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@laura_garcia shared a post, 11 hours ago

Software Developer, RELIANOID

𝗥𝗘𝗟𝗜𝗔𝗡𝗢𝗜𝗗 𝗮𝘁 𝗟𝗼𝗻𝗱𝗼𝗻 𝗧𝗲𝗰𝗵 𝗪𝗲𝗲𝗸 𝟮𝟬𝟮𝟲

🚀 𝗝𝗼𝗶𝗻 𝗥𝗘𝗟𝗜𝗔𝗡𝗢𝗜𝗗 𝗮𝘁 𝗟𝗼𝗻𝗱𝗼𝗻 𝗧𝗲𝗰𝗵 𝗪𝗲𝗲𝗸 𝟮𝟬𝟮𝟲 📅 June 8–12, 2026 📍 London, United Kingdom London Tech Week brings together innovators, enterprises, startups, investors, and technology leaders to explore the future of AI, cybersecurity, cloud infrastructure, digital transformation, and emerging technologi..

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@work4bots started using tool Spring , 2 days, 7 hours ago.

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@work4bots started using tool Helm , 2 days, 7 hours ago.

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@work4bots started using tool Azure Pipelines , 2 days, 7 hours ago.

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@work4bots started using tool Azure Kubernetes Service (AKS) , 2 days, 7 hours ago.

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@work4bots started using tool Azure , 2 days, 7 hours ago.

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@work4bots added a new tool Bicep , 2 days, 7 hours ago.

Story FAUN.dev() Team

@eon01 shared a post, 2 days, 11 hours ago

Founder, FAUN.dev

AWX in Action is out, and there's a course

#red hat... #ansible #Tower #AWX

"AWX in Action: Ansible Orchestration at Scale" is now available in print and ebook. It covers running AWX on Kubernetes for real, not a sandbox demo that falls over the moment you add a second execution node.

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@varbear shared a link, 2 days, 12 hours ago

FAUN.dev()

When Code Becomes Cheap, What's Left?

Teams that use Claude Opus 4.6 for spec-driven development generate code at low cost, so they spend scarce developer time on review and QA. Developers create more value by judging code than by typing it... read more

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@varbear shared a link, 2 days, 12 hours ago

FAUN.dev()

I Did 11 Technical Interviews in 60 Days. Here Is the Pattern Nobody Tells You.

The key insight from the article is that at mid-to-senior backend levels, coding rounds matter least while judgment, communication, structure, and ability to defend decisions are critical. Focus on rehearsing key design, incident, and behavioral answer structures to succeed, not just LeetCode... read more

INTELLECT-3 is a frontier-class 100B+ Mixture-of-Experts language model developed by Prime Intellect and trained end-to-end using their large-scale asynchronous RL framework, PRIME-RL. Built on the GLM-4.5-Air base model, INTELLECT-3 combines supervised fine-tuning with long-horizon reinforcement learning across hundreds of verifier-backed environments spanning math, code, science, logic, and agentic tasks.

The model was trained on a high-performance cluster of 512 NVIDIA H200 GPUs across 64 nodes, supported by Prime Intellect’s Sandboxes execution engine, deterministic compute orchestration, and Lustre-backed distributed storage. The result is a model that surpasses many larger systems in reasoning benchmarks while remaining fully open-source.

Prime Intellect released not only the model weights but also the full training recipe: PRIME-RL, Verifiers, the Environments Hub, datasets, and evaluation suites. INTELLECT-3 is positioned as a foundation for organizations seeking to post-train or customize their own frontier-grade models without relying on proprietary AI labs.