📰 Medium · DevOps

One of the biggest challenges in enterprise AI is integrating Large Language Models (LLMs) securely into existing infrastructure. Continue reading on Medium »

Your agent test suite is slow, expensive, and flaky for one reason: it rolls a live, non-deterministic model on every run. Continue reading on Medium »

We shipped our LLM feature on a Tuesday. By Thursday 3AM, it was returning hallucinated answers with 100% confidence. No errors in the… Continue reading on Towa

Closing the gap: High-performance coding models you can run on your own infrastructure instead of restrictive APIs. Continue reading on Medium »

There’s a moment that kills most “AI for logs” projects. Continue reading on Towards AI »

Building AI application is easy , bu can you trust it in production and leave you bussiness in hands of AI lets found out how we can make… Continue reading on M

Navigating the trade-offs between managed services, open-source engines, and existing database extensions for production AI. Continue reading on Medium »

Only Guide You Need to Start Ollama Continue reading on Stackademic »

OpenCode CLI is similar harness to as GitHub Copilot or Claude Code, so if you have these configured already configure OpenCode to work… Continue reading on Med

How a custom 12-layer causal transformer detects silent cluster failures in 14ms without labeled training data. Continue reading on Medium »

OpenAI and Broadcom reveal a custom 3nm ASIC designed to halve inference costs and challenge the dominance of general-purpose GPUs. Continue reading on Medium »

There are a thousand tutorials telling you to grab Oracle Cloud’s free 4-core, 24GB ARM instance. Continue reading on Medium »

How a machine finds meaning: from words, through geometry, to time Continue reading on Medium »

If you’ve ever tried to onboard a legacy application to a modern CI/CD platform, you know the real challenge isn’t writing the pipeline —… Continue reading on M

Over the past few weeks, I’ve been exploring how organizations can adopt Large Language Models (LLMs) at scale without compromising on… Continue reading on Medi

28th June 2026,Netherlands — In today’s technology world, terms like Artificial Intelligence, Machine Learning, and Deep Learning are used… Continue reading on

A hands-on walkthrough of taking a Streamlit LLM demo from “it runs on my laptop” to a governed, multi-environment, CI/CD-driven product —… Continue reading on

How to stop your AI from being a glorified parrot and make it a functional agent with MCP. Continue reading on Medium »

Stop overpaying for closed-source APIs and brittle GPU instances. Optimize your infrastructure for high-performance GGUF inference on the… Continue reading on M

They all trace your LLM calls. The difference that matters later is whether the traces are yours (OpenTelemetry) or theirs (proprietary). Continue reading on Me

Your billing dashboard tells you what you spent. It cannot tell you why. Here is how to build attribution that actually answers the hard… Continue reading on Me

For the past few years, every blogger and AI company representative has been talking about how artificial intelligence is changing lives… Continue reading on Me

The source was a live Kubernetes node — 12 projects, 100+ containers, 8 H100 GPUs running model training and inference, a Qdrant vector… Continue reading on Med

A two-phase approach to building production inference infrastructure on Kubernetes — IaC, GitOps, and full observability Continue reading on Medium »