10/ On-Call Reality Check Ask how they handle a critical incident at 2am on a Sunday. The answer tells you everything about how the team actually operates. No clear protocol means you are inheriting someone else's chaos.
SYSTEMS
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System Design: Define Problem Constraints Before Solutions
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7/ System Design Under Pressure Before drawing anything, spend the first 15 minutes asking about constraints. Read and write ratios. Latency requirements. Acceptable staleness. Senior engineers define the edges of the problem before they solve it.
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Developer leverage: Deep systems understanding and precise AI direction
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The developers who will have the most leverage in 5 years are the ones who understand systems deeply and can direct AI tools precisely. That combination requires both.
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Agent Memory Management: Filtering, Sharing, and Temporal Consistency
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Great questions. – No, not everything should be stored. The agent needs to filter what's actually useful vs what's not. – Yes agents can ahev shared memory, and most memory infra support multi tenancy. – For contradictions, timestamped facts let newer info override older
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Intelligent forgetting in AI systems memify strengthens useful paths
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That's a fair reframe. Knowing what to forget is arguably harder than knowing what to remember. memify() is exactly aimed at that, strengthening useful paths and letting stale ones decay. The title optimizes for the hook, but you're right that intelligent forgetting is the
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Graph Search vs Vector Search: Beyond Similarity in AI
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Exactly. Vector search answers "what's similar" but not "how are these connected." The Alice-project-outage example in the post explains this. Most real questions need at least two hops, and that's where graphs become essential, not optional.
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Multi-stage verification gates ensure AI output quality
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The staged approach works because each stage is a quality gate. You're not trusting the output, you're verifying it at multiple checkpoints before it goes anywhere.
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AI Agents Require Infrastructure and Security Strategy Overhaul
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Your AI Strategy Needs A Rebuild Before Agents Break It #AI agents are moving from pilot projects into real business roles, but many companies are discovering that their #cloud #infrastructure, #security models, and #workflows were built for people, not #autonomous systems.
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Wendy: New Operating System for Physical AI and Edge Devices
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Today I’m incredibly excited to announce Wendy.
— Maximilian Alexander (@signalgaining) 14 avril 2026
Wendy is an operating system and developer platform for Physical AI — built to make it dramatically easier to build and deploy on NVIDIA Jetson, Raspberry Pi, and other edge devices.
We think robotics, edge AI, industrial systems,… pic.twitter.com/pTLLpPgfRSToday I’m incredibly excited to announce Wendy. Wendy is an operating system and developer platform for Physical AI — built to make it dramatically easier to build and deploy on NVIDIA Jetson, Raspberry Pi, and other edge devices. We think robotics, edge AI, industrial systems, autonomous machines, and smart cameras should be far simpler to create. Less setup. Less infrastructure pain. Faster time to first demo. This is the start of something big. Get started at wendy.sh
→ View original post on X — @scobleizer, 2026-04-14 05:12 UTC
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Domain Specific Architectures for AI Inference Systems
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Domain Specific Architectures for AI Inference! #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #NLProc #DataScientist #Linux #Programming #Coding #100DaysofCode