Plenar
Continuous project planning for the agentic age.
Work plans go stale within days, because work changes faster than teams can update them. AI coding agents widened the gap: an agent ships code in minutes, while replanning by hand takes days.
Plenar computes a work plan in seconds. Its engine assigns work and builds the schedule from skills, availability, dependencies, and deadlines. As agents and engineers work, updates from pull requests, deploys, and completed tasks feed back, and the plan recomputes automatically. Over time, Plenar learns how long work actually takes and sharpens future estimates.
The result is a plan that stays in sync with execution — and a clear answer to what will ship and when.
What makes Plenar different
Every constraint, weighed together. Plenar optimizes the goals that compete — meeting target dates, matching the right skills, balancing workload across the team, finishing committed milestones — while respecting the limits that can’t bend: dependencies, availability, capacity, and which work is Must vs Nice. It balances all of them as one, not one rule after another.
A New Plan preview on every schedule-affecting change. Edit an estimate, reassign a task, add a dependency, or move a target date, and Plenar shows the diff first — which tasks move, which goals slip, which target dates are still safe. Add three days to one task and the projected ship date might move Jun 18 → Jun 25 — the slip compounds as Plenar re-fits the rest of the plan around it, across dependencies, capacity, and competing priorities — and a goal that was On Track drops to At Risk, all before anything is saved.
An agentic planning interface. Tell your agent what needs to ship and it structures the tasks, dependencies, and skills. For estimates it pulls comparable past work and your team’s calibration data from Plenar, so its numbers are grounded in how long similar work actually took — not guesses. Plenar handles assignments, the timeline, and ETAs, and connects to Claude Code so you plan from your editor.
A plan that learns. As work happens, execution signals feed back in real time — tasks started and finished, blockers, merged pull requests, deploys — and the plan recomputes to match. Over time, Plenar calibrates estimates from how long work actually takes, so the plan grows more accurate the longer you use it. See How the plan learns.
Deadline feasibility. Plenar projects when work will be done given current scope and capacity, so you know whether a goal will hit its target date before you commit to it.
Get started
Pick the path that matches where you are:
- Explore the sample project — every new organization comes with a worked example. Best if you’re new to Plenar.
- Create your project — build one for what you’re shipping, from the dashboard or by describing it to your agent. Best when you’re ready to start.
- Connect Claude Code — manage your plan from the terminal. Best if you have a project and want the agentic workflow.
- How scheduling works — the model behind the plan, for when you want to see how Plenar builds it.