Business context consists of several layers
A brand profile is necessary but not sufficient. For a specific campaign, the system needs permanent brand rules, current product data, goal and period of the order, channel requirements, confirmed learnings and – if available – performance signals. These layers have different lifespans and reliability.
Permanent facts such as brand names or banned terms may be given greater weight than a short-term trend. Current inventory is more important than an old campaign note. An explicit user instruction for the current job takes precedence over a general preference. This priority must be defined in the system and not arise spontaneously in the text model.
- Brand identity and tonality
- Product and offer facts
- Order goal and target group
- Channel and format rules
- confirmed learnings
- current performance and commerce signals
Origin and workspace are part of the information
The sentence “this product sells well” is hardly usable without a source. A reliable signal names workspace, product ID, data source, time period, measurement value and confidence. This allows an agent to decide whether the signal belongs to the current campaign and whether it can be a recommendation or a hard requirement.
Workspace isolation prevents learnings, orders or brand rules from mixing between customers. This also applies to seemingly harmless data such as preferred emoji usage or text length. A preference from another workspace is not a shortcut, but an incorrect data source.
Performance becomes an input, not an autopilot
A successful format can influence the next planning, but should not determine it alone. Reach, clicks, leads and sales answer different questions. In addition, a result can be influenced by season, budget, target group or offer. The learning therefore not only stores the winner, but also the measurement, sample and evidence.
Confidence protects against overreaction. A single post can generate a candidate rule. Only repeated and comparable signals turn this into an active preference. This means the system remains capable of learning without declaring every short-term deviation the new truth.
Shares create high-quality context
A user's change is a strong signal, but its significance depends on the reason. If a sentence has been corrected due to incorrect product information, this is more important than a spontaneous change in style. A review dialogue should therefore be able to record whether a change was factual, legal, brand-related or purely campaign-specific.
The system can immediately apply the specific change to the current post. She will initially be saved as a candidate for future campaigns. If the user confirms the same pattern several times or performance data supports the change, confidence increases.
A good result explains which context was effective
At the end of an agent run, it should be visible which brand rules, product data, learnings and performance signals were applied. The number of rejected or unsuitable signals is equally important. This makes the decision verifiable and helps to correct incorrect rules in a targeted manner.
Business context is therefore not the largest possible prompt. It is a curated decision log: relevant to the order, limited to the current workspace, evaluated by origin and controllable by human approval.
FAQ
Which information takes precedence in the conflict?
An explicit instruction for the current order usually precedes a general preference. Verified product and brand facts must not be overwritten by weak performance signals.
Does every user change automatically become a learning experience?
She can be saved as a candidate. A permanently active rule should require additional confirmation, sufficient confidence and comprehensible evidence.