Viktor

Credit-based billing is a common business model for AI employee products like Viktor: users consume credits to invoke model capabilities, different tasks consume different amounts, and complex reasoning and long-context retrieval typically consume more credits.

Viktor is an AI employee that can be installed into a Slack or Google Teams workspace, rather than an ordinary AI tool; it autonomously completes the onboarding process, reads workspace messages, learns business context, and works independently.

After connecting to Asana, Viktor can automatically discover all projects, editor rosters, and task statuses, read messages in each channel, understand the business lines, and proactively suggest process improvements.

RAG (Retrieval-Augmented Generation) is one of the core technologies behind Viktor's autonomous onboarding; it lets the large model retrieve context from external knowledge bases (such as Slack channel history, Asana task lists, and Google Drive documents) before acting.

Viktor's first formal job is the daily triage handling for the AI Agent Builders community, running automatically at 3 a.m. (Dubai time) every day.

In one triage run, Viktor opened 79 post threads, flagged 17 window-period member posts, generated 1 draft, and flagged 2 items requiring human attention.

Viktor's weekly member summary task analyzes all posts and new member activity, clusters the most concentrated discussion topics, and generates live event suggestions and content drafts; its most recent output showed 130 active threads, 89 member posts, and 114 active speaking members.

In one task, Viktor got stuck at a waiting-for-confirmation step and needed assistant Zell to reply before it could continue, but Zell did not see it in time, and ultimately Tim had to step in for it to be rerun and completed; this shows that an autonomously operating AI employee still needs human cooperation at key nodes.

Viktor performs a read-only audit once a day, reporting post activity, course counts, paywall status, and Drive backup coverage gaps; in a full audit it found missing link codes, one broken command, and duplicate source documents, and provided fix plans.

Viktor first spent 11 minutes generating a fix plan, and after getting approval, completed actual modifications to the top five most critical issues in Google Drive, and synchronously updated the source mapping files.

Viktor reads course documents through the Google Drive API, sends and receives messages through the Slack API, and syncs task statuses through the Asana API; APIs are the technical prerequisite for AI to directly operate business systems.

Giving AI write permissions brings risks: once the model makes a wrong judgment, it may directly alter production data, so Tim's process retains a "generate fix plan -> human approval -> execute modifications" confirmation step.

Unlike the conversational interaction of ChatGPT or Claude, Viktor exists in the workflow, proactively running tasks, proactively reporting, and proactively suggesting improvements.

After using Viktor for over two weeks, the initial complimentary 16,000 credits still had not been used up, and no actual costs had been incurred yet.

Tech With Tim used the AI employee Viktor for over two weeks, experiencing its autonomous onboarding, community triage handling, member summaries, and course auditing features.