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Review
CommunityGLM-5.3

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

Original source

X (Twitter)

AuthorSaleh Abdulaziz (@Sal7one)

Source date2026-08-16

Tabbit curation2026-08-19

Read original

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)

Curated by Tabbit

This is a third-party source navigator. Model versions, test environments, and personal experience vary; consult the original source.

GLM-5.3

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