AI Safety
ai-safety
Behavioral Interviews
OpenAI: Mission Alignment and Safety
OpenAI's behavioral loop sits at the intersection of three signals that no other major engineering employer asks for in the same combination: substantive engagement with the AGI mission, serious consideration of safety as a daily constraint, and the intensity of frontier-lab work paired with collaborative care. Candidates who walk in with strong engineering credentials but no view on the mission, or who recite mission language without engaging with the safety-versus-capabilities tension, do not score well. This lesson defines what mission alignment actually means in interview context, walks through how the loop probes safety thinking specifically, maps the cultural signals to the questions interviewers ask, and shows two model answers tailored to the mission-articulation and intensity-with-care signals OpenAI privileges.
Community
AI Coding Assistants: Where They Help and Where They Hurt
Two years of using AI coding assistants daily, the four tasks where they have made me measurably faster, the three places they have actively cost me time, and the workflow I have settled on.
Prompt Engineering Patterns That Survived Six Months of Prod
The five prompting techniques that have actually held up across model upgrades, the four that I tried and dropped, and the eval discipline that lets me tell which is which.
LLM Fundamentals: Tokens, Context, and Cost
Tokens are not characters or words. Context is not free. Cost is per-token in both directions. The three fundamentals that determine 80% of how an LLM-backed feature performs and bills.