A hands-on guide to Jev and System One models: fast, calibrated decision models. Covers how they work, how you could build one, what the early benchmarks show, and where they fit next to reasoning LLMs. Jev is an AI model from TypeSafe AI that makes decisions instead of writing text. You give it some input […]
What Is Jev? System One Models Explained Read More »
AI guardrails are the controls that decide what an enterprise AI system can accept, access, do, and say. This guide explains how they work across LLM apps, RAG, and AI agents, what the research says they can and can’t stop, and how to assemble them into a defense-in-depth architecture. AI guardrails as layered defense: probabilistic
AI Guardrails in Enterprise AI: Architecture, Controls, and Limits (2026 Guide) Read More »
TL;DR: An LLM gateway governs how applications use models: routing, cost, failover and audit. An MCP gateway governs how AI agents use tools: identity, per-tool permissions, schema pinning and human approval. They solve different problems, so enterprises need both, deployed as sequential control layers in three phases: visibility, protection and governance. Modern enterprise AI operates
LLM Gateway vs MCP Gateway: Why Enterprise AI Needs Both Read More »
This IKEA AI case study begins with a chatbot named Billie and ends with a €1.3 billion business — and the distance between those two numbers is the most valuable lesson in enterprise AI today. Most companies deploy AI to do the same work for less. IKEA did that too: its Billie chatbot quietly saved
IKEA AI Case Study: How Billie Became a €1.3 Billion Business Read More »
A frontier model went from “the most capable ever shipped” to completely offline in three days. For the enterprises that had already built on it, the disruption had nothing to do with model performance and everything to do with AI vendor lock-in — the underestimated risk of running a business on a single model you
AI Vendor Lock-In: Lessons From the Fable 5 Shutdown Read More »
When evaluating an enterprise technology stack, the build vs buy ai decision used to be a simple coin toss.Three years ago, most enterprises were building narrow prompt-response applications like basic chatbots, code copilots, or document summarizers. Your architectural choice usually came down to a straightforward question: do we call a frontier model API, or do
Build vs Buy AI in 2026: The Definitive Enterprise Framework Read More »
GPU compute is the most expensive line item in modern AI development. Whether you’re training a foundation model or fine-tuning a domain-specific LLM, every idle GPU second translates directly into wasted budget. Meta recently published a detailed breakdown of how their engineering teams tackled 30–40% overhead in GPU training time — and the fixes are
GPU optimization for AI training: 4 critical fixes to reclaim 40% Read More »
Every setting, workflow, and practitioner insight your engineering organization needs. Claude Code has crossed the threshold from “impressive demo” to legitimate infrastructure for engineering teams. But there’s a yawning gap between getting one developer to try it and deploying it across a 50-person organization in a way that actually sticks. Configuration matters. Habits matter. Governance
How to set up a 10X more powerful development workflow with Claude Code Read More »
OPINION | ENTERPRISE AI | THOUGHT LEADERSHIP By Sukrit Goel | Founder & CEO | April 2026 The next time ChatGPT tells you that your mediocre pitch deck is “really compelling” or that your half-baked product idea is “genuinely innovative,” know this: it is not malfunctioning. It is doing exactly what it was designed to
Why AI Sycophancy Is a feature, not a bug — and why is it alarming Read More »
If you’ve used an AI coding assistant on a large codebase, you’ve probably sat there watching a spinner while the agent “searches for relevant files.” That wait isn’t just annoying — it’s a fundamental technical problem. And solving it properly requires going back to 1973 and rethinking how search actually works. This post explains how
Faster RegEx Search for AI Agents in Large Codebases Read More »