blog // engineering guides
How the decision layer
is actually built.
Practical, vendor-neutral guides to ranking, recommendations, and monetization on consumer platforms. Written to explain how these systems work, not to sell you one.
# 01 / guides
Ranking and decisioning, explained end to end.
Each guide takes one system apart: the stages, the tradeoffs, the failure modes, and where a decisioning API fits if you would rather not build it. Start anywhere.
Learn how recommender systems work, from collaborative filtering and ranking to cold starts and production deployment.
Explore 7 ways to monetize an app beyond ads and subscriptions, from transaction fees to sponsored listings.
Learn how ad server APIs select ads, fill sponsored slots, and integrate with marketplace search and feed systems.
Build personalized For You feed with one API call. Learn candidate ranking, integration, latency and production basics.
Learn how a feed ranking API replaces in-house ranking logic, simplifies infrastructure, and supports personalization.
Learn how marketplaces turn feed positions into revenue with sponsored listings and advertising.
Recommendation API vs engine: Compare architecture, costs, ranking, and when to build vs buy.
How auction APIs rank bidders, set clearing prices, and place sponsored results in real time.
Add sponsored listings to search and feeds without building a full ad server.
engineering ownership, data requirements, and the long-term cost of owning it yourself
what a ranking API does, how it differs from a recommendation engine, and what to check before you buy
candidate generation, ranking, serving, evaluation, and the build-vs-buy call
take-rate, sponsored listings, and balancing buyers, sellers, and supply
why the two stages are different problems, and where each one belongs
retrieval, ranking, and the serving stack behind a personalized recommender
auctions, pacing, and pricing paid slots against the organic order