AI teammates that do the busywork
Set up agents with one job each — the standup, delivery risk, new-task triage. They run on a schedule or when work changes, show their reasoning, and wait for you before they change anything that matters.
- Loaded workspace6 projects · 41 open items
- Looking at search items3 similar checkout bugs · 1 shipped fix last week
- Looking at workspace membersRavi has 4 open items on Storefront, Ana has 11
- Proposed an updatePriority and owner for NWD-214
Reported to Priya's Inbox · 6 credits · run #1,284
Each agent has one job.
Start from a ready-made agent or a blank one. Everything stays editable — name, instructions, tools, projects and who hears about it.
Standup writer
Reads what moved since yesterday and what is planned today, then posts the standup to your Inbox — blockers first.
Delivery watchdog
Checks delivery confidence and blockers every morning and reports only the projects that are at risk or got worse.
Triage agent
Sets a sensible priority on new tasks and suggests an owner with capacity. You approve each change.
Client update drafter
Drafts the weekly client update in client-safe language — no internal codes or names — saved as a note for review.
You decide when, and how far.
Decide when each agent runs, and how far it may go without a person in the loop.
When it runs
- On demand
- Press Run now, or pick the agent on the Agent page and talk to it directly under its own rules.
- On a schedule
- Daily, every weekday, or one day a week — at a time you choose, in your own timezone.
- When work changes
- A task is created, assigned, changes status or priority, or becomes overdue — scoped to the projects you pick.
How far it goes
- 01
Read-only — Analyzes and reports.
Write capabilities are never offered to the agent, even if they are on its list.
- 02
Ask before writes — Proposes, you decide.
Every change it suggests waits in its run history and your Inbox until a person approves or rejects it.
- 03
Auto-run safe writes — Small changes, applied for you.
On scheduled and event runs it may create or update tasks and notes on its own. Projects, sprints, meetings and milestones still wait for approval — and a run you start by hand never auto-applies.
It looks before it acts.
Not a one-shot command router: the agent checks the facts, then answers or proposes — and shows every step.
- 01
Read the workspace
It starts from a live snapshot of your projects, open work and this week's meetings — never a stale export.
- 02
Look things up
When the answer depends on facts it doesn't have yet, it runs a lookup, reads the result and decides again — up to 3 times.
- 03
Answer or propose
It replies with the answer and the tasks, projects and meetings behind it — or proposes a change for you to approve.
- 04
Show its work
Every step appears live while it works, and stays on the answer as “Worked through N steps” you can open later.
Answers you can act on.
Ask on the Agent page and the answer comes back structured — with the real items behind it.
Cards, not walls of text
Projects arrive as health cards with progress, tasks as a checklist with due dates and reasons, meetings as an agenda.
Grounded answers
Each answer says what it was based on — “2 blockers · 1 project” — and every card opens the real item.
The next question, ready
Follow-ups name the actual task or project — “Why is KR-9 stuck?” — one tap to ask. They cost no credits.
Talk to a specific agent
Switch the Agent page to any dedicated agent and its instructions, tools and limits apply to the conversation.
Your permissions, never more.
Built so you can let an agent run overnight and still pass a security review.
Your permissions, never more
An agent acts as the person who set it up — or whoever pressed Run now — and can't see or change anything they can't.
A tool list per agent
Give each agent only the capabilities its job needs. Anything outside the list is refused, even if the model asks for it.
Approvals in one place
Proposed changes wait in the agent's run history with Approve and Reject — and arrive in the Inbox of the person they act as.
No runaway loops
Changes an agent makes never wake other agents, and each event-driven agent runs at most 30 times an hour.
Stops when its owner leaves
If the person an agent runs as leaves the workspace, the agent switches itself off instead of acting on their behalf.
Every run on the record
Each run keeps its trigger, its steps, what it found or changed, and the credits it used. Client guests never see agents.
Prefer to work from Claude, Cursor or ChatGPT? Connect them through the MCP server. More on governance in AI agents & MCP and Security.
Common questions.
What is a dedicated agent?
A named AI teammate with one job — writing the standup, watching delivery risk, triaging new tasks. You give it instructions, the tools it may use, the projects it covers and how much it may do alone, then run it by hand, on a schedule, or when tasks change.
Can an agent change my work without asking?
Only if you choose “Auto-run safe writes”, and only on scheduled and event runs: it may then create or update tasks and notes by itself. Creating projects, sprints, meetings or milestones always waits for approval, and so does any change from a run you started by hand. Read-only agents never write at all.
Whose permissions does an agent use?
Scheduled and event runs act as the person who set the agent up; a manual run acts as whoever pressed Run now. Either way it can only reach what that person can reach. If the owner leaves the workspace, the agent switches itself off.
Who can create agents?
Workspace owners and admins set agents up. Every team member can see them, run them and talk to them. Client guests can't see agents at all.
Where do agent results go?
To the Inbox of the people you choose, as agent reports — plus the agent's own run history, where pending changes are approved or rejected. Agent reports are in-app by default and can be switched off in notification settings.
Does it use AI credits?
Yes — each run uses the workspace's AI credits like any other agent question, and every run shows what it cost. If credits run out, the run stops and the agent's owner is notified. Follow-up suggestions are free.
How is this different from Workflows?
Workflows follow fixed rules you draw: when X happens, do Y. An agent reads the situation and decides — it can look things up, reason over what it finds and explain itself. Both listen to the same task events.
How is this different from the MCP server?
The MCP server lets an AI tool you already use — Claude, Cursor, ChatGPT — work over Worksynk. Dedicated agents live inside Worksynk and run on their own schedule and triggers, with approvals built in.
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