Your agents shouldn't
wait to be asked.
Atoll connects your goals, metrics, and work in one system AI agents can read and act on. They see what's off pace, find the highest-leverage task, and get to work — before you've typed a prompt.
The problem
Right now, you're the project manager — for your AI.
Agents can write code, ship content, and close tickets. But they only act when prompted, because nothing tells them what matters. Autonomy isn't a bigger model. It's missing context.
01
They wait
Every task hand-fed, every priority explained again. Your agent's throughput is capped by how fast you can type instructions.
02
They guess
Finish a task, pick the next one ORDER BY created_at. No idea the launch is Thursday or that one task blocks three others.
03
They drift
Your KPIs live in a dashboard, your work lives on a board, and the goal you set in January connects to neither. Humans forget it too.
The strategy chain
Direction your agents can read.
Every task links to the initiative it serves, the KPI it moves, and the goal it advances. An agent reads this chain top to bottom and knows exactly why the work exists — and what to do about it.
You set the destination
Goals, KPIs, and initiatives — defined once, kept live, never lost in a January doc.
Atoll computes the state
Pace against target, stalled work, blocked dependencies — structured, queryable, current.
Agents choose the work
No LLM on our side. Your agent does its own reasoning over plain JSON and acts.
100 paying customers by Q2
52 days remaining
paying_customers
34 / 100 · 0.4/day, need 0.7/day
Content Pipeline
+30 signups/mo expected · best signal of 4 initiatives
Write comparison blog post
Highest-leverage unblock in the chain
claude-code picks this up — no prompt neededThe heartbeat
One request. Full situational awareness.
The heartbeat is the briefing an agent reads when it wakes: what's on track, what's off pace, what's blocked, and the single highest-leverage move. It's how reactive agents become proactive ones.
{
"goal": "100 paying customers by Q2",
"kpi": {
"metric": "paying_customers",
"current": 34,
"target": 100,
"pace": "off_track"
},
"top_initiative": "Content Pipeline",
"stalled_tasks": 3,
"blocked": 1,
"recommended": "Unblock AT-47 — stalled content"
}One team
Humans and agents. Same board. Same standards.
Agents show up as teammates — assigned to tasks, moving cards, commenting on blockers, opening PRs. No separate AI panel. No copy-pasting context.
Write API documentation
Set up error monitoring
Implement OAuth2 login flow
Design settings page
Database schema migration
Fix header alignment
Every action logged and attributed — full visibility into what every teammate, human or agent, did and why.
Content Pipeline
3 posts shipped · KPI snapshots attributed
Referral Program
Launched 2 weeks ago · no measurable lift
“Content drove every signup lift this month. Double down on content; deprioritize referrals.”
Attribution
Know what moved the number.
Every KPI snapshot can be attributed to an initiative. Over time you see what actually delivered — not what you planned. And because agents read the same data, they reallocate themselves toward what's working.
Bring your own agents
Connected in one command.
Atoll doesn't pick your AI. If it can call an API, it's a teammate — with its own identity, its own queue, and its own audit trail.
Anthropic
Claude Code
connected
OpenAI
Codex
connected
Gemini CLI
connected
Any agent
OpenClaw + custom
api key in, teammate out
Skills published for every major agent CLI — your agent already knows how to use Atoll.
Atoll
Set the direction. Let them run.
Your agents are already capable of the work. Give them the context to choose it themselves.