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AI agents, and how to build your first one.

A chat answers a question. A Project remembers your context so you don't re-explain it every time. An agent is a different thing entirely: you give it a goal once, and it goes and does the work in multiple steps, on its own, without you sitting there prompting each one.

What Makes Something an Agent, Not Just a Chat

A chat is a single exchange. You ask, it answers, you're both done. A Project is a standing chat with memory, it knows your team and your format, but it still only acts when you show up and type something.

An agent is neither. Give it a goal, "check this doc every week and summarize what changed," and it plans the steps itself: check the doc, compare it to last time, pull out what's different, write the summary, and hand it to you. It can use tools along the way, search, read a file, check a calendar, without you walking it through each one.

The distinction that actually matters for a manager isn't technical, it's this: a Project waits for you. An agent doesn't.

The Part That Actually Changes the Job: You Can Schedule It

This is the real shift. An agent doesn't just run when you ask, it can run on a timer. "Every Monday at 8am, check the team update doc, compile what's changed, and have a summary ready before my 9am." You never open the tool. It's just done, waiting, when you need it.

That's the leap from a tool you use to a system that runs without you, the same leap you're trying to build in your team when you delegate well: you're not doing the task, and you're not checking on it constantly either. You've set it up once, and now it happens.

Where This Actually Helps a Manager
A Monday status digest
Pulls updates from wherever your team logs them and has a draft summary waiting before you need it, instead of you assembling it from six Slack threads.
Meeting prep for recurring 1:1s
Pulls the last set of notes and any open action items for that person before each meeting, so you walk in already caught up.
Inbox or Slack triage
Flags anything time-sensitive so you're not scanning every message yourself first thing in the morning.
A recurring report reviewer
Checks a report against a rule set, numbers that don't reconcile, missing sections, before it reaches you, the same way the reviewing-reports use case in the last article works, just running on its own schedule now.
Every Agent Has Five Parts

Before you touch a product's specific buttons, it helps to know what you're actually building. Every agent, in any tool, on any platform, breaks down into the same five parts. Learn these once and you can build an agent anywhere, not just wherever these instructions happen to point today.

1. A job
One narrow, named outcome. "Summarize the update doc into three bullets every Monday," not "help me manage my team."
2. Instructions
The brief you'd give a new hire: what to check, how to decide, and the exact format you want back.
3. Knowledge
What it's allowed to draw on, past examples, a docs folder, your team's goals. Without this it guesses.
4. Tools
What it's actually allowed to touch, read a calendar, search a doc, draft an email. Keep this list short on purpose.
5. A trigger
What starts it: a schedule, an event, or you asking. This is the part that turns a Project into an agent, it runs without you opening anything.

The walkthrough below builds all five using Claude's or ChatGPT's Tasks feature, because that's the fastest way to get a real one running today. But if the interface changes, or you're using a different tool entirely, you still know what you're looking for.

Step by Step: Build Your First Scheduled Agent

Start with something narrow enough to trust quickly, not your whole job. A five-minute task you already do every week is the right size for a first one.

In Claude
  1. Pick one narrow, recurring job, "every Monday, summarize the update doc into three bullets," not "help me manage my team."
  2. Open Claude and look for Tasks (or start a chat and describe what you want scheduled, Claude will offer to set it up).
  3. Write the instructions the way you'd brief a new hire: what to check, what to produce, and the exact format you want it in.
  4. Set the schedule, the day, the time, and how often it should repeat.
  5. Let it run once, then read the output like a first draft from a new hire, not a finished product.
  6. Fix what's off by editing the instructions, not by manually correcting the output every time it runs.
In ChatGPT
  1. Pick the same kind of narrow, recurring task, small enough that a bad first run costs you nothing.
  2. Open ChatGPT and go to Tasks (or ask it directly: "schedule a task that checks X every Monday and does Y").
  3. Describe the job, the source material it should check, and the output format you want.
  4. Set the schedule. ChatGPT will message you when each scheduled run completes.
  5. Review the first few runs closely before you trust it to just sit in the background.
  6. Fold anything you had to fix by hand back into the instructions, so the next run doesn't repeat the mistake.
Agent Brief Template

Fill this out before you write a single instruction. If you can't fill in all six lines, the job isn't defined clearly enough to hand off yet, to an agent or to a person.

Goal: What should exist after this runs that doesn't exist now?

Source material: Where does it check, and what exactly does it read?

Output format: Bullets, a table, a short paragraph, sent where?

Schedule: How often, and at what time?

What to flag for me: What's important enough that it shouldn't wait for the next run?

What not to do: Any boundary it should never cross on its own (send externally, delete anything, make a commitment on your behalf).

Start Narrow

Don't hand an agent your whole job on day one, the same way you wouldn't hand a new hire your whole job in week one. Start with one recurring task small enough that a bad first run costs you nothing to notice and fix. Expand what it's trusted with only after it's gotten the small thing right for a few weeks straight.

Fun fact: the failure mode with agents almost never looks like disaster, it looks like drift. A vague instruction doesn't break loudly, it just quietly produces slightly-wrong output every week until you happen to notice. Check the first few runs closely, that's when the vague spots in your instructions actually show up.

Where to Go From Here

Once you've got one scheduled agent running reliably for a couple of weeks, your next move depends on what you're actually running into. There are two real directions, plus one thing you already have.

Need it to run on a schedule instead of by hand?
That's this page, the "Step by Step" section above. You're already here.
Want it really good at one specific job?
Narrow it further rather than broadening it, one job, one input shape, one output format. Build Your First AI Assistant and Your First Agent, One Example All the Way Through are both worked examples of a specialist doing exactly one thing well.
Hitting a ceiling one agent can't get past on its own?
That's the moment to connect a second, narrower agent instead of making this one do more. See Connecting Multiple AI Agents Together for the handoff pattern.
AI Hub · Go Further
Connecting Multiple AI Agents Together →
AI Hub · Advanced
Your First Agent, One Example All the Way Through →
AI Hub · Step 8
AI Isn't the Problem. What You Do With the Time Back Is. →