#test-driven development AI
146 related articles
·2 min
Andrew Ng on AI Agent Development: Evaluation and Error Analysis Are the Core Competitive Advantage
Andrew Ng argues that the core gap in AI Agent development isn't model selection — it's systematic evals and error analysis. A breakdown of his methodology.
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·2 min
Xiaomi MiMo Code Goes Open Source: How Cross-Session Memory Is Changing AI Programming Collaboration
Xiaomi's MiMo Code is an open-source terminal programming Agent with cross-session memory and multi-Agent collaboration. Explore its memory system, self-evolution mechanism, and how it differs from Claude Code.
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·3 min
Harness AI Engineering Programming: A Detailed Methodology for Enterprise-Level Project Development
Deep dive into Harness AI Engineering Programming methodology, covering SDD, Skill development patterns, and core practices for enterprise-level AI-assisted development.
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·3 min
Claude Code Loop Patterns in Practice: Community Insights and Best Practices
Explore Boris Cherny's Claude Code loop patterns with community insights on /loop commands, test-driven loops, multi-agent collaboration, and best practices to avoid loop divergence.
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·3 min
Reading Code Is More Important Than Writing It in the AI Era: 6 Practical Tips to Improve Your Code Reading Skills
In the age of AI-generated code, reading code is a critical skill. Learn 6 practical techniques—from entry point reading to tracing data flows—using a login endpoint example.
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·3 min
8 AI Coding Tools Compared: A 5-Tier Buying Guide
In-depth comparison of 8 mainstream AI coding tools including GitHub Copilot, Cursor, Windsurf, and Claude Code, ranked into 5 tiers with tips to avoid bad plugins.
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·3 min
OpenAI Codex Deep Dive: Core Capabilities and Engineering Best Practices Guide
Deep dive into OpenAI Codex's core capabilities including multi-task parallelism, Agent Loop mechanism, and Specification-Driven Development (SDD), with learning resources and advanced paths for mastering AI programming workflows.
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Deep Dive into the Three AI Programmin…
·3 min
Deep Dive into the Three AI Programming Frameworks: The Right Way to Do Specification-Driven Development
Deep dive into the three frameworks of Specification-Driven Development (SDD) for AI programming: Blueprint, Execution Flow, and Change Records — solving the problem of AI code going off the rails.
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·3 min
Claude Code + Codex: The Best Practice of One-Writes-One-Reviews AI Programming
A detailed guide on using Claude Code for writing and Codex for reviewing in AI programming. Includes a five-step closed-loop workflow and cross-validation techniques.
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Tutorials·2 min
Claude Code Beginner's Guide: A Complete Workflow from Setup to Project Delivery
A detailed guide to Claude Code's core curriculum: environment setup, multi-file project management, testing standards, AI architecture review & security auditing.
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Tutorials·3 min
Matt Pocock's AI Coding Workflow: A Complete Methodology from Ideation to Delivery
Deep dive into Matt Pocock's AI-assisted coding workflow: Grill Me consensus building, PRD generation, Tracer Bullet vertical slicing, AFK execution, and Deep Modules architecture design.
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Tutorials·2 min
OpenSpec in Practice: Write Specs Before AI Codes, Boost Efficiency by 70%
OpenSpec is a lightweight CLI tool that generates spec documents before AI writes code using a Propose→Continue→Apply→Archive workflow. DeltaSpec reduces output by 70%, supports 30+ AI coding tools.
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Expert Opinions·3 min
Is Learning to Code Still Worth It in the AI Era? An Honest Answer from an Atlassian Engineer
Can AI write code instantly—so is coding still worth learning? An Atlassian engineer breaks down the truth behind tech leaders' claims and AI coding limitations.
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Deep Dives·3 min
Deep Dive into How Claude Code Works: A New Programming Paradigm Driven by the Agent Loop
Deep dive into how Claude Code works, including the Agentic Loop, automatic context compaction, tool calling, and permission modes that power autonomous AI programming.
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Tutorials·2 min
The Five-Step Rhythm Method for AI Programming: A Practical Strategy Where Slow Is Fast
A methodology for rhythm control in AI programming: use a five-step strategy (identify, plan, minimal change, test, risk assessment) to prevent AI from going off-track and causing rework.
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Tutorials·3 min
SDD (Specification-Driven Development) in Practice: AI Programming Methodology from Cursor to Claude Code
Deep dive into SDD (Specification-Driven Development) methodology covering Cursor and Claude Code in practice—from intelligent data querying to enterprise compliance platforms across four progressive projects.
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Tutorials·2 min
Harness Engineering Explained: The Role Shift from Coder to AI Supervisor
Deep dive into Harness Engineering: how engineers shift from coders to AI supervisors. Learn to solve agent drift, feedback optimization, and build future-proof engineering skills.
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Tutorials·3 min
AI Programming in Practice: Great Skills Don't Need to Be Handwritten — Let Them Emerge from Real-World Experience
Learn how to let AI automatically distill reusable Skill prompts through a K8S cluster setup case. From task execution to problem discovery and iterative fixes, master the right methodology for knowledge management in the AI era.
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Tutorials·3 min
AI Programming in Practice: Great Skills Don't Need to Be Handwritten — Let Them Emerge from Real-World Experience
Learn how to let AI automatically distill reusable Skill prompts through a K8S cluster setup case. From task execution to problem discovery and iterative fixes, master the right methodology for knowledge management in the AI era.
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Tutorials·1 min
Full-Stack with Zero Backend Experience: Building a Message Wall with Trae + Supabase + Vercel
Learn how to build a full-stack message wall with Trae AI, Supabase, and Vercel — no backend experience needed. Covers setup, database, UI, and deployment.
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