Notes on software engineering, shipping products, and building fast, maintainable web experiences.
Showing 6 results for developer-experience.
ClearAI raises the baseline for speed—but also for correctness, security, and ownership. Here’s a practical playbook for staying valuable and shipping high-impact work with AI in the loop.
Tokens cost money and time. This guide shows practical ways to shrink prompts, tighten outputs, and use TOON-style structure to cut back-and-forth.
Agent skills are reusable, scoped behaviors that make assistants consistent and safe. This guide covers what they are, how to design them, and how to ship them in teams.
RAG is a pattern that lets an LLM answer with your data by retrieving relevant context first, then generating a response grounded in that context.
Model Context Protocol (MCP) is a standard way to connect AI assistants in your IDE to tools like files, Git, databases, and internal services—safely and consistently.
Autocomplete is table stakes. The next wave is agentic IDE workflows: the AI can plan, edit multiple files, run commands, and iterate until it ships.