The results are in! We are thrilled to announce the winners of the OpenClaw Challenge.
Over the past few weeks, you've been building, writing, and sharing your OpenClaw experiences with the community. Whether you were automating the mundane or tackling real-world infrastructure challenges, your submissions were a blast to review.
Selecting six winners from this pool of submissions was no easy task. Let's give a round of applause to our winners!
🎉 Congratulations To…
OpenClaw in Action Winners
@prema_ananda's WhiteHat is an autonomous ethical hacking agent that takes on the repetitive cycle of pentesting: scanning, reasoning, acting, and documenting, so you don't have to. A single SOUL.md file is what transforms the underlying LLM from a text generator into a methodical, principled penetration tester.
@lewisawe built KPLC Sentinel, a WhatsApp-based agent that analyzes prepaid electricity token purchase history to predict when a user's power will run out before it actually does. The result is a practical, real-world automation that solves a frustrating problem for anyone on a prepaid electricity plan.
@jasmin used OpenClaw's persona files to build a multi-agent system where two AI agents can talk to each other with controlled, limited information. A markdown file acts as a privacy contract, determining exactly what each agent is and isn't allowed to reveal about its human.
Wealth of Knowledge Winners
@dannwaneri shares a hard-won lesson: don't let a misconfigured OpenClaw agent burn through $5,600 in API credits in a month due to a flawed assumption in a spec file. The post breaks down what went wrong and introduces a spec-writing habit that prevents runaway token costs before they start.
@nirbhay_gautam_2a9e232b95 makes the case for why they are done trusting cloud-based AI tools with personal data, and how OpenClaw became the alternative. It's a sharp, personal essay about data ownership, the tradeoffs of convenience, and what it actually means to run AI on your own terms.
@gramli walks through how to run OpenClaw locally using Windows Sandbox for secure, disposable isolation. The guide is practical and reproducible, making it a great reference for anyone cautious about running AI agents on their main machine.
Prizes
Each winner will receive:
- $200 USD
- DEV++ Membership
- Exclusive DEV Winner Badge
All participants with a valid submission will receive a completion badge on their DEV profile.
What's Next?
The Gemma 4 Challenge is live! Whether you love to build or love to write, there's a prompt for you and a $3,000 prize pool up for grabs!
Thank you for participating! See you next time. 🦞
