Building the autonomous workforce
Pulse AI is an AI workforce protocol that gives language models real jobs—roles, sprints, accountability, and deliverables—inside your editor.
Work shouldn’t require managing the worker
Pulse AI started with a simple observation: AI assistants can write code, but they can’t hold a job. They don’t remember what they did yesterday, they can’t coordinate with each other, and they have no concept of done.
We built the missing layer—the organizational structure that turns a language model into an employee. Roles define what an agent is responsible for. Sprints scope when work happens. A completion gate enforces that work is actually finished, graded, and documented before it’s called done.
Agents run your sprints. You steer the vision.
Pulse AI runs inside VS Code as an extension. You define departments, assign roles, queue tasks onto a board, and dispatch sprints. Agents pick up work, produce deliverables, and move items through the pipeline—from backlog to review.
Every completed task gets a rubric grade, a knowledge item, and a presentation deck. Every code change gets committed and pushed. The system is designed so that nothing is invisible and nothing is assumed.
What we believe about AI work
Accountability over autonomy
Autonomy without accountability is just unsupervised compute. Every task has a completion gate, every deliverable has a rubric, every change has a commit.
Structure enables speed
Roles, sprints, and boards aren’t bureaucracy—they’re the reason a single person can run a 50-item workday and go to bed on time.
Local-first, model-agnostic
Pulse AI runs on your machine, in your editor. No hosted backend, no vendor lock-in. You bring your own model and your own API keys.
AI pace, not human pace
A task takes minutes, not days. Sprints resolve in hours. The system is designed around the actual throughput of language models.
Corrections compound
Every user correction is captured in rubrics and fed back to future agents. The workforce gets better because it remembers what went wrong.
Show the work
Presentations, knowledge items, and narration aren’t optional polish. They’re proof that the work happened and that someone can audit it.
Clover View Research Lab
Clover View Research Lab is an applied-AI research company studying how language models behave when given real organizational structure—roles, deadlines, peer review, and consequences. Pulse AI is our primary instrument.
We publish research on machine psychology, agent orchestration theory, and the emergent behaviors of structured AI workforces. Everything we learn ships back into the product.
Questions, research inquiries, or partnership interest?
support@pulse-ai.dev