ai
QUERY = 'contents'; CATEGORY = 'ai' // 25 rows
Pre-injection vs MCP Tool Loop: Context Strategies for AI Coding Agents
GrapeRoot injects context before the model starts, CodeGraphContext uses MCP tool loops. Same repo, same model, same prompts. One comes out 31% cheaper. Where's the architectural difference? Benchmark data and comparison with my own system.
An AI agent loop cost someone $187 in 10 minutes. Here's what monitoring tools won't tell you.
AI agents in production have a systemic blind spot: we can trace everything but understand nothing. Current observability tools are flight recorders, not collision avoidance systems.
Which Files Do You Actually Read? Developer Interaction Tracking
Do you know which files you looked at most during a week of work? Which searches returned zero results? Using Claude Code hooks to collect interaction data and trace analytics to reveal patterns, I tracked my own workflow. The data was surprising.
Context Engineering for AI Coding Agents: From Static Documents to a Living Ecosystem
CLAUDE.md and architecture.md are not enough. A four-layer context engineering ecosystem combining semantic code search, knowledge base, decision governance, and learning loops. Based on real project experience.
Claude Code Context Management: Three Different Approaches
Claude Code's context window fills up fast. claude-context-mode, claude-context, and dnomia-knowledge solve this problem in different ways. Architectural decisions, trade-offs, and real-world comparison.
Domain-Specific Prompt Optimization: The Knowledge Anchor Approach
How do LLMs retrieve knowledge, why do generic prompts fail, and how do knowledge anchors solve this? Structured prompting formats, domain-specific optimization steps, and the practical Prompt Forge approach.
Decision Gate v2: Multi-AI Spec Tribunal
Is a single AI's evaluation sufficient? An open-source Claude Code skill that runs the Decision Gate framework with multiple independent AIs in adversarial mode: /court. Add Gemini and Kimi as jurors, prevent rubber-stamping.
Why AI Agents Break Files: Practical Strategies and Tests
I benchmarked 5 file editing approaches used by AI coding agents across 20 scenarios. Sequential Edit, Atomic Write, Bottom-up Edit, Script Generation, and Unified Diff, which works when?
Why LLMs Fail at Turkish Characters: A Deterministic Fix with Claude Code
Large language models systematically drop Turkish diacritics (ç, ğ, ı, ö, ş, ü) during long-form content generation. The development process behind a zero-token-cost Claude Code plugin that solves this.
RAG Chunking: Strategies, Limitations, and Decision Map
A comprehensive guide to text chunking strategies in RAG systems. 12 different approaches, limitations, multilingual support, and a scenario-based decision table.