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@faun shared a link, 4 months ago
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[Cursor] Bugbot is out of beta

Bugbot hunts bugs in PR diffs, flagging logic slip-ups and strange edge cases. It then detects security gaps, blending top LLMs with custom heuristics. It plugs into the Cursor dashboard and runs dedicated Bugbot rules.Beta stats: 1M+ reviews, 1.5M+ issues found. Half the bugs are fixed before merge.. read more  

[Cursor] Bugbot is out of beta
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@faun shared a link, 4 months ago
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Seeing like an LLM

LLMs function as next-token predictors. With scant user context, they hallucinate—spinning fresh backstories. As these models morph into autonomous agents, context engineering—feeding facts, memory, tools, guardrails—halts rogue behavior. Trend to watch:A jump in context engineering. It pins LLMs t.. read more  

Seeing like an LLM
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The Future of Threat Emulation: Building AI Agents that Hunt Like Cloud Adversaries

AI agents tap MCP servers andStrands Agents. They fire off tools that chart IAM permission chains and sniff out AWS privilege escalations. Enter the “Sum of All Permissions” method. It hijacks EC2 Instance Connect, warps through SSM to swipe data, and leaps roles—long after static scanners nod off. .. read more  

The Future of Threat Emulation: Building AI Agents that Hunt Like Cloud Adversaries
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Microsoft Copilot Rooted to Gain Unauthorized Root Access to its Backend System

April 2025 Copilot Enterprise update slipped in aJupyter sandbox. It snuck in aPATH-poisonable pgrepat root’s entrypoint. Attackers could hijack that forroot execution.Eye Securityflagged the hole in April. By July 25, 2025, Microsoft patched this moderate bug. No data exfiltration reported. Why it.. read more  

Microsoft Copilot Rooted to Gain Unauthorized Root Access to its Backend System
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From Raw Data to Model Serving: A Blueprint for the AI/ML Lifecycle with

Post maps out aKubeflow Pipelinesworkflow onSpark,Feast, andKServe. It tackles fraud detection end-to-end: data prep, feature store, live inference. It turns infra into code, ensures feature parity in train and serve, and registers ONNX models in theKubeflow Model Registry... read more  

From Raw Data to Model Serving: A Blueprint for the AI/ML Lifecycle with
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Intel CEO Letter to Employees

Intel scraps itsGermanyandPoland foundries, shifting assembly fromCosta RicatoVietnamandMalaysia. It slows Ohio fab construction while ramping upIntel 18A/18A‑Pand planningIntel 14Aaround key customers. SMT returns. Focus shifts to Panther Lake, Nova Lake, and Granite Rapids.AI strategy pivots towar.. read more  

Intel CEO Letter to Employees
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AI Coding Tools Underperform in Field Study with Experienced Developers

METRran an randomized controlled trial  (RCT) with 16 open-source devs. They tackled real-world code tasks usingClaude 3.5andCursor Pro. The pitch:40%speed boost. Reality:19%slowdown. A deep dive into 246 screen recordings laid bare friction in prompting, vetting suggestions, and merging code. That .. read more  

AI Coding Tools Underperform in Field Study with Experienced Developers
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The Cybersecurity Blind Spot in DevOps Pipelines

DevOps pipelines serve as superhighways for cybercriminals to target with credential leaks, supply chain infiltration, misconfigurations, and dependency vulnerabilities. Security must evolve with development to combat these sophisticated attacks... read more  

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Self-hosting Trigger.dev v4 using Docker

Trigger.dev v4 sharpens self-hosting. It pins everything toDocker Compose. It bakesregistryandobject storagein. It chops YAML bloat. Env-var docs unify configs. Resource caps lock down security. Scaling? Spin up more worker containers... read more  

Self-hosting Trigger.dev v4 using Docker
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How GitHub engineers tackle platform problems

Product engineersare like builders ofGundam models, construcing the final product, whileplatform engineerssupply the tools needed to build these kits. Understanding theGundam analogyhelps differentiate engineering roles at GitHub... read more  

FAUN.dev() is a developer-first platform built with a simple goal: help engineers stay sharp without wasting their time. It curates practical newsletters, thoughtful technical blogs, and useful developer tools that focus on signal over noise.

Created by engineers, for engineers, FAUN.dev() is where experienced developers turn to keep up with the fast-moving world of DevOps, Kubernetes, Cloud Native, AI, and modern programming. We handpick what matters and skip the fluff.

If it’s on FAUN.dev(), it’s worth your attention.

Beyond curation, we run a course marketplace (WIP) designed to keep developers current. These courses go deep into the subjects that shape real-world work—things like Kubernetes internals, modern DevOps workflows, cloud-native architecture, and using AI tools to build faster and smarter. It’s practical learning, taught by people who’ve done the work. Developers from companies like GitHub, Netflix, and Shopify already rely on FAUN.dev() to stay on top of their game. They trust us because we keep it real: no hype, no filler, just what you need to grow and do your best work. For sponsors and partners, FAUN.dev() offers access to a focused, engaged audience of technical professionals. This isn’t just another broad developer community—it’s a place where smart engineers go to get smarter. If you have something meaningful to offer them, you’ll be in good company. In short, FAUN.dev() is more than a content hub. It’s a place to grow, to learn, and to connect with what really matters in software today.