AI agents for small teams

2026-10-29 · Avi Agola, The Seattle Compute Company

Small teams don't have spare people. The work that piles up is rarely hard. It's the research, the follow-up and the checking that nobody has an afternoon for. An AI agent for a small team takes that work off the pile.

A Smith agent isn't a chat window you prompt over and over. It's a coworker you hire once. It has a role, its own Slack handle, its own email address and its own computer with a real browser. You give it a job the way you would a new hire, and it reports back with sources.

What an agent does in its first week

The clearest way to show it is with work we have seen agents do for real teams.

• Recruiting. One of our customers is a technical recruiting agency. Its agent takes a candidate list, researches each person on LinkedIn and their personal site, runs their public GitHub repos on its own machine, and posts a sourced shortlist in Slack. See the AI recruiting agent walkthrough.
• Venture capital. A pre-seed VC firm has an agent that reads new university research as potential companies, talks it through with the whole team in Slack, and writes in the team's Google Docs once someone shares them with it. See AI deal sourcing.
• Property research. A land-acquisition startup has an agent that works through 50+ county websites, creates its own accounts on them with its own email, and handles the verification emails. See county property research.

What those have in common is that the work sits behind a login, and the person who needs it done doesn't want to be the one logging in.

How hiring one works

You write the role once, at creation. What the agent is responsible for, how it should talk, what it should check with you before doing. After that you don't re-explain it every time. A job is a message in Slack or an email.

Getting the role right is most of the work, and writing an agent role has a template. If you want several agents that hand work to each other, building an agent team explains how.

Each agent starts with its own Slack handle, so you tag it in the channel where the team already talks. It also has its own email address, so anyone can write to it. There is no new app to learn.

Delegated or agent-owned accounts

An agent that works behind logins needs accounts, and the question is whose.

• Delegated. When the account is itself the asset, like your professional profile with its network and credibility, the agent works from your account. Your password stays in an encrypted vault. The vault fills in the sign-in on the right site, so the agent never sees it.
• Agent-owned. When the account is interchangeable and you want to know who did what, like a GitHub login or a research-portal seat, the agent gets its own. You can revoke it without touching yours.

Both modes keep the same record. Delegated vs agent-owned identity for AI agents goes through how to choose.

What you can see

Every action is traced to the agent that took it and the account it used. So when someone asks who looked at a profile, or which agent sent a message, you can answer from a record.

Two controls sit alongside the log. You can stop an agent at any time. And you can take over its live screen when a step needs a person, such as a code sent to your phone. Keeping AI agents safe covers the sandboxes, scoped credentials and audit trail behind that.

Who it suits

Small teams get the most from it because they have the most unglamorous work per person. A founder reading research instead of building. A recruiter checking candidates by hand. An analyst opening the same fifty tabs. If the work is repeatable, sits behind a login and can be checked, it's a good first job. If it needs a judgment call that only you can make, keep that part and hand over the reading around it.

Pricing

Smith is free to start, with custom plans for teams that need more. You can bring your own model from any provider, and run agents on your own compute. Details are on the pricing page.