GILLI · · 4 min read
Species Queues Before Runtime Species
The safe way to expand a fishing app is to research species in a queue before promoting them into runtime forecasts.
The species queue exists so that research can mature before a species enters live forecasts.
Gilli's Mediterranean expansion work uses a queue-first approach because adding species affects more than content. It can affect predictions, search, aliases, images, regional presence, conservation language, and user expectations.
Research Has States
A species entry can be useful before it is forecast-ready.
It may have reliable taxonomy but uncertain temperature thresholds. It may have good habitat notes but weak regional seasonality. It may be safe for encyclopedia copy but not for scoring logic.
Those states should be explicit.
Otherwise the app treats incomplete research as production truth.
Forecast IDs Need Care
Runtime prediction systems need stable IDs.
Aliases and common names can change. Scientific names can have synonyms. Existing legacy forecast IDs may not match the desired unified species ID. If the bridge is wrong, the app can show one species while scoring another.
That is why bridge work should wait until profiles are verified.
Conservation Can Block Casual Scoring
Some species are high-interest but high-risk.
Bluefin tuna, groupers, and other regulated or conservation-sensitive species need careful language. An app should avoid presenting casual bite forecasts where rules, protections, or ethical context are central.
They belong in education before scoring logic.
Images Should Follow Identity
Species art is easiest after IDs are stable.
Generating field-guide images before taxonomy and profile promotion can create asset drift. The better workflow is research, verify, promote, then attach or generate assets with metadata.
The image should follow the species record, not precede it.
Queues Make Expansion Safer
A queue lets the team move quickly without polluting runtime behavior.
It captures candidate species, source targets, field classifications, implementation status, and future validation needs. It gives product and engineering a shared place to decide what is ready.
That is how Gilli can grow coverage without making things up.
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