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I wrote about building FlipperHelper without a backend a few weeks ago. That was the fun part. This is the other part — the one where you finish coding, push to the App Store, and realise nobody is coming. I'm a backend developer. Python, APIs, infrastructure — that's
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If you have a smartwatch or fitness tracker, there’s a high chance you’ve had that experience. You check your heart rate randomly and it’s a little higher than usual. Now it’s all you’re thinking about. Then you check again and again. And then comes a
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AI feels magical the first time you use it. You type a prompt, hit enter, and something useful appears almost instantly. It feels like the system understands you. It feels like the hard part is already solved. That feeling doesn’t last long. What comes next is not a crash
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AI agents are everywhere. They write emails, book calls, handle sales pipelines, and manage customer support systems. They’re the kind of tools that can make you three times more productive right up until the moment they make you redundant and have you doomscrolling jobs on LinkedIn. But while everyone
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Every big company faces two major shifts right now. The amount of SaaS tools, on-premise systems, and custom-built platforms needing to connect keeps increasing. At the same time large language models have moved beyond being just demos. People in businesses now want AI tools that do more than talk—they
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What’s so peculiar about a Saturday morning? Usually, techies just doze off till the afternoon, grab some brunch, and then jump into some hobby coding. But today, I found myself thinking about my first job back in 2013. I was in a backend role back then, and our team
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New Story by Abhilash Pakalapati May 8th, 2026 ← PreviousWhy My High-Stakes RAG Failed and How I Rebuilt it with Deterministic Graphs About Author Abhilash Pakalapati@abhilash-tech AI Engineer and Data Engineer who built scalable cloud and Big Data platforms,deployed AI/ML and GenAI solutions,optimized complex data pipelines. Read
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Author: Yurii Chudinov Date: April 24, 2026 Status: Engineering Note, Structural Hypothesis Companion papers: * [Chudinov, 2026a] SMRA (DOI: 10.5281/zenodo.18980854) * [Chudinov, 2026b] The Engineering Approximation Stack (DOI: forthcoming) * [Chudinov, 2026c] The Kleene Admission (DOI: forthcoming) Scope of This Note This note is a companion to the SMRA paper
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Why the rise of AI agents is creating Intelligence engineers As per the Gartner 2024 survey 62% of organizations using AI-driven orchestration saw 40% or greater reduction in pipeline maintenance time.The figure is not a forecast but it is actually happening. To understand this advent we will trace back
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It is a fact that discrete manufacturers invariably face the problem of planning, where demand is highly uncertain, the diversity of product is wide, the bill of materials (BOM) has a high complexity level, and there are long lead times involved. Statistical demand forecast models like ARIMA, exponential smoothing, and
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The same substations. The same cooling corridors. The same industrial shell, built to turn cheap power into compute. But inside a growing number of large mining sites in 2026, the shift is clear: ASICs are coming out, and GPUs are going in. This is not a cyclical adjustment. It is
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There is a peculiar property of black holes that astrophysicists find both elegant and terrifying: objects approaching the event horizon do not appear to fall in. From the outside, they seem to slow, redshift, and freeze -- suspended at the threshold for what looks, to distant observers, like eternity. Meanwhile,
