AI Software Development
Khairallah AL-Awady shares insights from an Anthropic engineer about the innovative approach to using Claude. The engineer emphasizes the importance of building systems that prompt themselves, showcasing effective workflows and common pitfalls in usage.
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This page discusses a streamlined workflow utilizing 4-6 agents that operate continuously, each generating hundreds of subagents daily. It emphasizes the simplicity of the process and the specific tools involved, challenging the notion that 'agentic' is overly complex.
This page discusses the architecture of a harnessed LLM agent, emphasizing a model design that inverts traditional relationships by making the model itself thin while pushing intelligence outward. It aims to clarify the composition of intelligence at runtime.
David Breslauer shares insights on transforming work habits through effective planning and engineering principles. He emphasizes the importance of strategic planning and leveraging recent experiences to enhance productivity.
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Manthan Gupta shares his approach to utilizing a setup of three skills that he applies to nearly every feature post-coding. This includes a review skill that activates three sub-agents from various models to identify performance issues, over-engineering, and security vulnerabilities.
This page discusses insights from a Cowork article emphasizing that the model is no longer the limit; rather, the input determines the output. It highlights Technique 9 and the concept of skills as markdown files that enable Claude to follow repeatable processes.
Discover a powerful GitHub repository featuring 50 MCP servers that equip your agent with essential superpowers. This resource supports web browsing, file management, app control, and workflow automation, and is compatible with Claude Code, Gemini, Codex, and Cursor.
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In this post, AI Engineer Rahul shares key insights on effective engineering practices in AI. He emphasizes the importance of harnessing engineering principles, context engineering, and managing caching strategies for optimal performance.
An Anthropic engineer discusses the challenges of managing complex AI systems, emphasizing the importance of breaking down tasks into manageable pieces. In a 45-minute presentation, he illustrates how the Claude Code team transforms an overloaded Claude into focused helpers for improved efficiency.
This page highlights ten open source GitHub repositories that provide powerful tools for automation, design, coding, and productivity, often replacing expensive software. It emphasizes how these projects showcase the rapid evolution of software capabilities, allowing creators and developers to access premium functionalities without the high costs.
Anthropic engineer James Brady discusses the challenges of AI agents lying in production. He explains the verification stack he built and the strategies the Claude Code team uses to mitigate these issues in a 29-minute presentation.
A Director at Google just open-sourced the exact engineering playbook their senior engineers follow. This resource, called Agent Skills by Addy Osmani, includes 23 production-grade skills designed to teach AI coding agents to function like senior engineers, featuring structured workflows instead of generic prompts.
The cc-logger project provides local observability for Claude Code by capturing sessions, sub-agents, and tool calls to Postgres via HTTP hooks. This tool is designed to enhance the monitoring and debugging capabilities of applications using Claude Code.
This page discusses how to effectively use prompts in cheaper AI models to create precise plans before utilizing more expensive models like Claude Code or Codex. It highlights the importance of minimizing token waste while maximizing output quality.
This page discusses the structure of a new prompt for Claude 5, emphasizing the importance of starting with the 'why' rather than the 'what'. It provides a framework for defining tasks and context files to enhance the effectiveness of the prompt.
Peter Steinberger just handed you the autonomous dev loop most teams are still paying engineers to do manually. This is one of the best workflows I've seen in a long time; he explains exactly how to run a self-sustaining repo loop with Codex and agents.
Nav Toor curates a list of 10 open-source GitHub repositories for automating real work in 2026, covering autonomous coding agents, multi-agent orchestration, workflow automation, and AI-powered tools.
A dev got so frustrated watching his AI agent write 500 lines for a 5-line problem that he built a fix. He called it Ponytail, named after the guy every team has - long ponytail, oval glasses, been there longer than the version control.
MANUALLY DRAGGING BOXES FOR ARCHITECTURE DIAGRAMS IS FINALLY DEAD. There is a new open-source agent skill that turns raw codebases into cleanly routed diagrams without you placing a single coordinate, running directly inside Claude.
Suraj Sharma outlines a structured 6-month plan to become an Agentic AI Engineer. The plan includes foundational skills in Python and Async programming, followed by learning about LLM fundamentals for agents.
Google has released a comprehensive 51-page blueprint for transforming vibe coding into production-grade software engineering. This guide outlines essential concepts such as agentic engineering, context engineering, and the evolving role of developers in leveraging AI coding agents effectively.
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This page discusses the essential requirements for AI to function effectively as an employee, emphasizing the need for AI systems to be long-running and self-evolving. It highlights the importance of context-specific learning and adapting to workflows, rather than relying solely on benchmarks or pre-trained models.
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Jamon shares his comprehensive agentic setup to help others avoid missing critical components that could hinder their progress. He provides a structured approach with an AGENTS.md file to guide users to the right skills, documentation, and tools.
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