A data scientist with around two years of experience has sparked a debate over onboarding practices at AI-first startups after claiming they were fired just 20 days into a new job, during the probation period. The employee alleged that the company offered little onboarding support, leaving them to navigate complex production systems and AI-generated code largely on their own.
“As a new joinee, I wasn't given any proper knowledge transfer sessions, documentation, or a structured onboarding process,” the data scientist wrote, explaining that considerable time was spent reverse-engineering the existing implementation, understanding business logic and determining how the systems worked before beginning assigned tasks.
The employee said they made a genuine effort to meet expectations, understand the codebase, replicate existing functionality and ensure that new implementations matched production outputs. They also used AI coding tools to keep pace with the team's workflow.
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However, the account highlighted a lack of clear guidance, communication and mentorship, leaving the employee to resolve many challenges independently.
Following the termination, the professional admitted that the experience had affected their confidence, raising questions about whether they lacked the necessary skills, should have adapted more quickly or had joined an unsuitable working environment.
The employee acknowledged that startups often operate under demanding conditions and that perfect organisation was not expected. However, they argued that a reasonable level of onboarding, communication and clarity should be provided, particularly when employees are expected to work with unfamiliar and undocumented codebases.
The experience has also prompted broader questions about the expectations placed on engineers in companies that increasingly depend on AI coding agents to accelerate development. "How do you distinguish between a genuine skill gap on your part and a dysfunctional work environment?
How do you cope with self-doubt and rebuild your morale after being terminated during probation?" he asked on Reddit.
The data scientist is now seeking advice from professionals working in startups, particularly in Data Science, machine learning engineering and AI engineering, on distinguishing genuine skill gaps from workplace management issues.
Among the concerns raised were how to evaluate onboarding processes, management styles, mentorship and delivery expectations before accepting a role.
“What questions should I ask during interviews to understand the team's engineering practices, onboarding process, management style, and expectations?” the professional wrote, seeking advice from others who have experienced similar situations.
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