How is this study material built?
Four-source synthesis. (1) Anthropic Academy courses on Skilljar (the official Anthropic content, free for all). (2) The CCA-F official exam guide PDF - domain weightings, scenarios, sample questions. (3) Anthropic Partner Network internal briefings on what beta-cohort candidates struggled with. (4) Community signal from r/ClaudeAI score posts and public exam debriefs. Every claim is tagged by source tier.
What is the evidence pip system?
Each factual claim on the site carries a colored emoji: 🟢 official-Anthropic (exam guide, Academy course, Anthropic team statement), 🟡 secondary (partner network materials, beta cohort consensus), 🟠 community (Reddit threads, community blogs, individual debriefs), 🔴 disputed (claims with conflicting sources). The system makes source-quality visible at-a-glance instead of asking you to trust the site uncritically.
Why use tier-graded sourcing instead of just citing sources?
Standard citations let bad sources hide behind a footnote. Evidence pips force every claim to declare its provenance inline - so you can tell at-a-glance whether a number came from Anthropic's exam guide (🟢) or someone's Reddit post (🟠). It mirrors how scientists distinguish primary literature from review papers, applied to certification prep.
How fresh is the content?
Every page footer shows its last-reviewed date. Standard review cadence is 60 days. When Anthropic publishes new guidance - exam blueprint update, Academy course release, release notes mentioning a new primitive - the site is refreshed within 5 business days. The /evidence page lists the source freshness review history.
Who built this site?
Manikandan Jeeva, VP of Data, AI & Analytics at Genpact. Built as personal CCA-F prep, then opened to the public when content depth proved useful. The site is independent of Anthropic but the author's employer is an Anthropic Partner Network member. The /evidence page lists all sources transparently.
How does the site avoid hallucinated or out-of-date facts?
Three guards. (1) Every claim has an evidence pip - a reviewer can spot un-sourced or 🔴 disputed claims at a glance. (2) Critical exam facts (60 questions, 720 to pass, 5 domains) are kept in a canonical fact registry (lib/exam-guide.ts) so they're never re-typed or paraphrased in prose. (3) AI-generated content (adaptive plans, mental-model summaries) runs through deterministic templates first - LLM only fills curated slots, never invents structure.
