Parallel agents hit a human limit faster than a system limit
Running multiple coding agents in parallel feels like a speed win until the bottleneck becomes the person trying to supervise all of them.
Shaping with AI
Categories
17 pages
Technical notes
Data engineering, system design, architecture
How to set up a Claude Code agent team workflow: from parallel tasks to peer review
A practical walkthrough of setting up Claude Code agent teams with clear roles, task ownership, communication rules, review steps, and lightweight output contracts.
Shaping with AI
Orchestrating parallel subagents for data collection, exploration, and reporting
A hands-on case study of using Codex subagents to coordinate data collection, preparation, and Slidev report generation in parallel.
Shaping with AI
Creating agent-backed skills in Codex: a uv-first Python repo health check
I wanted Python repository health checks without flooding the main Codex thread with raw `uv`, `ruff`, `pytest`, and `ty` output. So I built a subagent-backed skill that inspects the repo, runs the usual commands, and returns a compact report with clear pass, warn, and fail signals.
Shaping with AI
In agent systems, context matters more than the prompt
A practical guide to what the planner actually sees, why context is more than the prompt, and why better context selection matters more than simply adding more tokens.
Shaping with AI