Don’t start with AI. Start with one task.

Hey, Obaid here — back with this week's rundown: what we're building, a real result, and an AI shift worth knowing about.

Most companies know they should be using AI. Then they start researching it and get buried under models, tools, and conflicting advice before they've done anything at all.

The easiest way to begin is to pick one task your team already understands and give it to an agent. This week, we’re showing you what that looks like with a document operations workflow.

Client Win: 158 client documents organized and verified

Most firms already have a way to collect documents. The problem begins after those documents arrive.

A client shares files through a Slack channel. The files may have unclear names, belong in different locations, or arrive together without much explanation.

On a normal day, this daunting tasks of opening each document, determining where it belongs, renaming it according to the firm’s standards, uploading it to the correct folder, and checking that nothing was misplaced is assigned to an individual taking hours.

But now… A client shares the files through a Slack channel, and tags Susan, an AI Agent. Susan, then handles that work directly from the conversation.

Susan reads the client’s message and attachments, uses the surrounding context to understand each file, applies the firm’s naming convention, and places every document in the correct location.

Before finishing, the agent confirms that every file reached its intended destination.

Across just NINE active filing days, this agent organized and verified 158 client documents!

The client didn’t need another portal. What they needed was for all the tedious work after EVERY upload to disappear.

Worth Knowing: Jev, a model for fast decisions

Jev went viral this week because it is designed to make small, structured decisions quickly.

Think of it as a fast sorter. You give it information and ask it to choose, score, route, or stop.

HiringCafe tested Jev by scoring how closely a résumé matched a job. In its human-labeled benchmark, Jev scored 0.79, compared with 0.72–0.77 for the other tested models. The reported benchmark cost was $0.02, compared with $0.14–$0.29.See the benchmark.

Here is a simple way to identify a good Jev task:

Does the task end with a score, category, route, or yes-or-no answer?

An SEO agent could use a model like Jev to score thousands of opportunities based on rankings, visits, conversion potential, and booked appointments. A writing model can then research and create the winning article.

Have one repetitive task your team works through every week? Bring it to a call and we'll run it through the four-question test with you!

Until next time, — Obaid