But having this information available doesn’t necessarily mean Confluence employee training is effective for everyone.

For L&D and Training Managers, the challenge often isn’t creating more content. It’s turning existing knowledge into structured employee training that people can follow, complete, and understand.

The good news? If your organization already uses Confluence, you can leverage Confluence employee training instead of starting from scratch.

Why Confluence employee training needs more than a knowledge base

A Confluence knowledge base is designed to make information accessible. Employees can search for answers, explore documentation, and collaborate on shared knowledge.

Training, however, requires a different approach.

Imagine a new employee joining your company. You share five Confluence pages, a product demonstration, two internal policies, and a few videos.

Everything they need is technically there. But:

• Where should they start?
• Which materials should they complete first?
• How can you confirm they’ve reviewed the required content?
• How do you know whether they understood it?
• How can you monitor their progress?

This is where knowledge management and learning management differ.

A knowledge base helps employees find information when they need it. A learning program guides employees through specific content to achieve defined learning objectives.

For L&D teams, the opportunity is to connect both. The six steps below answer each of these questions, using the content you already have.

Step 1: Identify existing Confluence content for employee training

Before creating new training materials, review what’s already available.

Start with content that employees frequently need during onboarding, role-specific training, or ongoing professional development. For example:

The objective is to identify existing, maintained resources that can become part of a learning experience.

Step 2: Organize your content into a learning structure

Once you’ve selected your materials, organize them into a clear learning sequence.

Rather than sharing a collection of unrelated links, group content into logical topics. For example, a new employee training course could include:

1. Section 1: Welcome to the company
   • Company introduction
   • Mission, values, and team structure
2. Section 2: How we work
   • Internal communication guidelines
   • Tools and workflows
   • Employee policies
3. Section 3: Your role
   • Team-specific procedures
   • Product or service documentation
   • Knowledge assessment

Alternatively, you can organize the same content into separate courses and bring them together in a Learning Path.

For example, a New Employee Onboarding Learning Path could include:

1. Course 1: Welcome to the Company
   • Company introduction
   • Mission, values, and team structure
2. Course 2: How We Work
   • Internal communication guidelines
   • Tools and workflows
   • Employee policies
3. Course 3: Your Role
   • Team-specific procedures
   • Product or service documentation
   • Knowledge assessment

This structure gives learners a clear starting point and helps them understand what comes next.

With Smart Courses for Confluence, you can organize content into courses, sections, and individual learning components. You can include existing Confluence pages alongside videos, documents, text, and quizzes, instead of rebuilding your entire knowledge base inside a separate training platform. Your pages stay in Confluence, where your teams already maintain them.

To ensure learners review important content, you can set a minimum reading time on a component so they can’t skip ahead in seconds.

Step 3: Create learning paths

Not every learning objective can be covered in a single course.

New hires might need company orientation, security awareness, product knowledge, and role-specific training. Experienced employees might need advanced product training or periodic refresher courses.

This is where Learning Paths become useful. Instead of assigning each course separately, you can create a learning journey that brings related courses together. For example, a new employee Learning Path could include:

1. Company introduction
2. Internal tools and processes
3. Security awareness
4. Product knowledge
5. Role-specific training

Smart Courses supports Learning Paths that combine multiple courses and exams, with optional linear progression.

This allows training managers to guide employees through the right material in an appropriate order, without requiring them to figure out what to learn next.

Step 4: Assign training to the right employees

Making training available is one thing. Ensuring the right employees receive it is another.

Some courses may be relevant to everyone, while others are required only for specific teams.

With Smart Courses, training managers can assign courses to individual users or groups, set due dates, add a message, and send reminders. For example:

• HR assigns onboarding training to new hires.
• IT assigns security awareness courses to relevant employees.
• Support managers assign product knowledge training to support teams.
• Department leads assign updated process training to their teams.

For recurring needs like onboarding, continuous assignments keep training assigned as your teams change, so new team members get the right courses without a manager setting it up each time.

This makes the training process easier to coordinate, especially as teams grow and training requirements become more diverse.

Step 5: Check understanding with quizzes and assessments

Opening a document doesn’t necessarily mean someone understood it.

For L&D teams, assessments help determine whether learners have understood important information and can apply what they’ve learned.
Smart Courses supports seven question types: single choice, multiple choices, freetext, matching, ordering, fill in the blank, and essay. This lets you test recall, reasoning, and written understanding within the same course.

For example, after completing a product knowledge section, employees could answer questions about common features, customer use cases, or troubleshooting procedures.
In exam mode, you can set a minimum pass score, limit the number of exam attempts, choose whether learners see their results, and issue certificates when learners meet the required completion criteria.

This connects training content with measurable learning outcomes rather than relying entirely on page views or self-reported completion.

Step 6: Track employee training progress

Once training is assigned, managers need visibility into participation and completion.

Without dedicated learning management functionality, this often involves manually following up with employees or maintaining separate tracking spreadsheets.

Smart Courses provides Insights dashboards that help training managers monitor learning activity and results. Depending on the dashboard, managers can review course completion, learner status, assessment results, and related training data. They can also export reports for further analysis.

This helps answer questions such as:

• Who has completed their assigned training?
• Which learners are still in progress?
• Who has overdue assignments?
• Which courses may require attention?

Instead of chasing updates across different channels, L&D teams have a clearer view of training progress.

How Atlassian’s Teamwork Collection fits into employee training

Structured learning works best when it stays connected to the knowledge and daily workflows employees already use.

Atlassian’s Teamwork Collection brings together Confluence, Jira, Loom, and Rovo to connect documentation, work, video communication, and knowledge discovery. Each can support a different part of employee learning:

• Confluence: Maintain the documentation, policies, and resources employees need to learn.
• Loom: Record walkthroughs and explanations that make complex procedures easier to follow.
• Jira: Connect learning-related tasks and follow-up activities to everyday workflows.
• Rovo: Help employees discover relevant knowledge and find answers across connected resources.

Smart Courses adds a dedicated learning layer within Confluence, letting organizations organize content into training programs, assign learning, assess understanding, and track progress.

Smart Courses runs inside Confluence, so your training is built directly on your Confluence content. Jira, Loom, and Rovo complement Smart Courses: they don’t integrate directly, but they strengthen the environment where you create, find, and put your training content into practice.

From knowledge sharing to employee learning

Your Confluence knowledge base is already an investment in your organization’s knowledge. Turning that information into structured training helps you get more value from it.

You can start with a single course, such as employee onboarding or product knowledge training, using content your team has already created. Then, as your learning needs grow, you can add assessments, assignments, Learning Paths, and progress tracking.

You don’t need to recreate your knowledge. You need a better way to help employees learn from it.

With Smart Courses for Confluence, you can build a learning experience around the knowledge your organization already maintains.

Try Smart Courses for Confluence on the Atlassian Marketplace or book a demo

FAQ

Can I use existing Confluence pages in a course?
Yes. Smart Courses lets you add existing Confluence pages to a course alongside videos, documents, text, and quizzes, so you don’t rebuild content in a separate platform.

What is the difference between a course and a Learning Path?
A course groups content into sections on one topic. A Learning Path combines several courses and exams into one journey, with optional linear progression.

What question types does Smart Courses support?
Seven: single choice, multiple choices, freetext, matching, ordering, fill in the blank, and essay.

Can I issue certificates in Confluence?
Yes. Smart Courses can issue certificates when learners meet the completion criteria, such as reaching the minimum pass score of an exam.

How do I track who completed their training?
Insights dashboards show course completion, learner status, and assessment results, and you can export reports for further analysis.

Can Confluence be used for employee training and learning management?
Yes. Confluence can serve as a central knowledge base for employee training. With Smart Courses for Confluence, you can turn existing documentation into structured courses, create Learning Paths, assign training to employees or groups, assess their understanding through quizzes and exams, issue certificates, and track learning progress through Insights dashboards.

That means all four Creativas apps are now developed on Atlassian’s cloud app platform:

• Smart Courses for Confluence: LMS, employee training, onboarding, quizzes and compliance
• Smart Terms: glossary and terminology management for Confluence and Jira
• Smart Tables for Confluence: table filtering, reporting, charts, formulas, calculations and SQL views
• Smart Images for Confluence: image editing, image maps, sliders and galleries

Getting here took years of work.

Moving established apps with real customers, data, workflows and years of functionality wasn’t simply about changing the technology underneath them. We had to rebuild some parts, redesign others, and work around limitations as Forge itself continued to evolve.

Now all four apps share the same Forge foundation.

And for us, that’s where the interesting part starts.

Why did we move our Atlassian apps to Forge?

Forge is now Atlassian’s preferred platform for building Cloud apps. Since September 17, 2025, only Forge apps can be submitted as new apps to the Atlassian Marketplace, and Atlassian says it’s delivering new extensibility features on Forge. Read Atlassian’s Forge documentation for Confluence.

Atlassian Connect is also approaching end of support on January 31, 2027.

So we couldn’t ignore moving to Forge.

But we didn’t want to treat it as a deadline or a box to check.

Forge is also where Atlassian is investing in capabilities that can shape the next generation of Cloud apps: AI, Rovo extensions, Forge LLMs, Teamwork Graph and deeper connections across the Atlassian platform.

We wanted our apps to be ready for that future.

What is Atlassian Forge?

Atlassian Forge is the development platform for building apps that extend Jira, Confluence and other Atlassian Cloud products.

With Forge, Atlassian manages core areas of the platform such as infrastructure, compute and hosted storage, while app developers build the functionality customers interact with. Forge is Atlassian’s preferred cloud app development platform.

For Creativas, that gives us a common foundation across our products while keeping our apps closer to the Atlassian ecosystem they are designed for.

What does moving to Forge mean for our customers?

The biggest change isn’t something customers need to learn.

It’s what Forge allows us to build behind the scenes.

• Closer alignment with Atlassian Cloud: Our apps can evolve alongside the platform they extend instead of depending on a legacy framework.
• Access to new Atlassian capabilities. Forge gives us more opportunities to work with capabilities such as Rovo Agents, Forge LLMs and Teamwork Graph.
• A stronger foundation for AI. Forge LLMs allow Forge apps to call Atlassian-hosted large language models, giving developers a platform-native way to build AI functionality.
• Atlassian-managed infrastructure. Forge provides Atlassian-managed infrastructure and hosted storage, including data residency support for persistent Forge-hosted storage. Learn about Forge data residency.
• One foundation across our portfolio. Smart Courses, Smart Terms, Smart Tables and Smart Images can now evolve on the same Atlassian development platform rather than following separate technical paths.

And some of those benefits are already visible in the products.

Smart Courses: Building a Confluence LMS on Forge

Smart Courses for Confluence was the final piece of our Forge journey.

Smart Courses turns Confluence into a learning management system where teams can create and deliver employee training, onboarding programs, compliance courses, quizzes, exams, certifications and SCORM-based learning experiences.

Rebuilding an app with that much functionality on Forge required far more than moving a few components.

Courses, assignments, learner data, Insights and the workflows customers already rely on had to remain part of the experience while the app moved to its new foundation.

That work is now complete.

Smart Courses is on Forge, and that also gives us a better foundation for the next capabilities we want to bring into learning in Confluence, including more AI-assisted experiences and deeper connections with the Atlassian platform.

For teams looking for a Confluence LMS, employee training in Confluence, Confluence onboarding, or compliance training with SCORM, the technology underneath Smart Courses is now ready for where Atlassian Cloud is going next.

Smart Terms: A Forge-powered glossary for Confluence and Jira

With Smart Terms, teams can build and manage an enterprise glossary, define terminology, connect related vocabulary and automatically highlight terms across Confluence and Jira content.

Forge has already started changing what we can add to that experience.

We launched Lexi, our AI Glossary Assistant, to help teams analyze their Confluence knowledge, identify relevant terminology and create glossary content faster.

We’re also using Atlassian Forge LLMs for AI-assisted term translations, bringing AI into the terminology workflow using Atlassian-hosted models.

For organizations managing acronyms, technical terminology, product language or company-specific vocabulary, Smart Terms provides a Confluence glossary and terminology layer directly inside the Atlassian workspace.

And this is a good example of why our Forge migration matters: the benefit isn’t the migration itself. It’s what we can build because of it.

Smart Tables: Table filtering, reporting and AI queries in Confluence

Confluence tables often start simple. Then the data grows.

Teams need advanced filters, calculations, charts, pivot tables, grouping, reporting and different ways to understand the same data.

That’s where Smart Tables for Confluence comes in.

Smart Tables extends native Confluence tables with table filtering, charts, pivots, Excel-like calculations and additional reporting capabilities. Its SQL Views also let teams query their table data and create more specific views without duplicating the source table.

Forge is also opening new ways to simplify those workflows.

With AI Query, users can describe the result they need and generate the SQL query instead of having to write it manually.

For someone searching for a Confluence table filter, Confluence reporting app, pivot tables for Confluence, or SQL queries in Confluence, Smart Tables now combines those established capabilities with a Forge foundation we can continue building on.

Smart Images: Image editing and visual content inside Confluence

Not every Forge benefit needs to involve AI.

Smart Images for Confluence is our visual toolkit for teams that want to do more with images without constantly moving between Confluence and external editing tools.

Teams can edit and annotate images, create interactive image maps, and display visual content through sliders and galleries directly in Confluence.

Smart Images is also fully Forge-developed, giving it the same foundation as the rest of our Cloud portfolio.

For teams searching for a Confluence image editor, image map for Confluence, Confluence image gallery, or image slider, those workflows can stay where the documentation itself lives.

Forge, security and trust

Security was also an important part of why moving toward Forge made sense for us.

Forge provides Atlassian-managed infrastructure alongside built-in platform security controls. Atlassian documents security for Forge through a shared responsibility model, where Atlassian manages parts of the underlying platform while Marketplace Partners remain responsible for the security decisions and functionality within their apps. Read Atlassian’s Forge security guidance and shared responsibility model.

That doesn’t mean Forge removes our responsibility as a Marketplace Partner.

It means we’re building on an infrastructure designed specifically for Atlassian Cloud apps while continuing to take responsibility for how our apps are built, maintained and secured.

Forge also provides data residency support for persistent Forge-hosted storage.

For qualifying Forge apps, Atlassian also offers Runs on Atlassian, a trust designation with requirements around Atlassian-hosted compute and storage, data residency and external data egress controls.

Today, Smart Terms, Smart Tables and Smart Images carry the Runs on Atlassian badge on the Atlassian Marketplace.

All four apps are Forge-developed; Runs on Atlassian is a separate eligibility and trust designation.

Forge isn’t the finish line

Over the last few years, we did a lot of behind-the-scenes work to get our portfolio here.

There were limitations to work around, functionality to rebuild, architecture to rethink, and a platform that was evolving while we were building on it.

But the objective was never simply to say: “Our apps are on Forge.”

The objective was to make sure Smart Courses, Smart Terms, Smart Tables and Smart Images are ready for what comes next.

We’re already seeing that with Lexi, Forge LLM-powered translations and AI-generated SQL queries.

Next, we’ll continue looking at where capabilities such as AI, Rovo, Teamwork Graph and other Forge improvements can solve real problems across our apps.

Not because every feature needs AI, not because every new Atlassian capability needs to become a feature. But because when something can genuinely make training easier, terminology clearer, data easier to understand or Confluence content better to work with, our apps are now in the right place to build it.

Filtering, sorting, grouping, and pivot tables can handle a lot. But when you need more specific views, combined conditions, or custom summaries, SQL gives you another way to work with the same data.

With Smart Tables for Confluence, you can convert your native Confluence tables into Smart Tables and create SQL Views directly from them. And if you don’t know SQL, AI Mode can generate the query for you.

Let’s see how it works.

Can you use SQL with a native Confluence table?

Not directly.

Native Confluence tables are great for organizing information, documenting processes, or keeping lightweight trackers inside a page.

But a native table doesn’t provide an SQL editor where you can run something like:

SELECT Task, Team, Owner, Priority, Status, Due Date
FROM T1
WHERE Priority = 'High'
AND Status = 'Open'
AND Due Date <= CURRENT_DATE + INTERVAL 14 DAY
ORDER BY Due Date ASC;

Smart Tables adds that layer.

Instead of rebuilding the data elsewhere, you can convert your existing native Confluence table into a Smart Table and keep working with the information already on your page.

From there, you can use familiar Smart Tables features such as filters, sorting, grouping, formulas, pivot tables, and charts or create an SQL View when the question gets more specific.

So, let’s start from the beginning.

Step 1: Start with your Confluence table

Imagine you’re managing a project tracker in Confluence with columns such as:

• Task
• Team
• Owner
• Priority
• Status
• Due Date
• Budget

For normal day-to-day work, this table might be perfectly manageable. You can read through the rows, update statuses, and use Confluence as the shared place where the team keeps the latest information.

However, the problem arises when different people need different answers from the same SQL table. A Project Manager may want to see only open high-priority work. A team lead may want to know which team has the most open tasks. Finance may only care about budget totals. You could create separate tables for each need.

But now you have multiple versions of the same data to maintain. Instead, let’s keep one source table and query it.

Step 2: Convert your native Confluence table to a Smart Table

If your data is inserted inside a Smart Table macro, you can skip this step.

If you’re starting with a native Confluence table, you don’t need to recreate it manually.

Open the Smart Tables menu from the page header and select Convert to Smart Table.

The Table converter will show the tables available on the page. Select the one you want to convert and save your changes.

Your existing Confluence table is now a Smart Table, which means you can work with the same data while adding more advanced table features.

This is an important part of the workflow: you’re enhancing the table you already have rather than starting again somewhere else.

Step 3: Create your first SQL View

Now open your Smart Table from the Confluence page viewer.

From the + View menu, select SQL table. A new SQL table is created from your Smart Table data, and its edit mode opens automatically. One detail you’ll need to know before writing anything:

Your source Smart Table is referenced in SQL as:

So instead of querying the table by its page title or Smart Table name, your query uses FROM T1. Let’s try a simple example. Suppose we want to see every high-priority task that is still open:

Click Run Query. The result appears directly below the SQL editor.

Instead of changing the source Smart Table, you’ve created a focused view answering one particular question. As the source data changes, the SQL table stays connected.

Step 4: Understand what the query is actually doing

If you’re not very familiar with SQL, the query above can look more intimidating than it really is.
SELECT decides which columns you want to see. FROM T1 tells Smart Tables which source data you’re querying. WHERE defines the conditions the rows must meet. AND lets you combine more than one condition. ORDER BY decides how the final results should be arranged.

So this:

WHERE `Priority` = 'High'
AND `Status` = 'Open'

simply means:

Only show rows where the task is both high priority and open.

That’s where SQL becomes particularly useful. Instead of manually combining several filters every time you need an answer, you can define the exact conditions in one query and keep the result as its own view.

One more thing to remember: Smart Tables references column names using backticks in SQL queries.

For example:

`Due Date`

or:

`Daily Budget ($)`

Step 5: Go beyond filtering and summarize your Confluence table

SQL isn’t only another way to filter rows.

You can also use it to summarize the information inside your Smart Table.

Let’s say you want to know how many high-priority open tasks each team currently has.

Instead of returning every individual task, you can ask SQL to count them:

Now your detailed project tracker becomes a simple summary showing the number of open, high-priority tasks per team.

You can use the same approach to answer other questions, such as identifying which team has the most tasks assigned or comparing workloads across teams.

For example, to count the total number of tasks assigned to each team:

This gives you a breakdown of tasks by team, ordered from the highest to the lowest.

Your original Smart Table remains unchanged. You’re simply creating another view of the same data.

Step 6: Don’t know SQL? Use AI Mode

This is the part that makes SQL Views useful beyond technical teams. You don’t necessarily need to write the query yourself. From the SQL table toolbar, switch from SQL to AI Mode. Instead of writing code, describe the result you’re looking for in plain language. For example:

“Count all open high-priority tasks by team and show the teams with the highest number first.”

Run the request. Smart Tables generates the SQL query based on your table and your instructions. The SQL editor then opens automatically so you can see both the generated query and its result. That means AI Mode doesn’t completely hide the SQL. You can review what was generated, use it as-is, or adjust it if needed. It can also be a good way to learn.

Ask for something in plain language, review the SQL it produces, change the request, and see how the query changes.
If you don’t see AI Mode, the AI Engine is controlled from Confluence administration → Apps → Smart Tables configuration. A Confluence administrator can manage the setting from there.
And as with any AI-generated output, review the query and its results before relying on it for important reporting.

Step 7: Create different views without creating different source tables

Your main Smart Table can remain the source of truth while different SQL Views answer different questions.

Instead of duplicating the source table for every reporting need, create multiple SQL Views from the same underlying data. When the source data changes, those views stay connected.

And because SQL is another Smart Tables view type, it can sit alongside your Table, Pivot Table, and Chart views instead of moving reporting into another tool.

A few details that will save you time

Create and edit SQL tables from the page viewer: SQL tables are created from the Confluence page viewer, and inline editing lets you adjust your SQL View directly without going back to the regular Confluence page editor.

Use T1 for your source data: If your query can’t find the table, make sure you’re referencing the Smart Table as T1.

Check AI Engine settings if AI Mode is missing: The setting is managed by a Confluence administrator under the Smart Tables configuration.

Review AI-generated queries: AI Mode helps you create a starting point quickly, but your wording and table structure affect what it generates.

Save your Smart Table changes: When you’re finished creating or adjusting the SQL table, use the Smart Table Save button so the changes are stored for page viewers.

There is also one behavior worth remembering when duplicating content: SQL tables aren’t copied automatically when a Confluence page is copied, so they need to be added again on the copied page.

From a Confluence table to an answer

A table doesn’t become less useful as it grows.

Usually, people just start asking more complicated questions.

Native Confluence tables give teams a simple place to structure and share information. Smart Tables add more ways to work with that information through filters, formulas, grouping, pivot tables, charts, and now SQL.

When a normal filter answers the question, use the filter.

When you need to combine conditions, calculate totals, group results, or build reusable reporting views from the same source data, create an SQL View.

And when you know the question but not the SQL, describe what you need in AI Mode and let Smart Tables create the first query for you.

What happens to everything we’ve already built?

Your courses, assignments, learner data, Insights, and the workflows your teams already rely on all had to remain part of the experience.

The migration took several months of work, with one priority throughout: bring Smart Courses to Forge while preserving the features and workflows you are already familiar with.

But we didn’t stop at rebuilding what was already there.

Along the way, we also introduced improvements and new capabilities to make training easier to assign, track, and manage.

Smart Courses is now built on Atlassian Forge, with new capabilities to assign Learning Paths, understand learner status, and customize the information you see across course listings and Insights.

Let’s go through what’s new in this Cloud version of Smart Courses LMS.

Smart Courses is now on Atlassian Forge

Smart Courses for Confluence is now built on Atlassian Forge.

For most users, this change happens behind the scenes. The Smart Courses experience remains familiar, but the app is now built on the platform Atlassian is using for the future of its cloud ecosystem.

Why does this matter?

Moving to Forge keeps Smart Courses closely aligned with Atlassian’s platform and gives us a stronger foundation for future development.

As Confluence and the wider Atlassian ecosystem continue to evolve, Smart Courses can evolve alongside them, giving us more opportunities to introduce deeper integrations and new capabilities over time.

Most importantly, the move to Forge was designed around continuity. You can continue working with the training content and workflows you already know while benefiting from a version of Smart Courses built for Atlassian’s latest cloud platform.

Assign Learning Paths

Learning Paths already let you combine up to 10 courses and exams into one structured learning journey.

Now, you can assign an entire Learning Path to Confluence users and groups.

Instead of managing training course by course, you can assign the complete journey learners are expected to follow.

This can be especially useful for structured programs such as employee onboarding, compliance training, role-based training, or professional development.

Why did we add it?

This was actually one of the first feature requests we received after launching Learning Paths.

Creating a Learning Path makes it easier to organize related training, but customers also needed a simple way to assign that complete path to learners.

Now, instead of assigning each course separately or asking learners to find the right Learning Path themselves, you can assign the full path from the start.

See learner status directly in Course Insights

Course Insights help you understand how learners are progressing.

This release makes that information easier to scan by adding learner status directly to Course Insights.

You can now quickly see where each learner stands without relying only on progress percentages, completion dates, or other indicators.

Why does this matter?

Checking individual learner progress may be manageable with a small group. As the number of learners grows, it becomes much harder.

Having a clear status directly in the Course Insights makes it easier to identify who has completed their training, who is still progressing, and who may require follow-up.

Instead of interpreting several pieces of data, you get a faster overview of where everyone stands.

Customize your lists

Not every team needs to see the same information.

An HR manager tracking onboarding may care about different data than someone managing compliance training, internal certification, or another training program.

You can now choose which columns to display and then drag and drop them into the order that works for you.

Column customization is available in both the course catalog Listing view and Insights dashboards.

Why did we add it?

As more information becomes available in Smart Courses, listings and Insights can quickly include columns that are useful for one workflow but less relevant to another.

Now, you can adapt the view to what you are working on.

Keep the information you use most visible, hide columns you don’t need, and drag and drop columns to arrange them in the order that makes the most sense for your team.

External Links

There is one more change to be aware of if your courses use externally hosted content.

With the new Forge version, media, embedded websites, and SCORM content that load resources from external domains are subject to Forge egress controls.

In simple terms, Smart Courses can load content only from approved external domains.

We’ve already included some of the external links commonly used by Smart Courses customers, so media components using these services can continue to work without additional configuration:

• Google Drive
• SharePoint
• YouTube
• Loom
• Vimeo

If your media (video or audio) comes from one of these supported sources, you usually don’t need to do anything.

What if your content comes from another website?

You have two options, depending on the type of content you are using.

Option 1: Upload the file as an attachment

For media such as images, videos, or audio files, you can export the file and upload it directly to Smart Courses as an attachment.

Option 2: Add the external domain in Smart Courses configuration

If the content must remain externally hosted, a Smart Courses admin or Confluence admin with site administration permissions can add the required domain in the Smart Courses global configuration.

Once the domain is added, Smart Courses can load supported content from that external source directly inside the course.

This applies to externally hosted:

• Video and audio components
• HTML and web page components
• SCORM packages that load content or resources from external links

More improvements in this release

Alongside the bigger updates, we’ve made a few more improvements to Smart Courses:

• Cleaner filters: A new filter UI in both the course catalog and Insights keeps the interface less cluttered while making it easier to find what you need.
• Easy access to copied courses: When you copy a course, you can now retrieve the link to the new course directly from the confirmation modal.
• Refreshed design: Smart Courses has been updated to better align with Atlassian’s latest design system, creating a more consistent experience across Confluence.

Try Smart Courses for Confluence free

Confluence provides a central place for HR policy documentation, while Marketplace apps can add approval workflows, terminology management, and employee training.

Effective policy management goes beyond storing documents. It creates a clear process for keeping policies accurate, approved, accessible, understood, and up to date.

What is policy management in Confluence?

Policy management in Confluence is the process of creating, organizing, reviewing, approving, publishing, and maintaining company policies in one central environment.

An HR policy hub might contain an employee handbook, code of conduct, remote work and leave policies, security and data protection policies, benefits documentation, expense policies, and compliance procedures.

The difference between simply storing policies and managing them is control. HR teams should be able to identify a policy’s current version, owner, approver, and review schedule.

A clear process turns a collection of Confluence pages into a reliable policy management system.

Why HR policies become difficult to manage

As organizations grow, policies can become scattered across different tools, outdated, or difficult to track. Employees may not know which version is current, while ownership, review dates, and approvals become harder to follow.

Without a clear process, policies can remain outdated or be approved without a reliable record. A structured policy management process helps keep them current, accountable, and easier to manage.

How to manage HR policies in Confluence

A scalable system does not need to be complicated. It needs a clear structure, visible ownership, and a repeatable lifecycle.

Create a central HR Policy Center

Start by giving employees one place for official policies.

Organize policies into clear categories such as Employee Policies, Security & Compliance, Benefits, and Training.

The goal is simple: employees should know where to find the latest approved information without searching across multiple spaces, files, or tools.

Use a consistent policy template

A standard structure makes policies easier to create and maintain.

Each policy can include essential information such as the policy owner, status, effective date, last review date, next review date, scope, responsibilities, and related documentation.

Using the same structure across policies also makes missing or outdated information easier to spot.

Assign clear ownership

Every important policy should have someone responsible for maintaining it.

Review frequency will vary by policy, but ownership should always be clear.

Define the policy lifecycle

Policies should not follow a simple:

Create → Publish → Forget

A more reliable process is:

This gives HR teams a repeatable process for managing policies throughout their lifecycle rather than reacting only when something becomes outdated.

Add approvals to your Confluence policy workflow

Some policies require formal review before they become official.

A data protection policy, for example, may need input from HR, Legal, IT, or senior management.

Confluence provides the documentation foundation, while Marketplace apps can add structured approval workflows, approval status tracking, decision history, and audit trails.

The process could look like this:

HR drafts the policy → Legal reviews it → Management approves it → The approved version is published → Employees access the current policy

This creates a clearer record of how a policy moved from draft to approved documentation and reduces uncertainty around which version employees should follow.

Make HR policies easier to understand

Making a policy available does not automatically make it easy to understand.

HR documentation often includes abbreviations, legal terminology, technical language, and company-specific concepts that may not be clear to every employee.

With Smart Terms for Confluence, HR teams can build a shared glossary directly inside Confluence and make definitions available in context as employees read policies.

A glossary could include terms such as PTO, PII, EAP, probation period, confidential information, or internal role classifications. Teams can also add related vocabulary, including acronyms, synonyms, and plurals, to keep terminology consistent across policies.

For organizations working across regions, Smart Terms supports multilingual glossaries, allowing teams to maintain terms and definitions in multiple languages.

Teams can also use Lexi, the Glossary AI assistant in Smart Terms, to scan Confluence content or uploaded documents and identify terminology worth defining. Lexi can draft definitions based on the surrounding content and translate suggested terms into enabled glossary languages.

Instead of asking employees to search elsewhere for an unfamiliar term, HR teams can add explanations directly in the policy while keeping one shared source for key company terminology.

Connect HR policies with employee training

Some policies need more than publication. Employees may need to understand the content, complete required training, and demonstrate that they know what is expected.

This is especially important for onboarding, information security, workplace conduct, data protection, and compliance.

With Smart Courses for Confluence, HR teams can turn policy documentation into structured learning without moving employees to a separate LMS.

For example, a new-hire learning path could combine courses on the Code of Conduct, Information Security, Data Protection, Remote Work, and Workplace Safety. Learning Paths can group related courses and exams into a defined training journey, while prerequisites and skills can control what employees need to complete or demonstrate before progressing.

HR teams can add quizzes and exams to check understanding, assign training with due dates, and issue certificates when required learning is completed. Course insights also help HR teams track progress and completion, rather than assuming that opening a policy means it was understood.

For recurring compliance requirements, courses can be scheduled to repeat so employees revisit required training when necessary.

The process becomes:

Policy published → Training assigned → Learning completed → Knowledge checked → Completion or certification tracked

By connecting policies with structured learning, HR teams can move beyond simply publishing information and create a clearer way to support onboarding, compliance, and ongoing employee training directly in Confluence.

Turn policy updates into employee learning

The connection between policies and training becomes especially important when a policy changes.

If your company updates its data protection policy, publishing the new version may not be enough. The change may also require approval, employee communication, updated training, and a knowledge check.

Update policy → Review and approve → Publish → Notify employees → Update training → Check understanding

This connects policy updates directly to employee learning instead of assuming employees will notice and understand a changed page.

The compliance content stays specialized. The learning experience lives in Confluence.

Try Smart Courses for Confluence free for 30 days.

Most organizations solve the first problem with specialized compliance courseware. But for teams already working in Confluence, training can still sit in a separate system from the policies, procedures, and documentation employees use every day.

Smart Courses lets you bring compatible, appropriately licensed BAI/ProSight compliance courseware into Confluence through SCORM, connecting specialized training with the workspace employees already use.

What is BAI compliance training?

BAI compliance training is now offered under the ProSight brand. BAI and the Risk Management Association (RMA) merged in 2024 to form ProSight Financial Association.

ProSight provides compliance courseware designed specifically for banks, credit unions, mortgage organizations, and other financial institutions.

Its training covers areas such as BSA and anti-money laundering, UDAAP, GLBA, cybersecurity, identity theft, lending regulations, deposit and transaction regulations, and corporate compliance.

Courses are built around financial-services roles and can include practical scenarios, interactive activities, and assessments. That specialized content is one reason organizations may prefer licensing established compliance training instead of recreating regulatory courses internally.

The challenge is not only the content

Good courseware solves the content problem. Employees still need an easy way to access and complete it.

For teams working across the Atlassian ecosystem, much of the supporting knowledge may already live in Confluence: internal policies, security procedures, risk-management documentation, department resources, and compliance guidance.

Putting training closer to that knowledge creates a clearer connection between the policy employees are expected to follow and the training they need to complete.

Instead of reading a policy in Confluence and then searching for the related course in another system, employees can access both from the same workspace.

Can BAI/ProSight courses run in another LMS?

Yes. ProSight licenses its programs for use in other learning management systems through its Content Provider Service, subject to the applicable agreement and approved LMS configuration.

Through its Content Provider Service, ProSight can provide licensed programs for use through a client’s approved learning management system.

An important distinction exists between ProSight/BAI-owned courseware and custom content your organization creates.

• ProSight/BAI courseware: You cannot assume you can freely export, copy, or reuse licensed ProSight/BAI training in another LMS. Whether you can deliver a course through an external LMS depends on your licensing agreement with ProSight and the delivery options they provide. Confirm the applicable permissions and SCORM availability with ProSight before requesting or importing course files.
• Custom content created by your organization: If you create and design your own training content within the platform, that content is separate from ProSight’s proprietary course catalog. Where the platform provides SCORM export for that custom content, you can export the resulting SCORM package and use it in a compatible LMS, subject to your organization’s rights to the content and the platform’s applicable terms.

In other words, licensed ProSight courseware and your own custom-created training should not be treated as having the same export rights.

Before planning the integration, confirm with ProSight that your agreement supports external-LMS delivery and that the course is available in a format compatible with SCORM 1.2 or SCORM 2004.

Once you have a compatible SCORM package that you are authorized to use in your LMS, Smart Courses can deliver it inside Confluence.

From ProSight courseware to training in Confluence

Start by selecting the ProSight courses that match your regulatory requirements and employee roles. Training for frontline employees, mortgage teams, managers, or compliance officers may differ, so match the right courseware to the right audience.

Once you select the courses, confirm with ProSight that your license and delivery arrangement support external-LMS use, and request the compatible course files or delivery method available for your account.

In Smart Courses, create a new course, enable the SCORM course option, open the course editor, and upload the compatible SCORM ZIP package you are authorized to use and have obtained through your ProSight licensing or delivery arrangement.

Smart Courses supports both SCORM 1.2 and SCORM 2004, so you can import compatible courseware without recreating the original training as Confluence pages.

Once published, you can assign the course to individual users or Confluence groups with a due date.

For recurring compliance requirements, group-based assignment can also help automate enrollment as employees join the relevant groups.

Administrators can then use Course Insights to follow learner progress, completion status, scores, and due dates.

Connect compliance training with your Confluence policies

This is where the combination becomes particularly useful.

Smart Courses provides a Course Card macro that can surface an individual published course on a Confluence page. The Course List macro can display a filtered collection of courses based on criteria such as categories, labels, or spaces.

Imagine an employee opening a Mandatory Banking Compliance Training page in Confluence.

At the top, the compliance team explains the program and provides links to internal policies. Below that, employees can find the relevant BSA/AML, cybersecurity, lending, identity-theft, or transaction-compliance courses available through Smart Courses.

The same page can also contain training deadlines, instructions, and contact information for the compliance team.

Employees move from policy → context → training without having to search across disconnected systems.

Who handles what?

A practical example

Consider a bank already managing its policies and procedures in Confluence.

The compliance team creates a Mandatory Banking Compliance Training page containing its internal compliance guidance and links to the policies employees are expected to understand.

Courses licensed from ProSight are imported into Smart Courses as SCORM packages and assigned by employee role.

Branch employees may receive BSA/AML and identity-theft training, while mortgage teams receive the lending-related courses relevant to their responsibilities.

Course cards and filtered course lists make that training accessible from the compliance area employees already use.

Meanwhile, the compliance team can use Insights to monitor who has completed the required training and where follow-up is still needed.

The result is a closer connection between what employees are expected to know and the training they are expected to complete.

What does Smart Courses track from SCORM?

Smart Courses captures the completion and score information sent by the SCORM package.

For SCORM 1.2, that includes lesson status and raw score. For SCORM 2004, Smart Courses uses completion status, success status, and raw score.

This allows learner results such as completed, incomplete, passed, or failed to appear in Smart Courses depending on the information provided by the package.

One limitation to keep in mind: Smart Courses does not currently capture individual question-level results from an imported SCORM course. It reports the package’s overall status and score.

Therefore, we recommend testing a new SCORM package before assigning it organization-wide to ensure its completion and scoring rules are reported as expected.

You can also enable certificates for SCORM courses when completion requirements are met.

Bring financial compliance training into Confluence

Compliance training works better when employees can easily find it alongside the policies and procedures it supports.

Once you have a compatible SCORM package that your ProSight licensing and delivery arrangement permits you to use in an LMS, upload it to Smart Courses, assign it to the right employees, and make it accessible from the Confluence pages your teams already use.

The compliance content stays specialized. The learning experience lives in Confluence.

Try Smart Courses for Confluence free for 30 days.

Smart Tables for Confluence now supports SQL Views, giving teams a new way to explore large datasets directly inside Confluence.

Write your own SQL query or simply describe what you’re looking for in plain language. AI Mode generates the SQL automatically, creates an adjustable SQL query, and keeps everything connected to the same dataset.

What’s new?

Smart Tables has always helped teams organize information with sorting, grouping, filtering, global search, pivot tables, charts, and formulas. We’ve added a new advanced feature: SQL Views.

Instead of creating multiple filtered tables or repeatedly combining filters and formulas, you can now create adjustable SQL queries that answer more complex questions, all while working from the same table.

If you don’t know SQL, that’s fine. Simply describe the result you want, and AI Mode generates the SQL query for you.

Whether you’re managing project portfolios, sprint backlogs, financial reports, asset inventories, or compliance registers, Smart Tables now lets every team explore data with the level of precision they need.

Why do native Confluence tables eventually reach their limits?

Native Confluence tables are excellent for documentation and lightweight tracking.

Most teams don’t just want to find information anymore; they want to answer questions like:

• Which projects are overdue and over budget?
• Which high-priority risks still don’t have an owner?
• Which assets expire next quarter by department?
• What’s the average completion rate per team?

Smart Tables already solves many of these scenarios through sorting, grouping, filtering, search, pivot tables, charts, or formulas.

SQL Views don’t replace those features. They complement them.

For everyday work, filtering, sorting, or grouping is often the fastest solution.

When datasets become larger, or questions require multiple conditions, aggregations, or advanced reports, SQL Views provide another layer of analysis without leaving Confluence.

Why SQL views?

Many teams already think in queries, even if they’re clicking through filters instead of writing SQL.

SQL Views make those questions easier to answer.

They allow you to:

• Query multiple conditions in a single request.
• Aggregate data using counts, totals, averages, and calculations.
• Create other views without duplicating your tables.
• Generate multiple perspectives from one dataset.
• Save SQL Views for future reporting.

The biggest advantage isn’t writing SQL; it’s avoiding duplicate tables across your page.

One dataset and multiple views

One Smart Table can support multiple teams and use cases without filling your Confluence page with separate macros or duplicate tables.

With Tab Mode, you can display different views of the same Smart Table as tabs within a single macro. Each team can create its own SQL View based on the same source data and switch between views without leaving the table.

For example:

• Project Managers can monitor overdue tasks and project status.
• Finance can focus on budget variances and spending.
• Leadership can review high-level portfolio summaries.
• Engineering can track sprint progress and blockers.
• Operations can review resource allocation.

The source data stays the same. Each team simply gets the view it needs, all organized within one Smart Table.

AI mode makes SQL easy for everyone

SQL isn’t difficult for technical users, but for everyone else, AI Mode eliminates the learning curve.

Instead of writing a query, simply describe the information you’re looking for.

Examples include:

• Show all overdue tasks assigned to Marketing.
• Display projects exceeding their planned budget.
• Count high-severity risks grouped by owner.
• List assets that expire within the next 30 days.

AI Mode translates your request into SQL, automatically creates the SQL View, and lets you review or edit the generated SQL query if you’d like.

Technical users save time, and non-technical users gain capabilities they never had before.

Use case: How to manage Company Risk Register with SQL query?

Imagine a Project Manager Officer (PMO) team managing a company-wide risk register.

For daily work, they use:

• Sorting to prioritize risks by status.
• Grouping to organize risks by team or category.
• Global Search to locate a specific risk by ID or description.
• Filters to review only open, active risks.
• Pivot Tables to summarize risk counts by severity.
• Charts to visualize exposure across teams.

As the register grows, different stakeholders need different perspectives. Rather than maintaining multiple copies of the same table, the team creates SQL Views.

The Finance team creates a view showing every open risk with a cost impact above $20,000:

“Show me all risks where cost_impact_usd is greater than 20000, and status is Open.”

The Project Office creates a view of overdue, still-open risks to make sure they’re caught and acted on quickly.

SELECT `risk_id`, `description`, `owner`, `due_date` FROM `T1` 
WHERE `status` = 'Open' AND `due_date` < CURDATE() ORDER BY `due_date` ASC

Engineering and IT/Ops review a view of unmitigated risks, filtering to anything where mitigation hasn’t started yet, so effort goes where it’s needed first.

SELECT risk_id, description, mitigation_status FROM T1 
WHERE mitigation_status = 'Not Started' AND status = 'Open';

Every SQL View is based on the same Smart Table, ensuring everyone sees the latest information without duplicating or manually maintaining data.

How to use SQL?

If you’re new to Smart Tables, you’ll find the interface intuitive and easy to navigate. Whether you’re starting from scratch or importing an existing Excel file, you can begin organizing and analyzing your data in just a few clicks.

As your dataset grows, use familiar features such as sorting, grouping, global search, filters, formulas, pivot tables, and charts to explore your data from different perspectives.

When you need a more advanced view, simply click + View and select SQL table. From there, you can write your own SQL query or switch to AI Mode and describe the results you want in plain language. Smart Tables generates the SQL query for you and creates an adjustable SQL View alongside your existing Table, Pivot Table, and Chart views.

You can switch between these views at any time without modifying your original dataset, allowing different teams to work from the same data while focusing only on the information that’s relevant to them.

Why does this matter?

Every team works differently, and some questions can be answered with a simple filter.

Others require grouping, a pivot table, or a chart.

And now, as your data grows and your questions become more complex, SQL Views offer another way to explore the same information without exporting data or leaving Confluence.

Instead of choosing among spreadsheets, databases, and Confluence, Smart Tables brings them together into a single view on one page.

Key takeaways

SQL Views expand what teams can do with data in Confluence by adding powerful querying capabilities to the Smart Tables experience. Rather than replacing existing tools like filtering or grouping, they provide more ways to explore larger datasets and answer more complex questions.

• Analyze large Confluence tables more efficiently with SQL queries designed for advanced reporting and data exploration.
• Keep one source of truth by creating multiple SQL Views from the same Smart Table instead of maintaining duplicate tables for different teams.
• Generate SQL queries with AI by describing the data you want in plain language, no SQL expertise required.
• Combine SQL Views with existing Smart Tables features, including formulas, sorting, grouping, global search, pivot tables, and charts.
• Work entirely inside Confluence Cloud, with Smart Tables running natively on Atlassian Forge for a seamless and secure experience.
• Give every team the view they need, whether they’re tracking projects, reviewing budgets, managing assets, or monitoring operational data.

Frequently asked questions

Can you use SQL with Confluence tables?

Native Confluence tables don’t support SQL queries. Smart Tables adds SQL Views, allowing you to query table data directly inside Confluence without exporting it to another tool.

Do I need SQL knowledge to use SQL views?

No! Smart Tables includes AI Mode, which automatically converts plain-language requests into SQL queries. You can use the generated query as-is or edit it after running it.

When should I use SQL views instead of filters or grouping?

Filtering, sorting, grouping, and global search are the quickest way to work with everyday tables. SQL Views are best suited for larger datasets or more advanced reporting scenarios that require multiple conditions, aggregations, or complex queries.

Can different teams create different views from the same table?

Yes! One Smart Table can support multiple SQL Views, allowing project managers, finance teams, executives, and operations teams to work from the same dataset while focusing only on the information relevant to them.

Can I save and reuse SQL queries?

Yes! SQL queries are saved as SQL Views, making it easy to return to the same analysis without rebuilding filters or writing the query again.

Can SQL Views be used alongside Pivot Tables and Charts?

Yes! SQL Views become another view type within Smart Tables and work alongside Table, Pivot Table, and Chart views. You can switch between them at any time while keeping the same underlying dataset.

Does SQL work with imported Excel and CSV data?

Yes. After importing data from XLSX or CSV to Smart Tables, you can query it using SQL Views, build pivot tables, create charts, or continue working with the rest of Smart Tables’ features.

Is Smart Tables built on Atlassian Forge?

Yes! Smart Tables is a Forge-native Confluence app, meaning it runs directly on Atlassian’s cloud platform and integrates with the Confluence experience.

Which teams benefit most from SQL Views?

SQL Views are ideal for any team managing structured data in Confluence, including Project Management Offices (PMOs), Product teams, Engineering, IT Operations, Finance, HR, Compliance, and Operations. They’re particularly valuable when datasets become too large or complex for standard filtering and grouping alone.

With features like Atlassian AI definitions powered by ROVO, employees can select an unfamiliar term, ask for an explanation, and get an answer instantly. Some acronyms are even defined and highlighted automatically, so you don’t always have to look it up. It is fast, convenient, and often surprisingly accurate.

So if AI can explain terms on demand, do organizations still need a glossary?

The short answer is yes.

Because explaining a term and managing organizational terminology are two completely different challenges.

AI helps people understand information in the moment. A glossary ensures everyone across the organization is working with the same definition, the same language, and the same source of truth.

The most effective knowledge management strategy is not choosing between AI and a glossary. It is understanding where each one delivers value.

Where do AI definitions shine?

Imagine a new employee reading a technical document for the first time.

They encounter a term they have never seen before. Instead of opening another tab, searching through documentation, or messaging a colleague, they can simply define that word from a Confluence page using Atlassian AI definitions.

This is where this feature excels.

AI-generated definitions are contextual. They can analyze surrounding content, interpret intent, and provide explanations tailored to the situation. They require little maintenance and can scale across large amounts of information automatically.

For quick clarification, AI is often the fastest solution.

When the question is: “What does this mean right now?” AI is usually the right answer.

Where does AI reach its limits?

The challenge begins when terminology becomes specialized, or when the same word means something different depending on who you ask.

Consider terms like:

• RAID log (Risks, Assumptions, Issues, Dependencies), a staple for any PMO, rarely explained the same way twice
• WSJF (Weighted Shortest Job First), core to SAFe prioritization, and genuinely hard to look up in plain language
• Product Owner, a title that exists natively in Jira, yet means something different on nearly every team that uses it
• CAB (Change Advisory Board), meaningless as three letters unless your org has already defined it
• DORA metrics: deployment frequency, lead time, MTTR, change failure rate, often tracked differently team to team
• RTO / RPO (Recovery Time Objective / Recovery Point Objective), high-stakes compliance terms that are easy to mix up
• Definition of Done (DoD), famously interpreted differently by nearly every Agile team

These aren’t just vocabulary. They’re business-critical concepts, and in several cases, the inconsistency itself is the problem, not just the definition.

Different teams may interpret them differently. Different departments may create competing definitions. Over time, documentation becomes inconsistent, and onboarding becomes harder.

AI can explain these terms, but it cannot guarantee that every employee receives the exact same official definition every time.

AI explanations are probabilistic. They can vary depending on context and available content.
That flexibility is useful for understanding and less useful for governance.

The role of a glossary app

A glossary exists for a different reason. Instead of generating definitions dynamically, it establishes approved definitions that everyone can reference.

When someone asks:

“What is the official meaning of this term in our organization?”

A glossary becomes the authoritative source.

With Smart Terms, organizations can:

• Create and manage glossary entries
• Identify who created a term
• Control who can create and edit definitions
• Standardize terminology across teams, spaces, pages…
• Reuse definitions across multiple spaces
• Maintain a central glossary repository
• Ensure consistent definitions for every employee

AI helps people discover information.

A glossary helps organizations govern it.

A glossary is more than a definition.

One of the biggest misconceptions about glossary tools is that they simply store definitions.

Modern glossary platforms do much more.

A Smart Terms entry can include rich formatting, images, links, related terms, synonyms, acronyms, labels, multilingual definitions, and related vocabulary structures.

This transforms a simple definition into a knowledge object.

Instead of explaining a term, you are building relationships between concepts and creating a navigable knowledge network.

That is something AI-generated explanations do not inherently provide.

Why does highlighting matter more than definitions?

Definitions are only useful if people see them. This is where many AI-based approaches fall short.

Users must actively ask for a definition or trigger an AI interaction. Or, in the Atlassian AI definition case, it selects and decides which terms will be highlighted.

Smart Terms takes a different approach.

Terms are automatically highlighted throughout Confluence and Jira, making knowledge discoverable exactly where people are working. Hovering over a term immediately reveals its definition without interrupting the workflow.

More importantly, highlighting can be controlled.

Organizations can customize:

• Where terms are highlighted
• Which glossaries apply to specific spaces
• Global glossary behavior
• Term visibility
• Highlighting rules

This creates a structured knowledge layer directly inside Confluence rather than relying solely on ad hoc AI interactions.

AI and glossary management work better together.

The future is not AI versus glossary software; it is AI-enhanced glossary management.

That is exactly the direction Smart Terms is taking with Lexi, the new AI assistant for Smart Terms glossary.

Lexi helps organizations accelerate glossary creation while maintaining governance and control.

Instead of manually creating every glossary entry from scratch, teams can use AI to identify terminology, generate definitions, and build glossary content faster based on a space or page content. You can also upload a file, and Lexi will determine all the terms that should be defined.

The difference is that these definitions become managed assets rather than temporary AI responses.

Once created, terms can be edited, approved, enriched, translated, and governed like any other term created with Smart Terms.

Lexi helps create the glossary; Smart Terms advanced configuration helps manage it.

When to use Atlassian AI definitions and when to use Smart Terms Glossary?

Use Atlassian AI definitions when:

• Users need quick contextual explanations
• Information changes frequently
• You want immediate answers with minimal setup
• Understanding is more important than standardization

Use Smart Terms when:

• Definitions must be consistent across teams
• Terminology requires ownership and governance
• You need a central glossary repository
• Compliance and documentation accuracy matter
• You want rich definitions and structured relationships
• You need advanced highlighting and discoverability
• Multiple languages must be supported consistently

The strongest knowledge strategy combines both. AI helps people understand what they are reading, while a glossary ensures everyone is speaking the same language.

Final thoughts

AI has made knowledge more accessible than ever. But accessibility is not the same as consistency.

Features like AI definitions are excellent at helping employees understand unfamiliar concepts in context. They reduce friction and improve productivity.

Yet organizations still need a trusted source of truth for business terminology; that is where Smart Terms continues to deliver value, not because it competes with AI but because it provides the governance, structure, discoverability, and consistency that AI alone was never designed to provide.

And with Lexi bringing AI-powered glossary creation into Smart Terms, organizations no longer have to choose between intelligence and control.

This is the reality for most growing teams, and it’s usually handled with a mix of onboarding docs, Slack messages, and a manager’s best guess about when someone is “ready.” That approach breaks down because knowledge and workload live in two systems that don’t talk to each other: a wiki page doesn’t know how loaded someone’s sprint is, and a sprint board has no idea whether they’ve finished security training yet.

Why do most onboarding programs fall short?

Three failure patterns show up again and again in growing teams:

• Readiness gets measured in time, not knowledge. Three weeks in is treated as a milestone regardless of whether someone has absorbed what they actually need to know.
• Training and delivery are treated as separate phases. Once someone touches their first ticket, onboarding is considered “done,” even if half the learning material is unfinished.
• Capacity is managed informally. “We’ll ease them in” rarely gets written down anywhere a manager or teammate can see it, so it doesn’t survive contact with a real sprint.

Fixing this doesn’t mean replacing Confluence or Jira; it means connecting the tools you already use so learning progress and workload planning inform each other in real time.

Structuring the Learning Path with Smart Courses for Confluence

The first half of a scalable onboarding system is making sure every new hire follows a consistent Learning path, not a scattered mix of pages and informal handovers.

With Smart Courses for Confluence, HR and team leads build a dedicated onboarding Learning Path that sequences everything a new hire needs into the right order: company policy, security training, product knowledge, engineering standards, and role-specific material. Learning Paths let you group multiple courses into a complete program, so a developer, a customer success manager, and a project manager can each follow a tailored track while still sharing common company-wide training.

A few things make this especially effective for onboarding at scale:

Courses can combine Confluence pages, PDFs, images, videos, and even HTML or SCORM packages so whatever format your documentation already lives in, it can become part of the learning journey without being rebuilt from scratch. Since Confluence pages stay connected, any updates your team makes are automatically reflected inside the course, so nobody is ever learning from an outdated version.

Assign courses directly, with due dates. Managers can assign individual courses to specific users or groups, complete with due dates and automatic notifications. This makes it easy to deliver mandatory training exactly when it’s needed: security training before a first login, product knowledge before someone joins their first customer call, instead of hoping people find it on their own.

Skills and quizzes turn learning into evidence. Interactive quizzes at the end of each chapter or course confirm a new hire actually understood the material, not just clicked through it. Combined with prerequisites and skills, onboarding becomes competency-based rather than time-based. Teams may require specific knowledge or a completed quiz to unlock the next stage, so nobody advances on assumption alone.

Insights give managers a real-time view. Built-in insights dashboards show course completion, quiz results, and overall learner progress across every new hire at once. Instead of chasing status updates in a 1:1, a manager can see exactly where each person stands and catch gaps before those gaps affect day-to-day work.

By turning existing Confluence knowledge into structured, trackable training, Smart Courses answers the first key onboarding question: what does this person actually know, and are they ready for the next step?

Managing real workload with ActivityTimeline for Jira

Knowing what someone has learned only solves half the problem. The other half is knowing how much real work they can actually take on right now, and that’s a question learning tools alone can’t answer.

This is where ActivityTimeline for Jira comes in. It’s a resource and capacity-planning app built directly on top of your existing Jira projects, giving everyone, including new hires, a personal timeline showing what’s assigned to them, along with a workload indicator that reflects how loaded they are relative to their real capacity.

A few features make it particularly useful for managing new team members:

See real workload distribution. The workload indicator, color-coded from light green to red, is calculated from both Jira estimates and custom events such as bookings or training blocks. For a new hire, this means a manager can see at a glance whether an “easy onboarding ticket” is actually filling their whole week or leaving them mostly idle, rather than finding out during a retro two sprints later.

Control allocation for new hires. Rather than assigning tasks the same way you would for a tenured engineer, ActivityTimeline lets you set individual involvement (capacity) per person, for example, configuring a new hire at 4–5 hours/day of plannable work for their first two weeks. Booking events lets you reserve time for shadowing, pairing, or training sessions without needing a Jira ticket for each one, so that time shows up on the timeline and counts against capacity instead of disappearing into an invisible gap.

Avoid overloading during ramp-up. Because the workload indicator accounts for vacations, partial days, and custom involvement schedules, it’s much harder to accidentally schedule a new hire for more than they can handle. If a manager tries to stack tickets onto someone whose involvement is intentionally set to a lower level, the indicator visibly tips into yellow or red before the team finds out the hard way.

The result is planning grounded in actual capacity rather than assumptions. A manager isn’t asking “do I think this person is ready”; they’re looking at a timeline that already reflects training time, partial involvement, and current workload, and making a scheduling decision from there.

Bringing both systems together

Handing someone their first real piece of work comes down to two questions: has the relevant part of their learning path actually been completed, and does the timeline show they have the capacity for it right now? Smart Courses answers the first. ActivityTimeline answers the second. Put together, a manager isn’t guessing anymore; they’re looking at evidence of both readiness and availability before making the call.

Customer Success Manager onboarding

The same model works just as well outside engineering teams. Imagine a company hiring five new Customer Success Managers ahead of a major product launch.

Each new hire is enrolled in a Smart Courses LMS Learning Path that covers product knowledge, support workflows, communication guidelines, and internal tools, with quizzes to verify their understanding before they start working directly with customers. Managers track progress through the insights dashboard, just as an engineering manager would.

At the same time, ActivityTimeline helps team leads reserve time for product shadowing, customer call observations, and coaching sessions by reducing each new hire’s available capacity during their first weeks. As training milestones are completed, managers gradually increase their workload so new Customer Success Managers gain confidence without becoming overwhelmed.

Whether you’re onboarding developers or customer-facing teams, combining structured learning with capacity planning creates a repeatable onboarding process that scales as your organization grows.

Try Smart Courses for Confluence free for 30 days.

Try ActivityTimeline for Jira free for 30 days.

Why do native Confluence tables fail as status tracking tools?

Some teams use Page Properties Reports to create portfolio views. Others rely on large native Confluence tables. Both approaches can work, but as the number of projects grows, filtering, sorting, updating, and maintaining multiple stakeholder views becomes increasingly difficult.
On Confluence Cloud specifically, the Page Properties Report exists in a stripped-down form called the Content Properties Report. Macro nesting isn’t supported, which breaks the more advanced configurations that work on the Data Center. Cloud teams are largely left with a plain native table, and the limitations compound fast.
There’s no way to filter by team or RAG status in view mode, no sorting by deadline or priority, and no grouping by phase. The table shows everything to everyone, which, for a portfolio of 15 or more projects, usually means it shows too much to be useful.

All your projects, one table

Smart Tables for Confluence (Table Filter & Charts) approaches the problem differently. Instead of spreading project information across multiple pages and reports, it keeps everything in a single structured table and adds the interactivity needed to manage it effectively.
One row per project, all data in one place, different stakeholders interact with that same data in different ways without creating additional pages, exports, or versions.

Some of these capabilities are available in other Confluence content formats: inline editing in Live Docs and filtering in Databases.

RAG status that you can actually act on

RAG stands for Red, Amber, Green, a simple health indicator that tells stakeholders at a glance whether a project is on track, at risk, or off track and in need of immediate attention. It’s the first thing anyone looks for in a portfolio review, and the first thing that becomes meaningless when a Confluence native table goes stale.
From there, the whole table responds.
Filter to show only Red and Amber projects before a steering committee meeting and sort by RAG status to surface risk at the top.
Group by status to get an instant count of how many projects are on track versus struggling.
The RAG column stops being a label someone remembered to update and becomes a filter you can query.

Grouping and sorting your portfolio view

As portfolios grow, flat lists become difficult to interpret. Grouping reorganizes the same table instantly by owner to understand workload distribution, by phase to see where projects are concentrated, or by priority to surface what needs immediate attention.
The data stays unchanged; only the view does.
Before a portfolio review, sorting delivers the same speed: by deadline to bring upcoming work to the top, by RAG status to lead with risk, or by last updated date to catch stale projects before they become reporting issues.

Inline editing directly on the page

The biggest reason Confluence tables become outdated is friction. If updating a project requires opening the editor, locating the correct row, making the change, and saving the page, the update gets delayed. And delayed updates compound until the table is no longer trusted.
With Smart Tables, updates happen directly in view mode. A project manager changes the status during a standup. A delivery lead updates a phase during progress review. Small updates take seconds, so they actually happen, and the Confluence table stays current.
Jira remains the right home for tracking work items and operational reporting, but project context, stakeholder updates, and strategic notes live in Confluence, and Smart Tables for Confluence (Table Filter & Charts) make that page interactive enough to serve as the portfolio view too, no switching tools required.

Visualize portfolio health

Smart Tables can also generate charts directly inside Confluence from the same project table, no export, no separate reporting tool needed.
A program manager can visualize projects by phase to see where the portfolio is concentrated.

A department head can view workload distribution across teams; an executive can pull up a RAG status breakdown of how many projects are Green, Amber, or Red as a chart alongside the table, ready for a board update. The chart updates automatically as the underlying data changes, so it always reflects the portfolio’s current state.

It stays connected to the rest of the page

A program manager opens the Confluence table before a portfolio review and sorts by RAG status. Every Red project appears first. An engineering lead filters to their team and groups by phase within seconds; they can see what’s in delivery and what’s still in planning. An executive opens the same page and sorts by priority to focus on the highest-impact initiatives.

Smart Tables also work naturally alongside the rest of a project page: Jira issue embeds, smart links, user mentions, decisions, and other Confluence content, the table remains connected to the broader project context rather than becoming a separate reporting destination.

The best project status table is not the one with the most metrics; it’s the one people actually keep up to date. When filtering, sorting, grouping, and editing are frictionless, the Confluence table stops being documentation and starts becoming an operational tool teams trust.

Building a project status table in Confluence that actually stays up to date is not a process problem. It’s a tooling problem, and one structured, filterable, inline-editable table is usually all it takes to solve it.