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Open Source

What Works and What Doesn't in CLAUDE.md

Writing "Write clean code" in CLAUDE.md changes nothing. During the process of building 10 personal apps in three months, I rewrote CLAUDE.md many times. Since it became clear what worked and what didn't, I will outline that distinction. What Doesn't Work Giving instructions with

DEV Community
Database

Stop Building AI Agents. Start Building AI Systems.

There's a phrase I keep seeing everywhere in AI development: "We need an AI agent." Need to analyze documents? Build an agent. Need to automate a workflow? Build an agent. Need to interact with APIs? Build an agent. Need to write code? Build an agent. At some point, I started asking a diff

DEV Community
Open Source

Your offline GitHub

Hi all! I’ve been coding professionally for the last 15 years - and more and more with AI next to me. Naturally pushed by the market to produce more and more output, I now find myself hopping daily between 5 to 7 simultaneous AI sessions. I realized that the bottleneck is becoming the code review

DEV Community
DevOps

What Actually Happens When You Run `docker run`

What Actually Happens When You Run docker run You type docker run -d --memory 512m myapp:latest and hit Enter. A second later, a container is running. It feels like one action. It is not. Behind that single command, four separate programs hand work down a chain, an image gets pulled apart into la

DEV Community
AI & ML

GPT-6 is released [N]

Benchmark scores (GPT-6 uses a harness for ARC-AGI-3, and is at about 60% without one): https://preview.redd.it/v7nik4nbtfnh1.png?width=1378&format=png&auto=webp&s=a6ec04b5b87e7f2dce748b275d878ab0243f751d https://openai.com/index/gpt-6-astra/ submitted by /u/we_are_mammals [link]

Reddit r/MachineLearning
Backend

Graph Engineering: The End of the Monolithic AI Agent

For the past year, the default approach to building AI automation has been simple but flawed: write a massive prompt, hand it to a single "god-mode" AI agent, drop it into an autonomous loop, and cross your fingers. While this loop engineering works for simple summarizations, it shatters in product

Dev.to (EN Zone)
AI & ML

D2C Technology Stack: How to Design for Omnichannel Growth

A D2C technology stack is often discussed as a shopping list: commerce platform, OMS, CRM, analytics, payments, search, loyalty, customer support and increasingly AI. That framing is useful when a brand is starting. It becomes dangerous when the brand begins to scale. The reason is simple: custome

Dev.to (EN Zone)