First, give conclusions that can be used for decision-making
The core of AI Application Development does not add a chat box to the ordinary system, but rather places probabilities into controlled business processes. The project requires the definition of real tasks, inputs, expected results, unacceptable errors and manual responsibilities, and the selection of models, RAGs, rules or tools for call-up. The application layer still needs to build account numbers, privileges, pages, backstages, APIs, databases, logs, monitoring and distribution systems; the AI dedicated to the preservation of models, tips, know-how, tools and evaluation versions, which deal with lack of answers, hallucinations, low confidence, non-availability of models and cost overruns.
What conditions need to be identified before judgement is made?
The same question may have different answers under different business, data and project phases. It is suggested that the following conditions be checked and that the common findings on the web be incorporated into their own projects.
Suggested order of advance
First, we'll be clear about the target and the border.
Recast operational objectives as duplicate user assignments and samples.
Validation Key Dependence
Distinguishing between the establishment of rules, AI judgement and steps that must be manually confirmed.
Development of assessable outcomes
The product systems, model knowledge, privileges and abnormal retreats are designed simultaneously.
Make sure you decide the next step with the real results.
(c) The acceptance of evidence of production works in a layered manner.
How do you understand it in the actual business?
Traditional passenger service orders can be created by creating a list of work in the required fields; the AAI client service also needs to understand the user’s expression, retrieval and response. The system must show the basis, limit access to client data, commit to refunds to transfer labour, and retest the model or update knowledge, and not only verify whether the worksheet buttons can be clicked.
The easiest pit to step on.
Make the call big model API equal to completing the AI application
Just a few smooth conversations, no fixed task set.
Ignore account privileges, interface failure, manual takeover and ongoing costs
How should we end up receiving and confirming?
The acceptance and inspection should examine the business function, the quality of the AI mission, serious errors, security of authority, interface write-back, manual clearance, performance costs, deployment retreat and delivery of assets separately; the enterprise personnel should be able to update knowledge, switch configurations and repeat the main evaluation.
When preparing to communicate with suppliers or internal teams, it is recommended that current processes, representative samples, existing systems, planning time and budget levels be brought. First, the unknown items are clearly marked, and then the decision is made to use diagnostics, PoC, fixed-range projects or ongoing research and development, which is usually more reliable than a direct demand for a price and duration without borders.