Atlassian brings automation to Confluence to help curate the 'content explosion'
- Atlassian this week brings workflow automation capabilities into Confluence and adds new connected automations to Jira.
It's never been easier to find information, but is it reliable? The growing ease with which it's possible to create and publish information is leading to a growing headache of curation and validation. Yesterday, Atlassian added automation tools to its Confluence knowledge-sharing platform to help enterprises ease that headache, at least for their own internal knowledge base. Erika Trautman, Head of Product Management, Work Management For All, at Atlassian, says:
If you think about the things that hold you back from ensuring that your source of truth is really useful, up-to-date and current, there's a gazillion little meaningless tasks that matter for the overarching hygiene and health of your corpus. They get neglected because we're humans — they're not interesting, they're not what we want to focus on. They are the perfect thing to be outsourcing to the computers to do for you, and automation lets us do that.
Confluence is now gaining similar automation capabilities to those introduced almost three years ago within Atlassian's Jira work management products, which also gained some new features this week. The new Automation for Confluence toolset includes a library of preconfigured rules and a low-/no-code rule builder, so that admins can either start with a ready-made pattern and amend it as required, or create their own from scratch. Examples of preconfigured rules range from automated notifications when certain authors post new content, reminders when scheduled tasks remain uncompleted, automated tag updates, and auto archiving of inactive pages, to notifying content owners or curators of outdated content, and automatically creating a set of new documents when starting an activity.
Curating the content explosion
Many of these tasks are often overlooked or ignored when managing content manually, but are a fundamental part of the crucial housekeeping that's needed to ensure shared knowledge stays fresh and accurate. With more and more content being generated, automation becomes essential for content managers to keep pace. Trautman says:
Content creation has been on a trend where it's been cheaper and cheaper to do, because tools have made it so easy, and democratized who can create content, who can create information. So we've seen a proliferation of content. In the media space, you've seen a proliferation of UGC [user-generated] content. So we were in a content explosion, and then obviously, chatGTP and those kinds of [generative AI] solutions are going to just blow that out of the water.
So curation, and human interaction with, to verify, I think that's going to be the hardest problem to solve — what is the verifiable, most important information? ... There needs to be a human curation component in that. I think that automation, and even machine learning automation, can be a tool for humans to get better at that curation process.
The automation introduced this week is a first step but there will be more to come as Atlassian expands its capabilities. She elaborates:
We will be leaning even more into nudging you into good content hygiene. That good content hygiene ranges from organization, which is going to be increasingly important in a world of proliferation of content, to verification. There's some interesting stuff that we're contemplating like, we have data around how people interact with your documents. So we can potentially help surface like, 'Look, this concept, it's hot debate, and 75% of people don't agree with it.' That might be interesting information for me, as the drafter of that content, to understand in order to make it more useful, more relevant, to move some idea forward. Those are ways in which we can use heuristics, machine learning, to help in the process of elevating, refining and curating the right content, even as there's so much proliferation of it.
Joined-up workflow automation
The new toolset is included with Confluence Cloud Premium and Enterprise licenses and free trials. Although it doesn't yet join up with automations in other Atlassian products, the functionality comes from the same underlying platform and connecting workflows across different products is definitely in the product roadmap. Trautman says this will be important for tasks that are shared between business and technical teams. She explains:
Atlassian is ... really positioned to do this well, to really connect the technical teams and the business teams together in terms of a shared knowledge base, in terms of a shared data structure, and in terms of workflows, being able to flow between technical and business teams. So you'll see this go from Confluence specific — which, all by itself, I think is going to be tremendously valuable to our customers — to across the Atlassian portfolio, via the Atlassian platform.
Existing automation capabilities in the Jira product set saw extensions this week to connect workflows into other tools used by developers and IT teams. To enable automations across the DevOps toolchain, there are new native connections between Jira, Confluence, and release management tools such as LaunchDarkly, as well as bi-directional actions between Jira and Git tools such as Bitbucket, GitHub, or GitLab. Automation in Jira Service Management has a new connection to AWS that enables ITOps teams to automate manual tasks and run actions there. There are expanded connections with CI/CD tools to automate the creation of change requests. Finally, a new low-code/no-code form builder linked to Assets objects makes it easy for business teams to create self-service forms to initiate requests for new equipment, such as when onboarding new staff.
Knowledge sharing is crucial to the smooth operation of the modern enterprise, whether it's guides to internal policy and process, how-to knowledge used in customer service and support, product specifications and handbooks, compliance manuals, and so much more. Some of the most useful knowledge is gained in the midst of fixing issues or finding answers for customers, but the challenge is then storing that knowledge so that it can be reused the next time the need arises. This is especially challenging when there may be earlier solutions still on record that no longer work so well or which have been superseded by changes in product specifications or compliance guidelines. The job of collecting, storing and validating all this information often isn't taken as seriously as it should be, and yet the task is getting more and more challenging as the proliferation of content expands. The contributions from sources like chatGPT only add fuel to the ongoing explosion, and not in a good way.
It's good to see Atlassian bringing new automation tools to Confluence but given that the technology has been in the company for more than three years now, it could have been introduced even earlier. The sooner these capabilities get joined up with other products in the porfolio — and beyond to third-party products too — the better it will be to help customers automate more of these and other crucial workflows.