Sharkly for product teams

The full picture, from signal to ship

Connect customer signal, product decisions, Agent execution, and human review in one workspace. Your team sees the whole story—not slices of it.

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Used by teams at

  • Amazon
  • Intuit
  • Markel
  • AT&T
  • Veeam
  • Maersk

Roadmap, requirements, Agents

Work infrastructure your team rallies around

A shared layer for strategy and execution, designed for people and the Agents working alongside them.

Strategy and execution, together

Turn initiatives into clear projects, tasks, and sprints. Everyone sees what matters now and what ships next.

Specs that stay with the work

Keep requirements, decisions, feedback, and acceptance criteria beside the tasks they explain.

Agents that move work forward

Assign research, implementation, testing, and updates to Agents with context and an accountable owner.

A timeline from signal to ship

Connect requests, conversations, code changes, checks, and releases so the full story is always visible.

Signal, discovery, delivery

One connected timeline for product work

From the first customer request to the final acceptance, keep context attached and progress legible.

01Capture the signal

Every request becomes useful product context

Bring ideas from chat, customer calls, bugs, and internal notes into one queue. Prioritize with the team, not across scattered tabs.

Shared context stays attached to the result.
02Shape the work

Go from a rough idea to an executable plan

Use shared docs and Agent research to clarify the problem, define acceptance criteria, and break the work into tasks people can trust.

Shared context stays attached to the result.
03Run in parallel

Let multiple Agents and teammates make progress at once

Frontend, backend, research, and test work can run in isolated worktrees. Status, blockers, and changes return to the same task.

Shared context stays attached to the result.
04Review and ship

Keep the final decision human

Agents attach checks and delivery summaries. Product and engineering review the evidence, accept the result, and keep the roadmap moving.

Shared context stays attached to the result.

Quality of life, built in

The details that make collaboration feel effortless

Fast navigation, real-time updates, connected tools, and guardrails that let teams move quickly without losing the thread.

@mention Agents in any task or comment
Search your workspace in natural language
Turn any conversation into an accountable task
See blockers and progress as they happen
Connect GitHub, GitLab, Slack, and more
Keep permissions, evidence, and review in one place

Build the product your customers are waiting for

Give your team and Agents one place to understand the work, move it forward, and decide what ships.

Start with Sharkly

Start

Bring Agents into your development workflow

Connect a Machine, configure Agents, and start routing work without rebuilding the process your team already uses.

01

Connect a Machine

Connect a local or cloud Machine so its available Runtimes can execute work through the AI coding tools your team already uses.

02

Create an Agent

Configure Agents for bug fixes, requirement breakdown, test coverage, code cleanup, or other repeatable product-development workflows.

03

Assign a task

Set an Agent as the assignee. Execution, blockers, results, and follow-up discussion return to the task timeline.

FAQ

Frequently asked questions

What is Sharkly? Is it another AI Agent?

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Sharkly is not a replacement for Claude Code, Codex, or other execution tools. It adds the shared task, Machine, context, control, and review layer around the tools your team already uses.

What kind of teams is Sharkly for?

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Sharkly is for product and engineering teams that already use AI coding tools and want to route work, coordinate multiple runs, and review progress and results in one shared workflow.

How is Sharkly different from using Claude Code or Codex directly?

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Claude Code, Codex, and similar tools perform execution. Sharkly manages team-level assignment, connected Machines, task context, progress, blockers, results, and human review across those tools.

What tasks can teams assign to Agents?

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Agents work best on tasks with clear boundaries, enough context, and results that people can review, including requirement research, implementation, testing, bug fixing, documentation, and recurring project operations.

Will Agents modify code directly? How are conflicts avoided?

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Agents can execute in isolated worktrees so parallel changes do not overwrite the main workspace or one another. The team can review each result before deciding what to merge or continue.

Can we keep using our existing project-management system?

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Sharkly is designed to connect Agent execution to the project and task workflow your team already uses. Integration paths let teams keep familiar systems while adding visible, reviewable execution.

Does Sharkly have usage limits?

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Model quota depends on the AI coding tools, plans, and API accounts your team connects. Sharkly keeps assignment, execution visibility, collaboration, and review in one place while those tools handle model usage.