AuricIDE / Blog
Blog
Notes from building AuricIDE: agent orchestration, machine-checkable goals, and systems for supervising coding agents.
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Multi Agent Coordination Is an Attention Problem
Multi agent coordination is not about running more agents at once. Learn how AuricIDE's Fleet attention rule and sequential chains solve it.
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AI Coding Workflow That Hands Off Context Correctly
AI coding workflow fails at handoffs, not generation. Learn how AuricIDE chains pass terminal context and design reliable multi-step flows.
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Code Automation Tools for Local-First Agent Workflows
Explore code automation tools that run locally, from templating to refactor bots and agent fleets, with practical tips for local-first setups.
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AI Tools for Software Engineers: A 2026 Guide
Discover the best AI tools for software engineers in 2026. Boost productivity, automate tasks, and write better code with our expert picks.
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Best Open Source IDE for Agent Fleets
The best open source IDE for coding agents is not about reading source code. It is about a JSON file you write yourself to register any CLI agent
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Agent Context Management: What Actually Gets Passed On
Agent context management is not a pipe. See what a curated terminal tail keeps, what MCP shared state adds, and the real cost of cutting at 2,000 characters.
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AI Code Agent Chains: Why Exit Code 0 Is Not Enough
Learn how AuricIDE tracks AI code agent success beyond exit codes, using chains with cleaned terminal tails to prevent cascading failures.
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Local AI Agents: What Changes Under the Hood
Discover what local AI agents actually change under the hood, from PTY processes to SQLite-backed shared state and concurrency tradeoffs you can feel.
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AI Development Agents: Why the Config Layer Matters Most
AI development agents depend less on the model and more on the config and permission layer around it. See how dynamic provider configs actually work.
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Open Source AI Tools for Developers in 2026
Curated open source AI tools for developers in 2026, from agent CLIs and local models to MCP servers, with trade-offs and clear use cases.
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LLM Agent Architectures: Three Shapes That Matter
A working engineer's guide to LLM agent architectures, the three shapes that define them, and the trade-offs each one carries
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How to Create an AI Agent That Actually Ships
Learn how to create an AI agent that goes from a single CLI tool to a coordinated fleet, with practical steps for architecture, skills, and state.