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The priority questions of this track, in study order. Answer each one aloud before you read anything: the theme page behind every question adds what a strong answer covers and what to read.

For a study sequence with weekly practice and completion checks, use the learning path.

Choose a focused route from the learning roadmap: AI-assisted coding, production AI engineering or AI Leadership.

See the coverage audit, Engineering research, Leadership audit and expansion plan for evidence limits and next steps.

Answers to these questions

• 1. An assistant reads external email, searches internal documents and sends replies. Where could an attacker redirect it, and how would you constrain the damage?
  • System design · Senior · Safety, security and governance · Asked at: Anthropic † · ✍ Answer
• 2. How would you organise safe deployment of an AI model into production?
  • System design · Senior · Safety, security and governance · Asked at: Anthropic † · ✍ Answer
• 3. How would you approach safety for a generative-AI consumer product?
  • Product case · Senior · Safety, security and governance · Asked at: OpenAI † · ✍ Answer
• 4. What safeguards should surround an AI system that acts on a user's behalf?
  • System design · Senior · Safety, security and governance · Asked at: OpenAI † · ✍ Answer
• 5. Describe a situation where delivery pressure conflicted with security or safety concerns. How did you decide what to do?
  • Behavioral · Senior · Safety, security and governance · Asked at: Anthropic 🗣 · ✍ Answer
• 6. How would you improve ChatGPT for enterprise customers?
  • Product case · Senior · AI product strategy and metrics · Asked at: OpenAI † · ✍ Answer
• 7. A model offers much greater capability but costs ten times as much. How would you decide what product to build with it?
  • Product case · Senior · AI product strategy and metrics · Asked at: OpenAI † · ✍ Answer
• 8. How do you decide whether an LLM is useful for a proposed product problem?
  • Product case · Senior · AI product strategy and metrics · Asked at: Google and Google DeepMind † · ✍ Answer
• 9. Design a Gemini-based assistant for university students.
  • Product case · Senior · AI product strategy and metrics · Asked at: Google and Google DeepMind † · ✍ Answer
• 10. Users say Gemini gives incorrect answers with excessive confidence. What would you change?
  • Product case · Senior · AI product strategy and metrics · Asked at: Google and Google DeepMind † · ✍ Answer
• 11. How would you prioritise features for an AI writing assistant in Microsoft Word?
  • Product case · Senior · AI product strategy and metrics · Asked at: Microsoft † · ✍ Answer
• 12. How would you measure success for an AI feature in a Microsoft product?
  • Product case · Senior · AI product strategy and metrics · Asked at: Microsoft † · ✍ Answer
• 13. What North Star metric would you choose for an AI search product, and what would constrain it?
  • Product case · Senior · AI product strategy and metrics · Asked at: Perplexity † · ✍ Answer
• 14. Notification engagement rises while total time spent remains flat. How would you interpret that result?
  • Product case · Senior · AI product strategy and metrics · Asked at: Meta 🗣 · ✍ Answer
• 15. Choose an AI agent or product you use and propose its most valuable improvement.
  • Product case · Senior · AI product strategy and metrics · Asked at: Amazon † · ✍ Answer
• 16. Define a strategy for an internal AI platform, including who owns its success metrics.
  • Product case · Senior · AI platform and operating model · Asked at: Stripe † · ✍ Answer
• 17. How would you support multiple model providers when some deployment environments permit only a subset of models?
  • System design · Senior · AI platform and operating model · Asked at: Palantir † · ✍ Answer
• 18. How would you handle an engineer who is not meeting performance expectations?
  • Applied scenario · Senior · Leading engineering teams · Asked at: Google and Google DeepMind 🗣 · ✍ Answer
• 19. How would you handle a high-performing engineer whose behaviour repeatedly creates conflict with teammates?
  • Applied scenario · Senior · Leading engineering teams · Asked at: Google and Google DeepMind 🗣 · ✍ Answer
• 20. Describe how someone you mentored progressed in their career.
  • Behavioral · Senior · Leading engineering teams · Asked at: Anthropic 🗣 · ✍ Answer
• 21. What do you do when your team disagrees with your proposed direction?
  • Applied scenario · Senior · Leading engineering teams · Asked at: Anthropic 🗣 · ✍ Answer
• 22. Tell me about a difficult organisational change you managed that involved high-performing engineers leaving. How did you respond?
  • Behavioral · Senior · Leading engineering teams · Asked at: Google and Google DeepMind 🗣 · ✍ Answer
• 23. How would you stabilise an engineering team after a change in management?
  • Applied scenario · Senior · Leading engineering teams · Asked at: Google and Google DeepMind 🗣 · ✍ Answer
• 24. Describe how you identified a valuable opportunity and persuaded a group to deliver it.
  • Behavioral · Senior · Leading engineering teams · Asked at: Monzo ✅ · ✍ Answer
• 25. Walk through the most difficult product launch you led.
  • Behavioral · Senior · Programmes and delivery · Asked at: OpenAI † · ✍ Answer
• 26. Three weeks before launching an LLM feature, evaluation reveals substantial hallucinations on edge cases. What happens next?
  • Applied scenario · Senior · Programmes and delivery · Asked at: Amazon † · ✍ Answer
• 27. Describe a large cross-functional project, including ambiguity, roadblocks and delays.
  • Behavioral · Senior · Programmes and delivery · Asked at: Meta 🗣 · ✍ Answer
• 28. How would you roll out updates to Alexa devices already deployed in people's homes?
  • System design · Senior · Programmes and delivery · Asked at: Amazon † · ✍ Answer
• 29. A customer wants to automate claims processing with AI. What would you do in the first two weeks?
  • Applied scenario · Senior · Applied and customer scenarios · Asked at: OpenAI † · ✍ Answer
• 30. A customer executive wants to cancel an AI pilot because it keeps producing wrong results. What would you do over the next 48 hours?
  • Applied scenario · Senior · Applied and customer scenarios · Asked at: Palantir † · ✍ Answer
• 31. A customer insists on fine-tuning their own model on support tickets, while you suspect retrieval would be enough. How do you proceed?
  • Applied scenario · Senior · Applied and customer scenarios · Asked at: Databricks † · ✍ Answer
• 32. A deployed agent's base model will be retired in 60 days. How would you migrate it without losing quality?
  • Applied scenario · Senior · Applied and customer scenarios · Asked at: Databricks † · ✍ Answer
• 33. A customer says their eight-GPU chatbot is too slow and too expensive. You have a week with them; how do you use it?
  • Applied scenario · Senior · Applied and customer scenarios · ✍ Answer
• 34. An enterprise wants document Q&A over two million internal files within four weeks, with no data leaving its VPC. How would you scope the pilot?
  • Applied scenario · Senior · Applied and customer scenarios · ✍ Answer
• 35. A shopping agent can initiate payments. How would you prove that each payment matches the user's actual authorisation?
  • System design · Senior · Payments and regulated domains · 🧪 generated from job-posting themes · ✍ Answer
• 36. An AI support agent initiates a refund, then the payment API times out. How should the system recover without issuing the refund twice?
  • System design · Senior · Payments and regulated domains · 🧪 generated from job-posting themes · ✍ Answer
• 37. A bank wants to roll out an AI assistant that proposes case decisions to employees. What evidence and controls would you require before expansion?
  • Applied scenario · Senior · Payments and regulated domains · 🧪 generated from job-posting themes · ✍ Answer
• 38. Why do you want to work at Anthropic, and where do you disagree with its approach?
  • Self-presentation · Senior · Behavioral and values · Asked at: Anthropic † · ✍ Answer
• 39. Describe a mistake you made, its consequences and what you changed afterward.
  • Behavioral · Senior · Behavioral and values · Asked at: OpenAI † · ✍ Answer
• 40. Tell me about a time you disagreed with someone and could not persuade them.
  • Behavioral · Senior · Behavioral and values · Asked at: Amazon † · ✍ Answer
• 41. Explain the product trade-offs in choosing a model.
  • Knowledge · Senior · AI product strategy and metrics · Asked at: Microsoft † · ✍ Answer
• 42. Which business use cases suit AI agents, and how would you compare them?
  • Product case · Senior · AI product strategy and metrics · Asked at: Microsoft † · ✍ Answer
• 43. How would you price an enterprise AI product, which costs must you count, and how does customising it for each client affect its margin?
  • Product case · AI product strategy and metrics · ✍ Answer
• 44. Where does an AI answer engine outperform traditional search, and where does it fall short? What would you improve first?
  • Product case · Senior · AI product strategy and metrics · Asked at: Perplexity † · ✍ Answer
• 45. How would you evaluate an enterprise AI assistant when your team cannot inspect customer data?
  • System design · Senior · AI platform and operating model · ✍ Answer
• 46. An engineering team adopts AI coding tools, but reviewers struggle to verify the resulting changes. How would you build the missing capability?
  • Applied scenario · Senior · Leading engineering teams · 🧪 generated from job-posting themes · ✍ Answer
• 47. Describe your most recent strategic engineering hire. How did you define the hiring bar and assess whether the hire met the need?
  • Behavioral · Senior · Leading engineering teams · Asked at: Stripe † · ✍ Answer
• 48. How do you establish engineering quality standards across a team?
  • Applied scenario · Senior · Leading engineering teams · Asked at: Stripe † · ✍ Answer
• 49. Researchers want more exploration while product engineers need a reliable release. How would you structure ownership and handoffs?
  • Applied scenario · Senior · Leading engineering teams · 🧪 generated from job-posting themes · ✍ Answer
• 50. How would you plan an AI programme whose central research hypothesis may fail?
  • Applied scenario · Senior · Programmes and delivery · 🧪 generated from job-posting themes · ✍ Answer
• 51. Engineering, operations and risk teams disagree about launch readiness. How would you reach a traceable decision?
  • Applied scenario · Senior · Programmes and delivery · 🧪 generated from job-posting themes · ✍ Answer
• 52. A contact centre wants voice agents to replace its phone menus. How would you lead the engagement?
  • Applied scenario · Senior · Applied and customer scenarios · ✍ Answer
• 53. A product team requests an exception to an AI safety control for one enterprise customer. How would you assess, authorise and time-limit the exception?
  • Applied scenario · Senior · Safety, security and governance · 🧪 generated from job-posting themes · ✍ Answer
• 54. Tell me about conflicting stakeholder priorities and how you established alignment.
  • Behavioral · Senior · Behavioral and values · Asked at: OpenAI † · ✍ Answer
• 55. Describe feedback that was difficult for you to hear and what you did with it.
  • Behavioral · Senior · Behavioral and values · Asked at: Anthropic † · ✍ Answer
• 56. Present a major initiative you led: what worked, what did not, and what you learned.
  • Self-presentation · Senior · Programmes and delivery · Asked at: Anthropic 🗣 · ✍ Answer
• 57. Tell me about a technical misjudgement that delayed a project.
  • Behavioral · Senior · Programmes and delivery · Asked at: Anthropic † · ✍ Answer
• 58. An upstream data team will miss a milestone on your AI programme. How do you revise the plan and communicate the impact?
  • Applied scenario · Senior · Programmes and delivery · 🧪 generated from job-posting themes · ✍ Answer
• 59. What is the largest team you have managed, and how did your responsibilities change at that scale?
  • Self-presentation · Senior · Leading engineering teams · Asked at: Anthropic 🗣 · ✍ Answer
• 60. Describe a team disagreement that you resolved without discarding the valid concerns on either side.
  • Behavioral · Senior · Leading engineering teams · Asked at: Google and Google DeepMind 🗣 · ✍ Answer
• 61. Two product teams need shared AI infrastructure, but neither can spare an engineer. How would you establish ownership without creating an unstaffed platform promise?
  • Applied scenario · Senior · Leading engineering teams · 🧪 generated from job-posting themes · ✍ Answer
• 62. A clinical AI service handles recordings, transcripts and notes containing protected health information. How does that constrain architecture and use of third-party model APIs?
  • System design · Senior · Payments and regulated domains · ✍ Answer
• 63. Refactor a small, poorly structured program with passing tests. Explain the first change and how you preserve observable behaviour.
  • Coding · Practical coding · Asked at: OpenAI † · ✍ Answer
• 64. Design an agent that creates and updates work orders in a live ERP without duplicating or silently corrupting business operations.
  • System design · Agents, tools and protocols · Asked at: Palantir † · ✍ Answer
• 65. What do you do when an MVP of an enterprise AI product is too expensive or too slow to build?
  • Product case · AI product strategy and metrics · ✍ Answer
• 66. In discovery for an enterprise AI product, who is the persona, where do you find B2B respondents, and how will you tell that a problem is worth solving?
  • Product case · AI product strategy and metrics · ✍ Answer
• 67. Design a moderation system that combines specialist classifiers and LLMs while controlling delay and review workload.
  • System design · AI system design · Asked at: Meta † · ✍ Answer
• 68. How would you weigh a performance improvement against reduced model interpretability?
  • Applied scenario · Senior · Safety, security and governance · Asked at: Anthropic † · ✍ Answer
• 69. Design a service that lets several teams query a shared dataset without exposing the underlying raw records.
  • System design · Senior · AI platform and operating model · Asked at: Palantir † · ✍ Answer
• 70. An enterprise customer says Claude hallucinates in their retrieval-based knowledge assistant. How would you investigate the first failures?
  • Applied scenario · Senior · Applied and customer scenarios · Asked at: Anthropic † · ✍ Answer
• 71. You own the next quarter’s AI investment portfolio. A 30% budget cut affects a revenue pilot, a mandatory risk-control project and shared evaluation infrastructure. How would you reallocate money and people and secure executive agreement?
  • Applied scenario · AI platform and operating model · 🧪 generated from job-posting themes · ✍ Answer
• 72. As the investment owner, decide whether to renew a managed AI service or fund an internal replacement. The vendor’s price doubles in six months and exported data alone cannot reproduce its behaviour. What decision and exit plan would you approve?
  • Applied scenario · AI platform and operating model · 🧪 generated from job-posting themes · ✍ Answer
• 73. You manage three engineering managers delivering a shared AI initiative. Two blame each other for an evaluation gap while the executive sponsor has promised a launch date. How would you restore accountability without taking over their teams?
  • Applied scenario · Leading engineering teams · 🧪 generated from job-posting themes · ✍ Answer
• 74. An AI product has rising usage but no credible improvement in customer outcomes; review costs keep increasing. The sponsor wants another quarter of investment. What evidence would make you expand, narrow, pause or stop it, and how would you handle existing users?
  • Product case · AI product strategy and metrics · 🧪 generated from job-posting themes · ✍ Answer
• 75. During an AI rollout, a provider changes model behaviour and harmful actions reach customers. The previous model cannot be restored immediately. As the programme lead, how do you coordinate containment, customer response and a defensible restart?
  • Applied scenario · Programmes and delivery · 🧪 generated from job-posting themes · ✍ Answer
• 76. Candidates now use AI assistants during technical interviews. How would you redesign your loop so that it still produces a usable hiring signal?
  • Applied scenario · Leading engineering teams · 🧪 generated from job-posting themes · ✍ Answer
• 77. Several product teams share one internal AI gateway. How would you keep one team's traffic, data and caches from affecting another's?
  • System design · AI platform and operating model · 🧪 generated from job-posting themes · ✍ Answer
• 78. A provider announces that a model version your products depend on retires in three months. How would you run the migration across the teams that use it?
  • Applied scenario · AI platform and operating model · 🧪 generated from job-posting themes · ✍ Answer
• 79. Inference spend on a shared AI platform doubles in a quarter and no team recognises the bill as theirs. How would you make the cost attributable and controllable?
  • Applied scenario · AI platform and operating model · 🧪 generated from job-posting themes · ✍ Answer
• 80. Your AI platform's latency and availability depend on an external model provider. What would you promise internal teams, and how would you keep that promise?
  • System design · AI platform and operating model · 🧪 generated from job-posting themes · ✍ Answer
• 81. Before launching an assistant that can use tools, how would you organise adversarial testing, and what would a clean result let you claim?
  • System design · Safety, security and governance · 🧪 generated from job-posting themes · ✍ Answer
• 82. Your organisation adopted AI coding tools and leadership wants to know whether they worked. How would you answer that credibly?
  • Applied scenario · Leading engineering teams · 🧪 generated from job-posting themes · ✍ Answer