---
url: "https://www.reddit.com/r/ClaudeAI/comments/1vhy33b/does_anyone_actually_have_a_fully_autonomous/"
title: "Does anyone actually have a fully autonomous coding agent that doesn't need constant follow-ups?"
source_kind: reddit
subreddit: ClaudeAI
author: Top-Affect2871
score: 22
captured: "2026-08-08T18:48:00+00:00"
comment_tree: false
topics: [ai-impact]
summary: A developer shares frustration that AI coding agents like Claude Code repeatedly miss bugs and edge cases across follow-up reviews, questioning if full autonomy is currently achievable.
status: ok
---

​
I've been trying to build a fully agentic software development workflow using Claude Code, and I've hit a frustrating problem.
The first implementation usually looks good, but every time I ask a follow-up like:
"Cross-check everything again. Did you miss anything from the plan?"
it suddenly finds new bugs, missed edge cases, forgotten files, or partially implemented requirements.
Example:
Pass 1:
- Implements Feature A
- Says task is complete
Follow-up:
- Finds 3 missing API updates
- Missed a permission check
- Forgot one database migration
Another follow-up:
- Finds a UI regression
- Finds an edge case in validation
- Notices a cache issue
Another follow-up:
- Finds even more small issues
It feels like every review uncovers something that should have been caught in the previous one.
I've already built a strict engineering workflow that forces:
- Understand the entire architecture first
- Review blast radius
- Implement
- Audit
- Fix
- Repeat until no more issues are found
- Run automated verification plus manual review
Even with all that, the next follow-up often reveals something new.
Has anyone solved this problem?
Is this simply a limitation of today's LLM agents, or have you found a workflow, prompt, MCP, or multi-agent setup that consistently reaches a point where additional follow-ups rarely discover new bugs?
I'd love to hear what has actually worked in production.