How to ship AI features into your product
Shipping AI features means deploying working software - a rubric engine, classifier, retrieval, or agent - into your product, not a prototype. The fastest, lowest-risk path is a fixed-scope sprint that ends with one feature running in production, then iterating from there.
Scope one outcome that can ship
Most AI work stalls because the scope is open-ended. The fix is to agree a single outcome that can be deployed in two weeks - one feature, one clear success measure - and build only that. A narrow, shippable scope beats a broad roadmap that never reaches production.
Build rule-first, then add the model
Put a simple rule in front of the model wherever one will do. It makes the feature faster, cheaper to run, and explainable when a decision needs to be checked. The model carries the cases the rules cannot, not the whole load.
Deploy, measure, iterate
Ship the feature into production behind whatever guard you need, measure it against the success measure you agreed, and iterate. A Ship Sprint with Cognitiv (USD $4,000, two weeks) is built to end exactly here - deployed and measured.
Common questions
How long does it take to ship an AI feature?+
With a tight scope, a single feature can be deployed in about two weeks. Cognitiv's Ship Sprint is a two-week, fixed-scope engagement that ends with one outcome running in production.
What is the most common reason AI features do not ship?+
Scope. Open-ended AI projects rarely reach production. Agreeing one outcome that can deploy in two weeks is the most reliable way to actually ship.
Can you ship AI features into an existing product?+
Yes. Cognitiv works inside your existing stack and repo, ships the feature, and hands over a short written guide so your team can run and extend it.
Have a roadmap you need shipped?
Start with a two-week Ship Sprint - deployed, not a document.