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One workflow · verifiable output

AI for one work task

I configure AI for one connected workflow: matching price lists, compiling a register, answering management questions using CRM and accounting records, or helping a sales representative prepare a sale. The assistant can answer different questions within the chosen workflow. Before starting, we define sources, permitted actions, outputs, and review steps.

Denis Skripnik — a blind specialist in working with AI agents. I examine the task, configure the workflow, and work with you to verify the result against agreed rules.

AI agent setup is already selected in the brief. Name the scenario: “AI for one work task”. Describe the files or systems you use, the result you need, and any exceptions. Start with a description of an anonymized sample.

Who this is for

A business owner, team manager, sales representative, or purchasing specialist with a recurring workflow, available data, and a designated reviewer. We start with one workflow. It may include different questions and several sources; automating the entire business is outside this scope.

Inputs and deliverables

• Input: sample files or agreed system exports, working rules, user questions, and examples of correct results, including exceptions.
• Output: a workflow configured in the agreed environment, producing a verifiable table, a source-linked answer, or a draft for an employee. Unknowns and exceptions are explicit; handover includes instructions and training.
• Before implementation, we define systems, roles, available fields and records, supported questions and actions, volume, output format, and acceptance criteria. An assistant is not restricted to one fixed question or report. We assess the result by how it performs the task, not by the model name.

Illustrative example, not a client case study

A purchasing team receives supplier price lists and manually matches them against its catalog. A bounded workflow reads the agreed files, proposes matches with source-row references, separates disputed items, and produces a review table. An employee decides whether items match and what to buy.

Scope to agree before starting

• Review one process using samples and choose an approach: ordinary rules first, AI only where it adds value.
• Configure reading selected sources, processing questions or data, output formats, and checks in the agreed environment.
• Test in the customer’s environment against an agreed test set, provide operating instructions, and train the responsible employee to review the result.

When a separate AI workflow is not needed

If a ready-made service, a 1C feature, a formula, or an ordinary script is sufficient, prefer it. Adding a model cannot fix undefined rules, unavailable data, or the lack of a reviewer. New systems, roles, data types, and extensions beyond the agreed volume need separate assessment. Sources are read-only: CRM writes, record merging, outreach, independent negotiations, and financial or HR decisions are excluded. A human reviews management answers and sales drafts.

Sources, access, and your responsibilities

• An anonymized export is enough to start: remove information that could identify a person, business secrets, and unnecessary fields. Do not put passwords or keys in the brief.
• For implementation, we agree the minimum necessary permissions, preferably a dedicated account with read access only to selected sources. An export instead of production-system access is an acceptable alternative.
• You provide lawfully available samples, rules, an authorized environment, and a designated reviewer who resolves disputed data. We agree storage, deletion, and permitted model-provider data transfers in advance.

Acceptance, instructions, and training

At acceptance, we run the chosen workflow in the customer’s environment. We agree criteria, a test set with ordinary and disputed examples, output format, and error reporting before implementation. Handover provides operating and review instructions and training for the responsible employee; their format and scope are specified in the proposal.

Iteration count, correction of nonconforming results, requirement changes, and support after acceptance are agreed separately before starting. Unlimited revisions and ongoing support are not implied.

Timing, price, and external expenses

The price and exact duration are confirmed after reviewing a sample and before work starts. They depend on data quality, formats, volume, environment, and review requirements. Existing service price guidance is not a fixed quote for this scenario.

If a sample is insufficient to define the scope reliably, a paid discovery or bounded pilot can be agreed separately, with its own deliverable and criteria. It does not automatically commit either party to full implementation.

Server costs, paid services, and model usage are separate from implementation fees. Before starting, we agree what is necessary, who pays for accounts, and spending and processing limits. Payment for the work follows scope and quote confirmation only.