OpenClaw users report planning and review bottlenecks with AI agents
The planning and review bottleneck
A recent discussion on r/openclaw highlights a persistent friction point when working with AI coding agents: while code generation works well, planning and review processes remain cumbersome and manual.
The user describes spending 30 minutes "nudging agents through an architecture review" and setting up file-based systems so agents could read each other's work, requiring constant babysitting and manual input. This results in a "MD file graveyard" of plans, architecture docs, and code reviews that are read and edited alone, then pasted into Slack for team feedback as "a wall of text with no way to comment on anything specific."
Collaboration breakdowns
When involving multiple agents in the process, reasoning gets lost. The user reports having an agent outline a refactor with detailed tradeoffs, only to have a review agent rewrite it into a clean plan that removed every tradeoff. The original reasoning disappeared entirely.
The current workflow is described as "MS-DOS: a text editor, and a chat window" - a stark contrast to the automated efficiency of code generation.
Emerging solutions
Some users are experimenting with what they call "Agent-Native document editors" - specifically mentioning comment.io and Proof by Every. These tools allow inline commenting and enable agents to co-edit documents without destroying each other's changes. While early, they represent attempts to improve on the "copy-paste-into-chat loop" that currently dominates planning and review workflows.
The core question remains: how to better plan and review with both agents and humans in a collaborative, traceable way.
📖 Read the full source: r/openclaw
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