Claudecode
8 articles about claudecode.
The Simplest Way to Log Parallel Sub-Agent Conversations
When running 5+ AI agents in parallel with an orchestrator, having each sub-agent write its conversation to a file is the most reliable logging approach.
Using Multiple LLMs for Multi-Agent Workflows - Orchestration Patterns That Work
How to run multi-agent workflows with different LLMs for different subtasks. Claude as orchestrator, specialized models for specific jobs, and env var
Memory of a Goldfish - Solving Mid-Conversation Context Drift in AI Agents
How to fix mid-conversation context drift in AI agents using anchoring techniques, CLAUDE.md files, periodic re-grounding, and structured task tracking.
Tips for Secondary Models - When to Use Haiku vs Opus in AI Agents
Choosing the right model tier for different AI agent tasks saves money without sacrificing quality. Learn when to use cheap models like Haiku and when to
Parsing Claude Code's JSONL Format for macOS Dev Tools
Building developer tools that read Claude Code's local conversation logs means figuring out the JSONL format - conversation turns, tool calls, and file
Accessing Claude Code Previous Sessions via JSONL Transcripts
Where Claude Code stores previous session transcripts as JSONL files, how to find them in ~/.claude/projects/, and practical tips for parsing and reusing
Why We Build AI Tools with SwiftUI Instead of Electron
Native macOS apps feel right - proper keyboard shortcuts, menu bar integration, system notifications. Electron apps are cross-platform but feel foreign on
Why Scoped 50K Context Agents Outperform One Million Token Context
One million token context windows sound impressive, but scoped agents with 50K context each consistently outperform a single giant context for real
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