developer tools
QUERY = 'contents'; CATEGORY = 'developer-tools' // 23 rows
An applied measurement
case, every week
Analytics and measurement, developer tools, server-side tracking, AI & LLM integrations: weekly real case analyses.
Local Semantic Code Search: An MCP Server for AI Agents
A local semantic code search MCP server that solves AI coding agents' search problems using Tree-sitter AST chunking and hybrid search. Development process, architectural decisions, and real-world results.
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.
When Is Data Studio Pro Worth It? A Scenario-Based Decision Matrix From Solo to Agency, Ecommerce to SaaS
Data Studio Pro offers per-user monthly licensing, a Gemini AI surface, and enterprise management. This article walks through five scenarios (solo freelancer, small agency, scaled agency, in-house ecommerce BI, SaaS embedded analytics) with ROI math, self-host alternatives (Metabase, Superset), and the absolute floor/ceiling trigger metrics that determine each transition.
Data Studio Community Connector: Niche Source Integration with Apps Script
Data Studio Community Connector architecture, the four required Apps Script functions, Head Deployment test flow, versioned production deployment, and the real cost of writing your own connector instead of paying $90/month for Supermetrics.
Compaction-Friendly Search Output: A Practical Playbook
There is a way to compress search output before the agent context window fills. file:line + 2 lines context format, file-cache, dedup, code examples for tool result wrappers, and measurement results.
Token Budget Arithmetic for Agent Search
An agent context window is a budget; search is a sub-budget. Where the ~15% search budget rule comes from, how it scales for different context window sizes, and how to catch overflow signals, with numerical examples.
Code Search for AI Agents: ripgrep, ast-grep, or Semantic?
ripgrep is fast, ast-grep is structural, semantic search is smart. But for an agent the right question is different: which backend in which order, under what token budget? Decision tree, academic evidence, and practical policy snippets.
Pivot Tables Guide: From Excel to Polars, Automated with AI
Pivot tables in Excel, Google Sheets, Pandas/Polars and AI. Polars 5-10x speed, LLM hallucination pitfalls, privacy-friendly local LLM examples in a practical guide.
grep, ripgrep, and AI-Powered Text Search
A comprehensive guide from grep fundamentals to ripgrep, how AI agents use text search tools, and next-generation alternatives like semantic search.
AI Pair Programming: Coffee Debt, Gamifying Error Tracking
AI coding assistants make mistakes. Edit commands fail to match, bash scripts crash, users have to step in and correct. The point isn't getting frustrated at errors, it's logging them and extracting patterns. The Coffee Debt system does exactly that.
Living Architecture Documentation for AI Coding Agents: Research, Approaches, and Tools
Codified Context, AGENTS.md ecosystem, C4 Model, Repomix, ADRs, Spec-Driven Development, Google Code Wiki. A comparative analysis of 11 different approaches to giving AI agents architectural context, backed by research.
Hybrid Search: Smart Search Architecture with FTS5 + Vector + RRF
Keyword search alone isn't enough. Neither is vector search. What happens when you combine them with Reciprocal Rank Fusion? Hybrid search architecture through the dnomia-knowledge implementation.
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.
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.