AI Interview Preparation Timeline:
Week-by-Week Study Plan

Three-month plan for thorough preparation: Weeks 1-4 (Coding Foundation): 2-3 LeetCode problems daily focusing on arrays, strings, trees, graphs. Review data structures basics. Build problem-solving patterns. Weeks 5-6 (Advanced Coding): Dynamic programming, backtracking, harder graph problems. Aim for 150-200 total problems solved. Weeks 7-8 (System Design): Study distributed systems fundamentals. Practice 2-3 full system design problems per week. Focus on AI-specific designs (RAG, model serving). Weeks 9-10 (Behavioral): Prepare 15-20 STAR stories. Practice with framework for each company (Amazon LPs, etc.). Week 11 (AI-Specific): Review ML fundamentals, LLM concepts, evaluation metrics. Prepare to discuss your AI projects deeply. Week 12 (Mock Interviews): 4-5 full mock interviews. Light review, rest, confidence building.

One-month compressed plan: Week 1 (Coding Blitz): 3-4 problems daily. Focus on most common patterns: two pointers, sliding window, BFS/DFS, binary search. Skip obscure topics. Week 2 (System Design + More Coding): Continue coding (2 problems/day). Add system design practice (3-4 full problems this week). Focus on AI system design: RAG pipelines, recommendation systems. Week 3 (Behavioral + AI-Specific): Prepare 10 strong STAR stories. Review ML/LLM fundamentals. Deep-dive your own AI projects—you'll be asked about them. Week 4 (Mock Interviews + Polish): 3-4 mock interviews (mix of coding, system design, behavioral). Identify and patch remaining gaps. Rest before real interviews.

Two-week emergency plan: Days 1-5 (Coding Focus): 4-5 problems daily. Focus exclusively on high-frequency patterns: arrays, hash maps, trees, basic graphs. Skip hard DP unless you're already strong. Days 6-8 (System Design): Study 2-3 AI system design problems deeply. Focus on your specific domain (RAG if you do RAG, etc.). Days 9-10 (Behavioral): Prepare 6-8 strong STAR stories covering: conflict, failure, leadership, technical decision. Days 11-12 (AI Deep Dive): Review your own projects thoroughly. Prepare to explain technical decisions and trade-offs. Days 13-14 (Mock + Rest): 2 mock interviews. Light review. Get sleep. Two weeks is tight but doable if you prioritize ruthlessly.

Effective daily schedule (adjust to your availability): Morning (1-2 hours): Fresh mind for coding—solve 2-3 LeetCode problems. Review solutions even for problems you solved. Lunch (30 min): Read one system design article or watch one video. After work (1-2 hours): Alternate between system design practice (2-3 days/week) and behavioral prep (2 days/week). Weekend (3-4 hours): One full mock interview. Review weak areas from the week. Rest is important—cramming burns you out before interviews. Aim for 10-15 hours/week for steady progress.

Priority order for limited time: (1) Coding—still the most common rejection reason. Focus on medium LeetCode, not hards. (2) Your own projects—you'll definitely be asked about them. Know every technical decision deeply. (3) Behavioral—easier to improve quickly than coding. 6-8 solid stories cover most questions. (4) System design—important for senior roles, less critical for entry-level. Focus on AI-specific designs (RAG, model serving). (5) ML fundamentals—brush up on basics but don't deep-dive unless role requires it. Prioritize areas where you're weakest AND that are most likely to be tested for your target role.

Adjust based on your strengths: Strong coder (competitive programming background)—spend less time on LeetCode, more on system design and behavioral. Strong communicator (consulting, PM background)—spend more time on coding, less on behavioral. AI researcher—focus on practical implementation, production systems, coding interviews. Career changer—allocate more total time, don't compress below 6-8 weeks. Take a practice assessment at the start to identify your actual skill levels, not perceived ones.

Most clients invest 10-15 hours per week, but this can be flexible based on your schedule. We'll have weekly 1:1 calls plus time for you to work on projects and learning. The key is consistency. Regular, focused effort beats occasional marathons.

You become a member of the AI Native Engineer community, and you stay and keep going. Career transitions take different amounts of time for everyone, and I'm not going to abandon you if things take longer. You get ongoing support through good times and bad.

Online courses give you content. 1:1 coaching gives you a personalized roadmap, direct feedback on your work, career strategy, interview prep, and accountability. You get answers to your specific questions and guidance tailored to your unique situation instead of generic advice meant for everyone.

Investment details are discussed during the 30-minute strategy call, where we'll assess your goals and create a custom plan. The program is designed to pay for itself quickly through your increased salary. Most AI engineers see a 20-50% pay increase.

Absolutely. Most of my clients work full-time and make steady progress. We'll schedule calls at times that work for you and create a realistic plan that fits your schedule. Consistency matters more than intensity.