#Databricks AI evaluation
26 related articles
·4 min
Transitioning from DevOps to MLOps: A Complete Learning Roadmap
How can DevOps engineers efficiently transition to MLOps? This guide covers MLOps core concepts, standard workflows, essential tools, and Azure practices with a progressive learning roadmap.
Read more →
·4 min
Full-Stack Machine Learning Project Repository Structure Guide: From Chaos to Convention
A detailed guide to organizing full-stack ML project repositories, covering directory structure design, data-code separation, and configuration externalization to help ML developers move from experimental code to production-grade engineering.
Read more →
·4 min
A Guide to Full-Stack Machine Learning Project Repository Structure: From Chaos to Convention
A detailed guide to organizing full-stack ML project repositories, covering directory structure design, data-code separation, and externalized configuration to help ML developers move from experimental code to production-grade engineering standards.
Read more →
WrenAI: An Open-Source GenBI Tool for …
·4 min
WrenAI: An Open-Source GenBI Tool for Querying Databases with Natural Language
WrenAI is an open-source GenBI tool by the Canner team that converts natural language into trusted SQL, charts, and dashboards via a semantic layer. Supports 20+ data sources including BigQuery and Snowflake. 16,000+ GitHub stars.
Read more →
GitHub Daily · July 19: The Dual Advan…
·3 min
GitHub Daily · July 19: The Dual Advance of Heterogeneous Inference and Agent Toolchains
GitHub Trending July 19: ktransformers tops the list with heterogeneous inference optimization, while jcode, cua, and AstrBot signal a maturing Agent ecosystem.
Read more →
·3 min
Flyte Deep Dive: A Practical Guide to Choosing Your ML Workflow Orchestration Tool
Deep dive into Flyte's core capabilities: cloud-native GPU scheduling, intelligent caching, checkpoint recovery, and conditional deployment — plus a full comparison with Argo and KubeFlow Pipelines.
Read more →
·3 min
MLOps from Scratch: A 100-Day Learning Challenge Roadmap and Practical Guide
A college student's MLOps 100-day challenge documents the full journey from Python engineering and Git to Docker, model deployment, and monitoring. A practical roadmap for data scientists transitioning to ML engineering.
Read more →
·2 min
Learning MLOps from Scratch: A Deep Dive into the 24-Month Roadmap
Can you learn MLOps from scratch? This guide breaks down core skill requirements and offers a practical 4-phase, 24-month roadmap covering Python, ML, DevOps, and MLflow.
Read more →
·3 min
Training a 100M-Parameter Model for Under $50: A Complete Record of Building SmoLLM from Scratch
An ML engineer trained SmoLLM, a 109M-parameter LLaMA-style model from scratch for under $50. Full breakdown of architecture, training pitfalls, instruction tuning, and real-world performance.
Read more →
·2 min
Databricks MLOps in Practice: What Actually Works with MLFlow, Agent Bricks, and Genie
An in-depth look at Databricks MLOps core features: MLFlow experiment tracking, Unity Catalog governance, Agent Bricks agent development, and Genie natural language queries—plus real deployment challenges and practical advice.
Read more →
·6 min
A Deep Dive into AI Agent Harnesses: The Core Engineering Behind Agent Frameworks
What is an AI Agent's harness? This article systematically dissects the core components of agent frameworks: context management, tool use, control loops, and caching strategies—revealing why the same model performs so differently across harnesses.
Read more →
Million Lines of Code: A Deep Dive int…
·2 min
Million Lines of Code: A Deep Dive into Enterprise-Grade AI Coding Assistant Benchmarks
Databricks benchmarks AI coding agents on multi-million line production codebases, exposing the limits of HumanEval and SWE-bench. A deep analysis of context management, cross-file reasoning, and validation in real enterprise code.
Read more →
·2 min
Databricks Tests Coding Agents in Production: The Truth About Cost, Performance, and Tool Selection
Databricks tested leading coding agents on a production codebase of millions of lines. Key findings: token price misleads cost estimates, open-source GLM 5.2 handles hard tasks, and harness design determines real-world performance.
Read more →
·2 min
The AI Model Versioning Crisis: What an Industry Rumor Reveals About Iteration Chaos
A viral AI rumor about a lost "version 5.6" model exposes three real industry pain points: version control chaos, compliance risk, and model asset management failures.
Read more →
·5 min
5 Things You Must Do Before Deploying AI Agents to Production (With a Banking POC Case Study)
Over 60% of AI Agent projects die between demo and production. This article breaks down Databricks lead Sandy's five-pillar methodology and a bank POC case study to help you avoid the most common deployment pitfalls.
Read more →
·6 min
Databricks Agent Framework in Practice: A Guide to ChatAgent Wrapping and Production Deployment
A deep dive into Databricks Agent Framework (Mosaic AI): unify LangGraph/OpenAI agents via ChatAgent, log & evaluate with MLflow, version with Unity Catalog, and deploy Model Serving Endpoints for production AI agents.
Read more →
·7 min
The Five Pillars of Production-Grade AI Agents: A Battle-Tested Guide from Demo to Deployment
Databricks tech lead Sandy shares a five-pillar framework for production-grade AI Agents—evaluation, observability, data foundation, orchestration, and governance—with a £85K retail banking failure case to bridge the demo-to-production gap.
Read more →
·6 min
Deploying Enterprise AI Agents to Production: The Five Pillars from Demo to Launch
A Databricks expert breaks down the complete methodology for taking AI Agents from demo to production, covering the five pillars of evaluation, observability, data foundation, multi-Agent orchestration, and AI governance, with a real eight-week banking chatbot POC case.
Read more →
·3 min
Zhipu GLM-5.2 Officially Launches | Full Breakdown of Anthropic's U.S. Export Control
Zhipu GLM-5.2 launches with tiered thinking and long-context support, while Anthropic faces rare U.S. export controls over AI security vulnerabilities. Full breakdown.
Read more →
·6 min
Claude Team Edition Launches as Encrypted Reasoning Controversy Sparks AI Transparency Debate
Anthropic launches Claude for team collaboration while encrypted reasoning controversy erupts. Plus Sakana AI's routing model and OpenAI's alignment research breakthroughs.
Read more →