Tag: Coding

September 1, 2026

The MLOps Adventure Continues: An AGENTS.md Ready Stack for AI/ML

Preparing an MLOps repository for AI coding agents requires eliminating friction points that cause AI hallucinations, such as fragmented toolchains and conflicting CI/local scripts. To create an "agent-ready" environment, teams should adopt a "single-gate pattern" that unifies execution commands across all environments, while ensuring that standard AGENTS.md instructions are strictly enforced by automated, machine-readable rules. Additionally, optimizing test performance for isolated MLflow environments—such as using a SQLite template database pattern—and managing dependency vulnerabilities through explicit, tested overrides are crucial. Ultimately, building a deterministic, rigorously checked repository allows AI assistants to bypass tooling drift and efficiently produce correct, production-ready code.

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August 4, 2026

Agent Levers: A Plan-Do-Check-Act Loop That Makes Coding Agents Finish What They Start

Many coding agents fail because they improvise internal planning loops, leading to unchecked code or runaway sessions. This article details how externalizing a structured Plan-Do-Check-Act (PDCA) engineering loop into a disk-based workflow acts as a leverage multiplier. By forcing agents through an explicit, step-by-step verification process, developers can reliably guide agents to finish what they start with minimal human intervention.

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July 21, 2026

Agent Docs: Answer Locally Before the Web — A Shared Reference for Every Coding Agent

Letting coding agents search the web for documentation wastes tokens, increases latency, and risks importing outdated or incorrect API patterns. To resolve this, this article presents `agent-docs`, a system of local references stored directly within the repository. By instructing agents to search local Markdown documentation maps before attempting web queries, developers can ensure that agents always build on correct, version-aligned instructions.

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June 23, 2026

Supagents: One Source to Rule Your Coding Subagents

Managing subagent personas across multiple AI coding platforms (like Claude Code, Gemini CLI, and Copilot) leads to fragmented configuration files and instruction drift. This article introduces `supagents`, a lightweight, idempotent Python CLI tool that lets developers maintain subagent definitions in a single markdown file with multi-target frontmatter. The tool automatically compiles and distributes these instructions to the correct paths, ensuring a consistent persona across all development environments.

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April 21, 2026

The 5xP Framework: Steering AI Coding Agents from Chaos to Success

The 5xP Framework is a practical strategy that uses five targeted Markdown files (Product, Platform, Process, Profile, and Principle) to seamlessly align AI coding assistants with your project's architecture and business goals. By defining strict context boundaries, this framework drastically reduces prompt bloat and prevents AI hallucinations, moving developers away from unstructured "vibe coding" and closer to reliable, spec-driven development.

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May 30, 2024

MLOps Coding Course: Bridging the Gap Between Data Scientists and Machine Learning Engineers

The MLOps Coding Course equips data scientists with essential software development skills to meet the demands of modern AI/ML projects. This open-source course covers building, deploying, and managing AI/ML systems, focusing on code structuring, validation, automation, dependency management, and Docker environments. Support includes the MLOps Coding Assistant and mentoring sessions. The companion MLOps Python Package demonstrates best practices. Ideal for both new and experienced ML engineers, this community-driven course encourages open-source collaboration. Start mastering MLOps today.

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October 21, 2025

Slides-To-Translate: When IT Says No, Build a $0.04 Solution on Your Lunch Break

When IT blocked every translation tool, Médéric Hurier decided not to wait. In just one lunch break, he built Slides-To-Translate — a fully automated Google Slides translator using Gemini 2.5 Flash, Colab, and Vertex AI — for only $0.04. His quick hack turned a bureaucratic bottleneck into a lightning-fast, secure, and reusable solution that proves anyone with a bit of code and curiosity can outpace corporate constraints.

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March 3, 2026

MLOps Coding Skills: Bridging the Gap Between Specs and Agents

This article explores how to use "Agent Skills"—simple Markdown-based context modules—to ensure AI agents strictly adhere to your team's MLOps practices and tooling preferences. By providing explicit organizational rules upfront, developers can eliminate generic boilerplate and align AI-generated code with production-grade standards.

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