Sharkly product development workflow

Product development workflow with Sharkly

A person first describes the problem and desired outcome in natural language. An Agent then researches the product and codebase, refines the requirement, and creates tasks. Agents develop in parallel and test the result for human acceptance, while projects and sprints provide the team-wide view of overall progress.

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Complete development workflow

Let Agents execute while the team keeps control of progress and decisions

Sharkly brings a person's natural-language request, Agent research, tasks, automatic development, project progress, and acceptance into one work system. Agents do not just answer questions. They refine work from the current state, move it forward, and return every result to the team.

01Describe and research

A person describes the need in natural language, then an Agent researches and refines the tasks

A person first explains the problem, desired outcome, and initial idea in natural language. The Agent then reads the existing product, codebase, historical tasks, and team rules, completes the scope and acceptance criteria, and creates executable tasks.

  • Describe the goal, problem, and initial idea in natural language
  • Let the Agent research product, code, and historical context
  • Complete scope and acceptance criteria, then create tasks
02Automatic parallel development

Let Agents develop automatically with multiple tasks moving in parallel

Once tasks are ready, Agents claim them automatically and work in isolated worktrees. Frontend, backend, bug fixing, and test coverage can move at the same time without overwriting one another.

  • Start execution automatically when work is ready
  • Run multiple Agents in isolated worktrees
  • Return progress, blockers, and changes to each task
03Test and human acceptance

Let the Agent test the result and hand it to people for acceptance

The Agent runs typecheck, tests, and the production build, then attaches the change summary, verification results, and known limits. A person accepts the delivery, requests changes, or decides the next merge and release step.

  • Return tests, builds, and evidence with the delivery
  • Keep known limits and unfinished work visible
  • Leave final acceptance and release decisions to people
04Projects and sprints

Use projects and sprints to manage scope, progress, and blockers

The team places tasks into projects and sprints to follow completion, ownership, dependencies, scope changes, and blockers. Agent execution becomes part of the team plan instead of disappearing into private terminals.

  • Organize scope through projects and sprints
  • Track progress, dependencies, and blockers continuously
  • Give people and Agents the same work view

Team capability system

Turn one good setup into a development capability the team can reuse

Team leverage does not come from opening more AI chats. It comes from sharing roles, rules, context, and workflows. Sharkly turns the Agent and process one teammate configured into a capability the whole team can use.

Reusable team Agents

Create stable Agents for product research, frontend development, testing, bug fixing, and other roles instead of starting from zero each time.

Shared Skills and context

Give Agents the same coding standards, task templates, test requirements, and domain knowledge across different tasks.

Standardized workflows

Define how work is researched, created, executed, reported, and delivered so progress stays trackable and outputs stay comparable.

Automation for recurring work

Trigger Agents for requirement research, task creation, bug triage, status sync, and scheduled checks without repeated reminders.

Agents research, execute, test, and report. People set direction, grant authority, and accept the result.

Sharkly does not treat completion as an automatic merge or deployment. Automation stops where team judgment is required and returns a delivery with complete context and inspectable evidence.

Getting started

Let Agents begin with one real requirement

Connect a Machine and repository, configure team Agents, then give one requirement to the research Agent and watch tasks move through execution, tracking, and acceptance.

01

Connect a Machine and repository

Connect a local or cloud Machine and make its Runtime available so Agents can read product context, code, and repository rules.

02

Configure Agents, Skills, and execution rules

Define the roles of research, development, and test Agents, plus task creation, verification, and reporting behavior.

03

Submit one requirement for research

Let the Agent research the current state and create tasks, then follow automatic development and human acceptance through projects and sprints.

FAQ

About the Sharkly product development workflow

What information can an Agent research before creating tasks?

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Teams can let an Agent read existing product documentation, the codebase, related historical tasks, discussion records, team Skills, and repository rules. The exact context is configured for each Agent role.

Which tasks will the Agent create automatically?

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The Agent uses the refined goals, scope, and acceptance criteria to create accountable and trackable execution tasks. Teams can keep a human confirmation step before automatic development begins.

How do parallel Agents avoid overwriting one another?

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Each development task can run in an isolated worktree so code changes from different tasks remain separate. The team still resolves real product or code conflicts during the final merge when needed.

How do projects and sprints reflect Agent execution?

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Agent task status, ownership, progress, blockers, and review results appear in the same project and sprint views the team uses, without manually reconstructing updates from private terminals.

Will an Agent merge or deploy automatically after testing?

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Not by default. The Agent returns inspectable code changes, a summary, and verification evidence. A person decides whether to accept the work, request changes, or continue with a merge and release.

Does Sharkly replace the AI coding tools the team already uses?

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No. Sharkly manages Agents, tasks, and team context in one workflow. Teams can connect their existing AI coding tools, Runtimes, and subscriptions instead of replacing them.