5 AI Coding Workflows tips (all free)
5 AI Coding Workflows resources, picked out of 5 liked tweets, from creators like @PrajwalTomar_, @bcherny, @cjzafir. 5 of them are free, freemium or open source.
A step-by-step workflow for developers and founders building software with the Cursor AI editor. It covers preparation steps like generating PRD and schema files, configuring project rules, managing context across chat tabs, and documenting reusable code patterns.
A detailed 8-point workflow guide by Boris Cherny on maximizing productivity with Claude Code. It covers practical tactics including running parallel sessions across terminal and web, maintaining shared CLAUDE.md files, using Plan mode, and configuring subagents.
This framework outlines a systematic method for developing applications with Cursor and complementary AI tools by establishing an explicit context boundary. It structures the process from initial brain dumps to requirements documents, file layouts, and phased frontend and backend generation. It helps prevent AI hallucinations and errors by providing models with exhaustive project specifications before writing code.
A practitioner framework for structuring the environment, context, and guardrails around AI coding agents. Grounded in a large-scale enterprise rollout across 20,000 developers, it focuses on context budgeting and four core control levers to prevent degraded performance and hallucinations. It treats the agent as a capable hire that needs onboarding via structured rules, targeted tools, on-demand skills, and detailed specifications.
A detailed configuration framework and workflow guide for Claude Code based on ten months of intensive daily use. It covers the setup and architecture for skills, lifecycle hooks, modular subagents, custom rules, and Model Context Protocol (MCP) servers. It emphasizes strict context-window management, LSP integration, and CLI developer ergonomics.