MLOps & LLMOps

"How do you deploy flows to production?" I ask this question in every governance workshop. The most common answer is still "export as managed, import manually,

If you maintain an MCP server, at some point you ask this. You've got twenty tools, you're about to add five more, and something feels wrong about it — but you

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MLOps, short for machine learning operations, is a set of practice employed to make machine learning model development deployable, usable… Continue reading on M

MLOps, short for machine learning operations, is a set of practice employed to make machine learning model development deployable, usable… Continue reading on M

PSI + KS testleri, FastAPI, Prometheus, MLflow ve auto-retrain ile uçtan uca mini MLOps mimarisi Continue reading on Medium »

Training a machine-learning model is only the beginning. The real challenge is getting it into the real world, keeping it reliable, and… Continue reading on Med

AI coding agents are the first contributors that read your entire repository and run shell commands non-interactively on day one. But… Continue reading on Mediu

AI coding agents are the first contributors that read your entire repository and run shell commands non-interactively on day one. But… Continue reading on Mediu

AI coding agents are the first contributors that read your entire repository and run shell commands non-interactively on day one. But… Continue reading on Mediu

Data pipelines have always been dumb by design — do exactly this, in exactly this order, and scream if anything moves. In 2026, teams are… Continue reading on M

From LLM fundamentals and open-source models to RAG, fine-tuning, AI agents, MCP, and production AI systems, these are the courses worth… Continue reading on Le

Today the most important factor in AI is cost. My idea is to split ML models inference (closed ones, proprietary) across server and edge computing on clients, a

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AI spend is hard to see. In most setups the same gateway credential is used by production, every preview environment, CI, and whatever load test someone ran on

Building a machine learning model is only one part of the journey. Here’s how real-world ML projects move from a business challenge to… Continue reading on Medi

A five-person team brought me in last month to help ship their first production model, a churn scorer...

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Response to Ollama Production Queries to the previous post Excellent questions — you've...

Why precision rather than recall is the product for a review bot, the comment-budget arithmetic that follows, and the one honest metric for whether it is workin

Run this against whatever you already have. `from collections import Counter def pass_all_k(run,...

Nobody tells you this until you’re on-call at 2 AM: testing AI pipelines is significantly harder than...

This article is part of my MCP series. In the previous article, I covered authentication, tool...

How Deployments, Services, Jobs, configuration, storage, autoscaling, and scheduling turn a containerized model into a production service. Continue reading on T

Why MCP Servers Need Verification Before Production The Model Context Protocol (MCP) is...

Establishing robust MLOps pipelines for model versioning, A/B testing, canary deployments, monitoring...

A complete walkthrough of a full-stack online store with JWT auth, OTP verification, Razorpay...

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When I first started out in data science, I spent almost all my time inside Jupyter Notebooks (.ipynb). I would tune hyperparameters, plot… Continue reading on

📖 TL;DR The 2026-07-28 spec shipped final on July 28, 2026 (RC locked May 21). It is the biggest...

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I have two FormLM environments: staging (staging.formlm.me) and production (formlm.me). I use staging...

MCP makes it easy to expose tools. That creates new failure modes. Here's how to design tools, manage catalogs, and segment gateways for enterprise scale.

An MLOps rollout decision is not “the candidate metric is higher, so ship it.” A defensible gate first refuses insufficient evidence, then protects hard reliabi

A working draft framework that asks one hard question — and refuses to answer with a vanity percentage. Continue reading on Medium »

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Why Is MLOps Essential for Scaling Machine Learning Projects? Continue reading on Medium »

Every week I watch someone spin up their first Model Context Protocol server, get echo working, and...

MLOps Serisi — Yazı 2/4 Continue reading on Medium »

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Bonsai 27B shrank from 54 GB to 3.9 GB while keeping math and coding surprisingly strong — but tool use and instruction following took a… Continue reading on Da

What Skills Do You Need for MLOps and AIOps Careers in 2026? Continue reading on Medium »

Why most ML models die quietly in production Continue reading on Medium »

Why most ML models die quietly in production Continue reading on Medium »

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By: Asfand Gul Kasi Continue reading on Medium »

When enterprises move algorithm models from development to production, the real challenge begins after the model is built. A model must navigate file packaging,