A former Meta L8 engineer shares his end-to-end agentic workflow, from terminal setup to prompt strategies. He outlines the tools (WezTerm, tmux, Neovim, Claude Code/OpenCode), voice input, and delegation techniques that let him manage AI agents like a dev team.

• A former Meta L8 produces 30+ high-quality PRs in a single day by managing AI agents instead of writing code himself
• His entire workflow runs in a terminal (WezTerm + tmux + Neovim) using Claude Code for Anthropic models and OpenCode for everything else, avoiding vendor lock-in features like auto-memory
• He pairs local, offline speech recognition with terminal prompts to iterate faster, treating each prompt like a spec refined against a "golden set" of expected outputs
• He's built custom CLI tools to automate context loading, versioning, and error handling so prompts plug into a repeatable pipeline

The article summarizes highlights from a podcast episode discussing recent advancements in AI and their impact on software engineering, particularly the emergence of coding agents. It covers topics like the inflection point in model capabilities, the changing role of software engineers, and the challenges faced by mid-career professionals.

• GPT 5.1 and Claude Opus 4.5 (released in November) marked a real inflection point where generated code became reliably functional rather than needing constant oversight
• The bottleneck in software development has shifted from writing code to testing it, since prototyping is now fast and cheap
• Running multiple coding agents simultaneously is mentally exhausting and risks burnout if overused
• Interruptions are now less costly to productivity since these tools let programmers pick back up quickly after breaks