How AI is Powering the Future of Our Products

Every product page has an AI section now, and most of them mean nothing. So rather than claim the whole ecosystem is AI-powered, it is more useful to say precisely where AI earns its place in what we build, and where adding it would make the product worse.

Where it works

Generating a first draft

This is the strongest case, and it is what CubieAI is built on. A blank caption box is a hard problem for a human and an easy one for a model. The model does not need to be right — it needs to give you something to react to. Editing a mediocre draft is far faster than producing a good one from nothing.

Summarising and classifying

Turning a long thread into three lines, or sorting incoming items into categories, is work that is tedious for people and reliable for models. It is unglamorous and it saves real time.

Surfacing patterns in your own data

In Cubie FX, the interesting question is not what the market will do — nobody can answer that honestly. It is what you keep doing. Which setups you lose on. Which sessions you trade badly. That is pattern recognition over a bounded dataset, and it is a genuinely good fit.

Where we deliberately don't use it

• Anything that looks like financial advice. A model that predicts price movements is a model that will be confidently wrong at somebody's expense. Cubie FX gives traders tools and data, not signals.
• Reading private messages. ChatCubie conversations are not training material and are not summarised by a model in the background. Encryption you undo server-side to run inference is not encryption.
• Replacing a working interface. If a task takes two clicks, a chat box that takes a sentence and a wait is not an improvement.

The rule we use

If the feature would still be useful when the model gets it wrong, it is a good use of AI. If being wrong makes it harmful, it needs a different design.

A caption suggestion that misses is a mild annoyance — you regenerate. A trading signal that misses costs money. That asymmetry decides where the technology goes.

What is coming

The near-term work is on the drafting side: more tools in CubieAI, better tone control, and multi-platform variations of a single post. Longer term, the interesting problem is the ecosystem one — giving each product access to the same assistant layer without each of them needing its own integration.