I’m Necati Demir, a PhD Computer Scientist with 20 years of industry experience, who transforms experimental ML projects into production-ready systems through expertly crafted data pipelines and infrastructure. With experience in end-to-end MLOps implementation, I bridge the gap between data science innovation and real-world production deployment.
Now as an independent consultant based in the US, I help organizations reduce model deployment time from months to days, and achieve significant performance gains through systematic approaches to data engineering. My unique combination of not only developing end-to-end ML pipelines but also building ML models helps me see the process end to end.
I Found the AI Cheat Code That Will Make You a 10x Developer
Most developers ask AI tools to write a function or fix a bug. That’s fine, but here’s the cheat code I discovered: treat AI like a developer on your team. When I do that, everything changes.
The Pattern I Discovered I use AI tools every day in my professional work and personal projects. Claude, ChatGPT, Gemini; I subscribe to all of them. Over time, I’ve noticed a pattern.
These tools excel at zooming in. By that, I mean they’re excellent at specific tasks: generating code, writing tests, refactoring functions, etc… . We all know this.
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Why 90% of Engineers Can't Debug (They're Looking in the Wrong Place)
Have you ever joined a new team with a new tech stack, with a new process, and a production issue already waiting for you? Here is how I ramp up fast: I zoom out before I zoom in.
The Problem: Everyone Hunts Where They’re Comfortable During my consultant gigs, I am constantly dropped into an unfamiliar environment. New teams, new architecture, new tech stack, new development process, new deployment process, it’s always new. The question is always the same: how do you stay on top of it?
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GPT-5 Fast vs Thinking vs Pro: How They Actually Work
OpenAI recently released the GPT-5 family, introducing three distinct options for Pro users: GPT-5 Fast, GPT-5 Thinking, and GPT-5 Pro.
While it’s common knowledge that GPT-5 Fast handles simple tasks and GPT-5 Pro tackles complex ones, the underlying mechanisms remain unclear to many users. This post provides a concise explanation of how each variant operates and when to use them effectively.
GPT-5 Fast For the context of this article, we will use GPT-5 Fast as our base model, think of it as a black box optimized for speed, good old LLM. When you submit a query, it processes the request and delivers an answer quickly without extensive deliberation.
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The AGI Definition War That's Breaking Contracts & Changing Laws
We keep hearing this: “AGI is coming.” But what exactly is AGI? Let’s explore this critical question.
Three Different Lenses Let’s look at AI through three different lenses.
The Economics Lens OpenAI defines AGI as “highly autonomous systems that outperform humans at most economically valuable work.” Their focus is entirely economic—it’s about jobs and economic productivity.
When framed this way, the definition essentially states: if AI surpasses humans at most work that people are paid to perform, then we have achieved AGI. The moment AI can produce the majority of economically valuable work, we’ve crossed the AGI threshold.
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Don't Be a Tool Engineer
“So, what kind of engineer are you?”
“I’m a Python engineer.”
Every time I hear this, I cringe a little. Not because Python isn’t amazing—it absolutely is. But because somewhere along the way, we’ve started defining ourselves by our tools instead of our craft.
I’m sure you’ve heard it too: “I am an AWS engineer,” “I am a React developer,” as if the tool has become their entire professional identity.
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Why Your $200k+ Engineers Are ACTUALLY Useless AND It's Your Fault
There’s a really weird communication pattern that I keep seeing all the time in big companies and small companies.
Picture this: You’re hiring an employee, consultant, contractor, whatever you want to call them. You think this person has good experience and you’re paying them hundreds of thousands of dollars. Once you hire them, you tell them, “Hey, I want you to do this.”
This is super weird. You’re not explaining the problem. You’re just trying to use this person as a human tool.
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Why You Shouldn't Use Microservices (Unless You Should)
I want to argue that you should build your product on microservices; not because of technical reasons, but because you should see it as a team management strategy.
The Double-Edged Sword of Microservices Let’s zoom out and first remember what a microservice is. A microservice is basically a small, deployable piece of service that, when meshed together with others, forms a larger application. If you’re already working with microservices or even if you haven’t built any so far, you’ve probably heard about it.
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The Decision Chain Mindset: Why Leaders Blame the Wrong People
Have you ever been in a meeting where people just keep putting band-aids on problems but don’t discuss how they came to that point? Let me talk about the decision chain mindset.
Understanding the Decision Chain Picture this: You make a decision, or someone makes a decision at a high level. Let’s call this Decision A.
Based on this decision, another decision is made. Let’s name it Decision B.
And based on that, now you have to make another decision. Let’s call it Decision C.
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The Leadership Lesson I Learned from a Coffee Shop
I walked into my neighborhood coffee shop for my regular Americano, but walked out with a lesson, a leadership lesson. Let me explain.
The Beginning This coffee shop opened here in my town around three years ago. Since then, I have become a regular customer. If I have time in the morning, I just walk there, I’m even the first or second customer, I have my morning coffee and walk back home. That’s how I start my days.
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An Introduction to StarRocks: My Experience Using It (Plus My Docker Setup)
An Introduction to StarRocks: My Experience Using It (Plus My Docker Setup) I’ve been working on projects including StarRocks for the last couple of years. When I first used it, that shocked me how lightning-fast the queries are. I decided to write an article about StarRocks. This article will serve me as future notes too ;) Let’s dive.
Table of Contents What is StarRocks? My Journey with StarRocks 2.1. Key Features That Makes StarRocks StarRocks Why Choose StarRocks? 3.1. Performance That Matters 3.2. Cost-Effective Scaling 3.3. Real-World Use Cases Architecture Deep Dive 4.1. Frontend (FE) Nodes 4.2. Backend (BE) Nodes Getting Started with StarRocks Using Docker 5.1. Quick Setup Guide 5.2. Repository Features Your First StarRocks Query Advanced Features to Explore 7.1. Materialized Views for Acceleration 7.2. Real-Time Data Ingestion 7.3. Window Functions for Advanced Analytics Performance Optimization Tips Monitoring and Operations 9.1. Key Metrics to Track 9.2. Backup and Recovery Community Conclusion 1. What is StarRocks? We can define StarRocks as high-performance analytical database designed for online analytical processing (OLAP) workloads. It was forked from Apache Doris but it has evolved into a powerful solution.
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