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Reflections on AI (large language models) in various fields

List of articles on the impact of AI(LLMs) on a developer's life from various perspectives, including: research, students, beginners, professionals, and others: professional: https://jpain.io/god-damn-ai-is-making-me-dumb/ https://ky.fyi/posts/ai-burnout Company: https://mastrojs.github.io/blog/2026-05-23-is-AI-causing-a-repeat-of-frontends-lost-decade/ Research: https://www.moderndescartes.com/essays/ai_and_expertise/ Academy https://htmx.org/essays/yes-and/ https://vickiboykis.com/2026/05/28/

aillmprogramming
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ExternalSoftware Engineering
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RAG - Hybrid search and RAG pipeline using FAISS DB

Hybrid Search Hybrid search is a combination of dense embeddings and sparse embeddings. Dense embeddings focus on semantic meaning, while sparse embeddings focus on exact keyword matching. By combining both approaches, hybrid search improves retrieval accuracy and relevance. OpenSearch is commonly used as a search engine for: Log analysis Observability and monitoring One of the key features of OpenSearch is hybrid search, which combines: Vector search (dense retrieval) BM25-based search (spars

aibeginnersrag
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ExternalSoftware Engineering
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Why ROU Asset Depreciation Checks Fail When Schedule And Journal Logic Drift

The depreciation problem usually gets reported as a journal problem. Someone sees a depreciation expense that looks off. The export no longer ties cleanly. The journal layer gets blamed first. In practice, the bug is usually upstream by the time anyone opens the journal tab. Most IFRS 16 depreciation failures are drift failures. The schedule still looks plausible. The closing ROU asset is still in the right ballpark. What broke was one of the connections underneath it: the liability was remeasur

productivity
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Tossed The T.V. but Kept the Remote? Here's how to NOT generate more E-Waste.

This is a submission for the GitHub Finish-Up-A-Thon Challenge Link to the Repo What I Built So what is this? Doesn't look like an API 👁️👁️ Tossed The TV Kept the Remote (TTVKTR) is a simple solution to the common problem of ending up with leftover Infrared(IR) Remotes from appliances long after the appliances are gone. They should be trivially easy to use with whatever you want, instead of ending up in landfills. After finding an old Apple TV Remote in the archi

devchallengegithubchallengeprogramming
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ExternalSoftware Engineering
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The Architecture Decisions That Actually Mattered: Building a Production-Ready Multi-Service Backend

What most system design articles skip is the part where you explain why the boring choice was the right one I built a platform that runs social media giveaway events, a gift card marketplace, and telecom gift vending — all in one system, all sharing the same PostgreSQL database and Redis instance, all running in production on infrastructure that costs €27 a month. This article is not about the product. It is about the seven architectural decisions I made while building the backend, why I ma

backendsystemdesignmicroservices
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ExternalSoftware Engineering
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Frontier Logic at Local Speed: The 2026 Strix Halo Ultimate Benchmark Suite

The era of choosing between "Small & Fast" or "Large & Slow" for local AI is ending. With the release of the Qwen 3.6 family and architectural breakthroughs in inference engines, we can now run frontier-class reasoning on personal hardware at human-reading speeds. In this technical audit, we benchmark the AMD Strix Halo (Radeon 8060S) using a custom-tuned llama.cpp stack to identify the optimal configuration for sovereign intelligence. Our test host ("Stark") utilizes the Strix Halo architecture

airocmperformance
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Why I Stopped Letting AI Write My Code (May 2026)

This article shares why a web engineer holding a Claude Code Max 20x plan has mostly stopped using AI for coding at work. It's not about abandoning AI — it's about narrowing down where I let AI take over. Looking back honestly, I was acquiring knowledge faster before I delegated most coding to AI. Once I drastically cut down on writing code by hand, I quietly gave up a side benefit: the investment in growth that came along for the ride with the act of writing. In learning theory terms: output (w

aiclaudecodecodex
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ExternalSoftware Engineering
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Building a PySpark and AWS Glue ETL Pipeline for Search Keyword Revenue Analysis

I published a public data engineering project that demonstrates a cloud-based ETL pipeline for analyzing web analytics search keyword revenue. The project uses PySpark, AWS Glue, Amazon S3, and Terraform to process hit-level web analytics data, extract external search engine domains and keywords, parse revenue, and generate a sorted reporting output. Key concepts covered: Batch ETL pipeline design This is a generic open-source portfolio project and does not include proprietary or company-provide

awsdataengineeringshowdev
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