X (Twitter) @Sal7one: Long-running Agent Sessions + Having GLM 5.3 Review Code Hourly

Core content summary

The author shares his experience running long-running Agent tasks with Chinese models (including GLM 5.3), and introduces a practical workflow: have GLM 5.3 perform a code review every few hours.

Evaluation highlights (full original text)

"The fact that I'm getting work done, I run agents for hours, I get great debugging, architecture, UI, security all from… This is a necessary excerpt; read the original source for full context.

Interpretation

• Long-horizon stability: The author runs Agent tasks for several hours with Chinese models (DeepSeek + GLM 5.3), which perform well on debugging, architecture, UI, and security, while he "barely hit the limits"—supporting GLM-5.3's positioning for long-horizon tasks (officially, some tasks are equivalent to several days of an engineer's work).

• Practical workflow: "Have GLM 5.3 do a review every few hours, just in case"—together with @Ubendev (GLM 5.3 found 10 serious bugs in Claude's code), this forms an "AI cross-review" pattern.

• Note: This is an individual's workflow share, not a controlled comparison; however, "long-horizon task stability + periodic code review" is a typical use of GLM-5.3 in a real development loop.

Key data

• Platform: X (Twitter)

• Time: 2026-08-16

• Type: Real-world workflow share (long-horizon Agent + periodic review)