Andromeda and Lattice: how Meta’s ad algorithm actually works now

Meta rebuilt its ad system around two things: a retrieval engine called Andromeda and a unified ranking model called Lattice. What each does, and what it means for how you should actually structure campaigns.

Most advertisers still structure Meta campaigns the way they did in 2020: tight audiences, separate ad sets per interest, manual bid control, one or two creatives per set. That approach now actively fights the system it runs on.

Meta rebuilt the machinery underneath. Two components matter: Andromeda, which retrieves candidate ads, and Lattice, which ranks and predicts. Understanding what each does explains why old habits stopped working.

What Andromeda does

Andromeda is the retrieval layer — the stage that decides which handful of ads, out of millions eligible, even get considered for a given impression. It runs on Meta’s own MTIA silicon and it dramatically expanded how many candidates can be evaluated per auction.

Previously, retrieval was a bottleneck. Coarse filters narrowed the pool early, which meant a well-matched ad could be discarded before ranking ever saw it. Andromeda widened that funnel by orders of magnitude.

Why this broke interest targeting

When retrieval was narrow, telling Meta "show this to people interested in digital marketing, aged 25–34, in Pune" genuinely helped. It reduced a search space the system struggled with.

Now that constraint is a handicap. You are restricting a retrieval engine that would have surfaced buyers your interest list never contained. This is the mechanical reason broad targeting outperforms layered interests in most accounts — not fashion, architecture.

What Lattice does

Lattice is the ranking and prediction layer. Its significance is consolidation: Meta replaced a sprawl of separate, narrowly-trained models with a unified architecture that learns across objectives, placements and formats simultaneously.

Before Lattice, a model predicting purchase probability on Instagram Reels learned largely in isolation from one predicting lead submissions on Facebook Feed. Signal did not transfer well. Lattice shares learning across all of it.

Why this changed the learning phase

Because signal transfers, campaigns exit learning faster and tolerate consolidation better. Fifty conversions per ad set per week remains the guidance, but a consolidated campaign reaches that threshold far quicker than eight fragmented ad sets each starving for data.

This is the mechanical argument for consolidation. Splitting budget across many ad sets does not give you control — it gives every ad set too little data to learn from.

What this means for how you build campaigns

1. Consolidate ruthlessly

2. Creative volume and diversity are now the lever

When targeting and bidding are largely automated, creative is what remains under your control — and Lattice evaluates creative more capably than any earlier system. It is the highest-leverage input you have.

3. Stop micromanaging bids

Manual bidding and aggressive bid caps now constrain a system with better information than you have. Use the lowest-cost or cost-cap strategies and let the auction work. Bid caps have a place in genuinely constrained economics — not as a default.

4. Fix your signal quality instead

This is where advertisers should spend the attention they used to spend on targeting. Lattice is only as good as the conversion data reaching it.

What to stop doing

What actually still needs your judgement

Automation did not remove the marketer. It moved the job.

A practical structure for Indian advertisers

The honest caveat

Meta publishes engineering detail selectively, and the names, architecture and behaviour of these systems change. Treat the specifics as directional rather than permanent, and hold the principle instead: the system now retrieves and ranks better than manual targeting can, so your leverage lies in offer, creative, signal quality and economics.

That principle has survived every algorithm change of the last five years, and it will survive the next.

A diagnostic checklist when performance drops

Campaign performance falls for a small number of reasons, and advertisers usually guess rather than check. Work through these in order — the sequence matters, because fixing creative when the problem is tracking wastes a week.

What to report to a founder or client

One page, monthly, with four numbers and one paragraph. Spend, conversions, blended CAC and contribution against target — then what you learned and what you are changing. Impressions, reach and engagement belong in an appendix if anywhere.

Marketers who report activity get treated as a cost. Marketers who report contribution get treated as an investment, and get budget increases. The difference is entirely in what you choose to put on the first line.

Frequently asked questions

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