Your AI Code Can Be Elegant Too
As the Machine Learning Engineering Manager at an AI-powered SaaS company, I get a front-row seat to the machine learning (ML) code written by data…
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My drift board learned to say "I don't know". Here is what it still cannot say.
Archival copy of record, committed before this post: https://github.com/Tania-coder/SEISMOGRAPH/blob/main/docs/reports/2026-09-22-weather-report-02.…
От 6 часов до 20 минут: как мы ускорили коллаборативную модель в рекомендациях Авито
Привет, я Салават Динмухаметов, senior ML-engineer в команде рекомендаций Авито . В статье расскажу, как мы изменили систему рекомендаций на главной…
MLOps Best Practices 2026
MLOps Best Practices 2026 {"title": "MLOps Best Practices 2026: Scaling AI from Prototype to Enterprise Production", "content": "### Introduction\n\…
Migrating to Native Git in SageMaker Unified Studio
Version control in analytical data platforms has always been a second-class citizen — tolerated, not designed. SageMaker Unified Studio just changed…
Four bugs from building a platform where AI agents publish autonomously
I spent six weeks building a publication where AI agents write articles, an automated moderator approves or rejects them, and no human reviews anyth…
Бесшовный переход в индустрию: как закрыть разрыв между вузом и реальным ИИ‑проектом
Привет, Хабр, я Анастасия Сапрыкина, работаю на стыке двух миров: академического и индустриального. Сейчас в России активно развивается пр…
От legacy до промышленной платформы: инженерная эволюция OSA в «Магнит»
Как мы провели проект через четыре «эпохи» — от ручных запусков на Windows‑планировщике до Spark + k8s на масштабе сет…
MLOps for LLM: A Case Study on Dresscode
I've recently participated in the Gemma 4 challenge here on DEV.to, but fell short compared to many amazing projects. I really liked LIKAS . I encou…
[Перевод] Как оптимизировать LLM-инференс в 2026 году
Если вы в 2026 году запускаете LLM в продакшене, то почти наверняка больше всего денег тратите на инференс. Одна неоптимизированная модель размером…
Why multi-agent orchestration is harder than it looks
One AI agent answering a question is useful. Five agents that divide a complex task, pass state to each other, and act on live enterprise systems is…
RLAIF Is Eating RLHF — Here Are the Four Places Human Feedback Still Wins
RLAIF is having a moment. Walk through any alignment paper or vendor pitch from the last six months and you'll see the same claim: replace your huma…
I Built a Complete AI Infrastructure Stack from Scratch — Here's What I Learned
I Built a Complete AI Infrastructure Stack from Scratch — Here's What I Learned Most AI projects start at the top of the stack. You grab an LLM API,…
QAT vs PTQ on our edge vision model: 6 months of A/B data
TL;DR: We ran post-training quantisation (PTQ) and quantisation-aware training (QAT) side by side on the same defect-classification model deployed o…
Part 2: Enterprise Decision Intelligence Architecture: AI Governance, Threshold Policy Engines, and Operational AI Systems
Part 1 showed how to evaluate binary classification thresholds in Python. This part asks the harder enterprise question: What happens when that thre…
llm-nano-vm v0.8.0 — deterministic FSM runtime for LLM pipelines, now with output validation and per-step timeouts
PyPI: pip install llm-nano-vm GitHub: http://github.com/Ale007XD/nano_vm MCP gateway: http://github.com/Ale007XD/nano-vm-mcp I've been building a de…
Stop paying for idle GPUs in your CI: batching LLM eval jobs
TL;DR: Running LLM evaluations on every PR will burn your GPU budget faster than you can blink. We cut our eval spend by about 60% by batching jobs…