource#flutter
Building File4Base: The Modern, Open-Source Alternative to old file bases (Powered by Antigravity)
For decades, platforms like Claris FileMaker, Microsoft Access, and 4D enabled businesses to build...
#gemma#googlecloud
Running a Jev-Style Decision Model on One TPU v6e: What Fits, What It Costs, and What Changes From a GPU
Gemma 4 E2B, E4B, 12B and a 26B-A4B fp8 build read by their label probabilities with vLLM on one TPU v6e chip, checked against the same read on an NVIDIA L4 and against Jev 1.13.0's published results. What fits one chip, how to read labels when vLLM on TPU returns only the top 32 log-probabilities, speed, cost, and why no 31B loads today.
#claude#googlecloud
Claude Opus 5.5 is now available on Google Cloud
Everyday complex tasks? No problem. Opus 5.5 handles long-running coding and knowledge work while...
#welcome
Welcome Thread - v 394
Leave a comment below to introduce yourself! You can talk about what brought you here, what you're...
#top7#discuss
Top 7 Featured DEV Posts of the Week
Welcome to this week's Top 7, where the DEV editorial team handpicks their favorite posts from the...
#gemma#llamacpp
A 4 GB Laptop GPU vs a 6-Core CPU on Gemma 4, Re-Measured in ABBA Order: 4.1x
Gemma 4 E2B q4_0 served by llama.cpp on one laptop, CPU-only and on a GTX 1650 Ti, rebuilt on CUDA 13.4 and re-measured in CPU, GPU, GPU, CPU order with a temperature gate. The card takes decode by 4.14x, and run order moves the answer by about 2%.