Reddit thread surfaces AI tool friction

The core frustration is not that AI is useless; it is that it often gets you 80-90% of the way there and then makes the final mile more tedious than doing the work yourself.

• –Users say the biggest tax is iteration overhead: fixing one hallucination or edge case can take ten prompts
• –Several replies point to inconsistency, where the same prompt produces great output once and junk the next time
• –The thread suggests the real bottleneck is workflow design, not raw generation quality: data inputs, governance, and tool integration matter more than prompt tweaks
• –A few comments hint that AI works best when split by job, using different tools for code, docs, design, and ops instead of expecting one chat box to do everything
• –The takeaway for builders is clear: reliability, observability, and constraint handling are becoming more important than model cleverness