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Why can a productive session become harder to continue?
Vibe coding does not remove the developer’s work so much as redistribute it. In an empirical study of extended sessions, Advait Sarkar and Ian Drosos describe a repeating cycle: prompt the AI, scan or test what it produces, and edit manually when needed. Programming expertise shifts toward managing context, evaluating output quickly and deciding when to switch from AI-driven work to hands-on coding. The study examined more than eight hours of curated video; that figure describes the material analyzed, not a fatigue threshold. Microsoft Research’s study explains the workflow.
You have to keep the project’s context straight
The assistant needs enough relevant information to make a useful change, while you need to keep the goal, constraints, prior decisions and code’s behavior in view. A 2026 qualitative study by Dov Te’eni and Adi Katz describes a gap between a developer’s persistent project knowledge and an agent’s session-bound context. Too little context can lead to misunderstandings; too much can consume attention or obscure what matters. Their analysis covered 163 interaction episodes in a single developer-agent collaboration on an academic paper-generation system over several months. It offers a way to understand coordination problems, not a rate that applies to all developers. The study on the human-AI context gap discusses these dynamics.
Review still takes human attention
Generated code may arrive faster than you can confidently establish that it is correct. In an IBM Think article published September 11, 2026, interviewees described fatigue from steering an agent, interpreting its output and checking the result. They also reported pressure to keep pace, interruptions from permission prompts and tool switching, and confusion after poor output in some long interactions. These are reported experiences from interviews, not a population estimate or a claim that every assistant behaves this way. IBM’s account of vibe-coding fatigue describes those experiences.
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A change can appear to work and still be wrong
A project that runs is not necessarily a project that meets the requirement. Columbia University’s DAPLab identifies failures in business logic and error handling that can remain silent: the code executes, but the behavior is wrong. The context-gap study also describes interacting problems in which missing context contributes to communication failures and functional errors, which can erode trust and require more effort to recover. Together, these findings make repeated prompt-and-patch cycles risky when nobody pauses to check what changed and whether it behaves as intended. Columbia DAPLab’s discussion of coding-agent failures explains why visibility and policy matter.
Is two hours an actual tipping point?
No general cutoff is established by the sources cited here. They describe mechanisms that may grow more demanding over a long interaction and interviewees’ accounts of fatigue, but they do not quantify a common onset time or show that vibe coding generally fails after two hours. “After hour two” may describe when a particular person notices accumulated steering, context and review work; it is not a validated threshold. Terms such as “vibing fatigue” and “context drift” are descriptive language, not standardized measures or clinical diagnoses.
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Other qualitative work helps describe the kinds of experience involved, without settling the timing question. Veronica Pimenova and co-authors analyzed more than 190,000 words of interviews and online discussion for themes around co-creation, communication, flow and trust. That corpus size is not a measure of how many people experience fatigue or when it begins. Their qualitative study examines those broader experiences.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to make a long session easier to manage
These practices address the coordination and review demands described in the studies. They are workflow suggestions, not experimentally proven treatments for fatigue.
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Define a small change before prompting
Turn a broad request into one bounded task with explicit expected behavior and constraints. IBM’s interviewees described using smaller, structured tasks and rigorous specifications to reduce cognitive load, even when preparing the specification took extra time.
Keep a compact project brief
Maintain a short, current note with the goal, relevant files, decisions and their rationale, constraints, attempted fixes and the next verification step. This is a practical response to the documented gap between persistent project knowledge and session-bound agent context; the study did not test this exact checklist.
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Check each change before stacking another
Ask for one bounded change, then inspect the diff and test the behavior before adding another request. This preserves the prompt–evaluate–test–edit cycle described in the vibe-coding workflow study and makes it easier to catch functional errors before they spread.
Reduce switching and isolate experiments
If moving among terminals, codebases or documents is adding friction, reduce concurrent tasks or agents. Some IBM interviewees limited concurrent work for this reason. For risky experiments, use a sandbox or dedicated directory before integrating changes; isolation can lower the stakes of a quality problem, but it does not remove the need for review.
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Pause when patches keep widening the problem
Restate the expected behavior, inspect the accumulated changes and isolate a minimal reproduction before requesting another modification. This cautious reset follows from documented context and error-expansion mechanisms; it has not been established as a tested protocol. Whether to take a break or stop for the day is an individual workflow choice: the cited sources do not test a prescribed break interval or timer schedule.
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