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Why Canada Is the Best Place to Build Healthcare AI Right Now

5d ago · 7 min read · Every week I talk to a founder who's building healthcare AI in San Francisco and spending 40% of their engineering time on HIPAA compliance across fifty different state-level interpretations. Meanwhil

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ASArpita Shreesystembreakdown.hashnode.dev

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How LinkedIn's Algorithm Ranks Your Profile ?

6d ago · 9 min read · I wasn't active on LinkedIn for months. My Profile was dead! But then someone gave me one piece of advice "at minimum, make sure your profile tells people who you are and what you do." So I spent thre

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MKMudassir Khanmudassirworks.hashnode.dev

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RAG vs fine tuning: how to choose for a production LLM feature

Jun 4 · 7 min read · When you are building a production LLM feature that needs to be factually accurate, you will eventually face this decision: retrieve the facts at query time, or bake the knowledge into the model throu

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GJGlendel Joubert Fyne Acostaopenmas.hashnode.dev

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Building AI Workflows Is Easy. Making Them Reliable Is Systems Engineering

May 30 · 9 min read · Building the first version of an AI workflow is usually easy. Connect an LLM to a few tools. Add some instructions. Let the model decide what to do next. Run the demo. It works. The problem starts l

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SPStefan Petschinkastefanpetschinka.hashnode.dev

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A local leather studio in Cologne just outranked Hermès

May 29 · 1 min read · A local leather studio in Cologne just outranked Hermès. Not in paid search. Not in a campaign. In the answer of ChatGPT and Google AI Search. When you ask ChatGPT or Google AI Mode about Kelly Bag re

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SPStefan Petschinkastefanpetschinka.hashnode.dev

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Machine First: Why AEO Is Not SEO 2.0

May 29 · 1 min read · This is an excerpt from my full article on AEO architecture. Answer systems don't rank, they infer. That requires a fundamentally different approach to how we build entity signals, structured data and

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AJAlen Joypragmaticstack.in

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Why Most Agentic AI Systems Fail in Production — A Software Architect's Perspective

May 28 · 11 min read · 🗓️ Last updated: May 2026 — reflecting current production patterns and the OWASP LLM Top 10 (2025). Every few years, the software industry rediscovers the same lesson. A new architectural pattern ar

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DKDivyajot Kaurai-beginners-journey.hashnode.dev

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Part 8: Overfitting vs Underfitting in Machine Learning

May 28 · 3 min read · Imagine a student preparing for an exam. One student memorizes every single question and answer from previous papers without actually understanding the concepts. Another student barely studies and onl

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PDPriyanka Dvectorverse.hashnode.dev

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The New AI Stack: LLMs, Vector Databases, Agents, and Memory

May 26 · 4 min read · A few years ago, building software was predictable. Frontend. Backend. Database. APIs. Deploy. Pray nothing breaks on Friday night. Now every startup deck contains: AI agents, memory systems, retrieva

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ACAnik Chandanikchandml.hashnode.dev

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#1 Performance Metrics in ML

May 23 · 5 min read · ML models are not judged only by whether they work or not. We need mathematical metrics to measure how good a model actually is. These metrics help us to compare models, improve predictions and avoid

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Trending tags this week

Why Canada Is the Best Place to Build Healthcare AI Right Now

How LinkedIn's Algorithm Ranks Your Profile ?

RAG vs fine tuning: how to choose for a production LLM feature

Building AI Workflows Is Easy. Making Them Reliable Is Systems Engineering

A local leather studio in Cologne just outranked Hermès

Machine First: Why AEO Is Not SEO 2.0

Why Most Agentic AI Systems Fail in Production — A Software Architect's Perspective

Part 8: Overfitting vs Underfitting in Machine Learning

The New AI Stack: LLMs, Vector Databases, Agents, and Memory

#1 Performance Metrics in ML