Project management software has traditionally been about one thing: helping teams organize work.

Create a task. Assign it to someone. Add a deadline. Track the status. Move it across a board. Repeat.

That workflow still works, but AI is changing what happens after a task is created.

AI coding agents can now write code, fix bugs, add tests, investigate issues, and work across repositories. That creates a new question for engineering teams:

Should an AI agent just help manage the work, or should it actually become part of the team doing the work?

This is where the comparison between Sharkly and Asana gets interesting.

Asana is a mature work management platform built around projects, tasks, goals, workflows, reporting, and collaboration. Sharkly takes a similar project-management foundation but builds AI agents directly into the execution workflow.

So, Sharkly.ai vs Asana: which one should you choose?

It depends on how your team works.

Sharkly.AI vs Asana: Quick Comparison

The table makes the products look similar.

The important difference appears when a task leaves the planning stage and needs to be executed.

What Is Asana?

Asana is one of the better-known work management platforms for teams.

It gives organizations a central place to manage projects, tasks, deadlines, dependencies, goals, forms, reporting, automation, and team workloads.

Asana also supports multiple ways to visualize work, including list, board, calendar, timeline, and Gantt views. More advanced plans add features such as portfolios, resource management, goals, reporting, and additional workflow capabilities.

For teams managing marketing campaigns, product launches, operations, HR processes, or cross-functional projects, that broad approach makes sense.

Asana has also moved heavily into AI.

Its current AI offering includes AI Teammates, Asana Dash, AI Studio, AI-assisted project work, and integrations that allow external AI tools to interact with Asana's Work Graph.

So this isn't a comparison between an AI product and a non-AI product.

Both platforms are moving toward AI-powered work management.

The difference is how deeply AI is connected to execution.

What Is Sharkly.AI?

Sharkly is a work management platform designed around teams that include both humans and AI agents.

It provides the familiar building blocks you'd expect from a project management system:

• Tasks
• Projects
• Backlogs
• Sprints
• Boards
• Lists
• Dashboards
• Gantt views
• Comments
• Custom fields
• Team collaboration

But Sharkly adds another type of assignee.

An AI Agent can become the execution owner of a task.

Instead of simply writing:

Fix the authentication bug.

and assigning it to a developer, a team can assign that ticket to an Agent.

The Agent can then execute the work through connected coding tools, while progress, blockers, and results return to the same task for review.

That creates a different workflow:

Task → Agent → Execution → Review

rather than simply:

Task → Human → Execution

And that distinction is the main reason an engineering team might consider Sharkly instead of a traditional work management platform.

Sharkly vs Asana: Where They Differ

1. Traditional project management

If you're looking strictly at project management, there isn't an enormous gap between the two.

Both platforms can help teams organize projects and tasks, assign responsibility, monitor progress, and visualize work.

Asana has a particularly mature set of project management features.

Its Starter plan, for example, includes Timeline and Gantt views, reporting dashboards, custom fields, forms, automations, templates, and other tools for managing structured projects.

Sharkly also provides boards, lists, tables, dashboards, Gantt views, Projects, Issues, and Sprints.

If your team simply wants a powerful system for organizing human work, Asana is already very capable.

Winner: Asana

For traditional project and work management, Asana's maturity and breadth give it an advantage.

2. AI agents as teammates

This is where the comparison becomes more interesting.

Asana has AI Teammates that can be assigned work and help teams automate tasks and workflows. Asana describes its AI as a way to automate work, provide insights, summarize information, and work alongside teams inside the platform.

Sharkly takes a different approach.

Agents are built directly into the task execution model.

An Agent can be configured with instructions, Skills, and a Runtime, then assigned to a real task. Once assigned, comments, blockers, progress, and results can stay connected to that task.

For a software engineering team, this is important.

The Agent isn't just helping you decide what should happen next.

It can actually be responsible for executing the task.

Winner: Sharkly

For teams specifically looking to put AI agents into the execution loop, Sharkly has a more focused approach.

3. AI coding workflows

Imagine your team has this ticket:

Add automated tests for the payment API.

With a conventional project management workflow, the ticket gets assigned to a developer.

The developer opens their development environment, reads the ticket, checks the repository, writes the tests, runs them, and submits the changes.

With an AI-native workflow, an Agent can take the execution role.

Sharkly supports Agents running through coding tools such as Claude Code, Codex, and Gemini CLI, with Computers and Runtimes providing the execution environment.

The work can happen in an isolated worktree, while the task remains the place where the team can see progress and review the result.

That creates a much tighter connection between project management and software execution.

Asana can certainly integrate with developer tools and its AI capabilities can participate in workflows, but software development execution isn't the central model of the platform.

For engineering teams that already use AI coding agents, this distinction matters.

Winner: Sharkly

4. Human review still matters

One concern with AI agents is giving an AI too much freedom.

Nobody wants an agent making changes to production without oversight.

Sharkly's workflow is designed around keeping the human in the loop.

The Agent works on the assigned task, while its progress and results return to the task for review before the work is merged.

This is a useful middle ground.

The goal isn't:

Let AI do everything.

It's:

Let AI do more of the execution while humans remain responsible for reviewing the outcome.

That model makes more sense for engineering teams that want to increase development capacity without completely removing human oversight.

What About Asana's AI?

It would be misleading to describe Asana as a traditional project management tool that simply added a chatbot.

Asana has made AI a significant part of its platform.

Its current AI features include AI Teammates, Asana Dash, AI Studio, AI-assisted workflows, and integrations with external AI systems.

Asana AI can help with things such as:

• Automating repetitive work
• Summarizing projects
• Drafting updates
• Analyzing information
• Assigning work to AI Teammates
• Building AI-powered workflows

Starting in September 2026, Asana's advanced AI capabilities include AI Teammates and Asana Dash for eligible organizations, with AI usage managed through an AI Request system.

So the real comparison isn't:

Asana has AI vs Sharkly has AI.

It's:

Where does the AI sit in the workflow?

Asana is expanding AI inside an established work management platform.

Sharkly is building the work management platform around a world where AI agents can be assigned real work.

That is a subtle but important difference.

5. Switching From Asana to Sharkly

One of the biggest reasons teams hesitate to change project management platforms is migration.

Nobody wants to rebuild years of projects and task history.

This is where Sharkly's Asana compatibility becomes particularly useful.

Sharkly supports importing Asana projects, tasks, and history. It also supports two-way synchronization so teams can run the systems alongside each other while they transition.

That means a team doesn't necessarily have to make a massive switch overnight.

A practical approach could look like this:

Step 1: Import an existing project

Bring one existing Asana project into Sharkly.

Step 2: Keep the existing workflow

The team can continue using familiar project and task structures rather than starting from scratch.

Step 3: Introduce an Agent

Choose one repetitive engineering task, such as bug fixes, test coverage, or documentation.

Step 4: Assign the task to an Agent

Let the Agent execute the task while the developer reviews the result.

Step 5: Expand gradually

If the workflow works, gradually move more engineering work into Sharkly.

This is arguably more realistic than asking an entire organization to abandon its existing project management system in one afternoon.

6. Sharkly vs Asana Pricing

Pricing is another important consideration.

Sharkly currently offers its full product free for organizations with up to 10 people.

Its Team plan is $7 per user per month when billed annually for organizations above that limit. Agents, Crews, Computers, and Runtimes do not occupy seats. Sharkly also uses a bring-your-own-model-usage approach, meaning model usage runs through the coding plans or API accounts connected to the Runtime.

Asana's current paid plans start at $10.99 per user per month when billed annually for Starter. Advanced is $24.99 per user per month billed annually. Asana's paid plans include AI capabilities, while AI usage can also be governed through its AI Request system.

That makes the pricing models quite different.

For a small team experimenting with AI-powered development, Sharkly's free allowance can make it easier to test the platform without immediately committing to another per-user subscription.

For larger organizations, the choice becomes more dependent on the team's existing workflows, required enterprise features, and how much value they expect from AI-powered execution.

7. Who Should Use Asana?

Asana is still an excellent choice for many teams.

You should probably consider Asana if your main goal is managing projects across different departments.

It is particularly well suited to teams such as:

• Marketing
• Operations
• HR
• Product
• Sales
• Customer success
• Cross-functional business teams

Asana's broad collection of project management, reporting, automation, goals, and resource-management features makes it useful when the main challenge is coordinating people and processes.

If your team isn't looking for AI agents to execute technical work, there may be little reason to move away from a platform you already understand.

8. Who Should Use Sharkly?

Sharkly becomes more interesting when software development is a major part of the workflow.

It is worth considering if your team:

• Uses AI coding tools regularly
• Wants AI agents assigned directly to tickets
• Manages multiple AI coding agents
• Wants AI to execute repetitive engineering tasks
• Wants development progress connected to the original task
• Wants humans to review AI-generated work
• Is experimenting with AI-native development workflows
• Wants to introduce agents without completely abandoning project management

The biggest question isn't whether your team uses AI.

Most modern teams are beginning to.

The better question is:

What do you want the AI to actually do?

If the answer is "help me manage my work," Asana may be enough.

If the answer is "take a ticket, execute the engineering work, and bring the result back for review," Sharkly is built much closer to that use case.

Sharkly vs Asana: Final Verdict

There isn't a universal winner.

Asana is a mature, flexible work management platform with strong project planning, automation, reporting, collaboration, and increasingly sophisticated AI capabilities.

Sharkly takes a narrower but potentially more significant direction.

It treats AI agents as participants in the work itself.

That's the key distinction.

For a marketing team planning campaigns, an operations team coordinating processes, or a company managing complex cross-functional projects, Asana remains a very strong option.

For an engineering team asking:

"What if our AI coding agents could be assigned tickets just like developers?"

Sharkly is a much more interesting proposition.

The shift is subtle but important.

Traditional project management asks:

Who is responsible for this task?

AI-native project management asks:

Who — human or agent — should execute this task, and how do we review the result?

That may be where project management software is heading next.

And for teams already building with AI agents, it may make sense to start making that transition now.

Frequently Asked Questions

Is Sharkly an alternative to Asana?

Yes. Sharkly can serve as a project and work management platform, with tasks, Projects, Sprints, Views, comments, and other planning features. Its main difference is that AI Agents can also be assigned to execute work.

Does Sharkly work with Asana?

Yes. Sharkly supports importing Asana projects, tasks, and history, as well as two-way synchronization during migration.

Does Asana have AI agents?

Yes. Asana currently offers AI Teammates and AI Studio as part of its broader AI-powered work management platform.

Can Sharkly AI agents write code?

Yes. Sharkly Agents can run through connected coding tools and execute development work from assigned tasks. Sharkly currently lists support for tools including Claude Code, Codex, and Gemini CLI.

Is Sharkly free?

Sharkly currently offers its full product free for organizations of up to 10 people. Its Team plan is $7 per user per month when billed annually for larger organizations.

Is Asana better than Sharkly?

It depends on the use case. Asana is particularly strong for general-purpose work management and cross-functional teams. Sharkly is more focused on teams that want AI agents to participate directly in task execution.