PLACEMENT READY GATE (Pre-Placement Clearance)

Weekly contest + 5-problem cold recall sprint from Problem-Solving Journal.

Check that every problem named in Architecture §14 is logged in the Journal with a solution link and a re-solve date; list gaps and schedule them. Why: you must know what you can actually solve cold before drives begin. Ledger checkpoint: ≥ 370 unique problems logged in the Journal (cumulative; tracked metric, Architecture §3).

Practice adaptive pitches for Track A (product), Track B (bank), and Track C (AI platform). Master technical walk-through of your capstone and ml-from-scratch repositories. Develop a structured 5-minute capstone demo script (problem statement, architecture overview, key technical decisions, live demo walk-through, performance metrics) and prepare answers to 5 likely interviewer follow-ups; record yourself delivering the demo and pitch. Map your 5 STAR stories to company-specific behavioral frameworks beyond Amazon LPs: Google "Googleyness" (intellectual humility, comfort with ambiguity, collaborative problem-solving), Uber "Go-Getter" (bias to action, making the big bet, owner's mentality), Atlassian Values (open company, no bullshit; build with heart and balance). Architecture §6.5

Verify all GitHub repositories have clean READMEs, architecture diagrams, step-by-step installation guides, and live demo links. Architecture §6.1

Review OA format, syllabus, past interview questions and tech stack for the Target-40 companies in the first drive wave; mark each Apply / Prepare / Stretch.

Fill the Readiness Scorecard (Architecture §4.2) from logged evidence only: (1) transfer pass rate ≥ 75% of problems across the last 8 transfer sets; (2) cold re-solve of 10 random Journal problems, ≥ 8 solved inside 25 min each; (3) OA simulations average ≥ 70% of test cases over the last 3, none below 50%; (4) the last 4 mocks each pass the §15 rule (no dimension below 3/5, average ≥ 3.5), at least 2 of them with an experienced interviewer; (5) both 90-min machine-coding rounds produced running, tested code; (6) capstone README holds a measured load test with its method; (7) aptitude drill accuracy ≥ 70%. Any red metric triggers its remediation lane in W39–40.

Calendar check against the Opportunity Calendar (Architecture §16); send ≥ 8 personalised outreach messages (alumni, seniors, recruiters) and log each in the Tracker; follow up open threads; ask for a referral 1–2 days after any OA invite; apply within 72 h of any new posting on the Target-40.

60-min unseen HLD prompt (e.g. news feed) followed by a 30-min behavioural with LP mapping. Rubric: HLD (Architecture §15.3: requirements → estimation → API → data model → architecture → deep dive → bottlenecks/trade-offs). Rubric: Behavioural (Architecture §15.4: STAR + LP mapping + quantification + brevity).

Take an unfamiliar small repo, extend one feature and add tests with an AI assistant while narrating; practise verifying or rejecting AI output and prepare an honest "how I use AI at work" talking point. Zero-AI wording applies only to timed DSA sets. Rubric: AI-assisted round (Architecture §15.6: problem framing, verification, tests, narration).

30-minute blitz revision across OS (virtual memory, deadlocks), DBMS (normalization, indexing, transactions), and CN (TCP handshake, TLS).