We’re moving to an era of systems of intelligence, from systems of record. In the previous era, you could win by building software that had a better, cleaner and simpler user experience.
In the new era, though, a system of record is table stakes.
The future is about orchestrating AI systems to build new systems of intelligence - leading humans to significant productivity like never before. Software that remains as just systems of record will perish or become much less valuable. Systems of intelligence are the ones that will stick around in the next decade and longer.
Every product category is evolving to meet the demands of this brave new world:
Customer support software is moving from helping you just track tickets, measuring SLAs to actually solving user problems (not just by answering questions, but taking actions).
CRM software will ambiently capture contact information, meeting notes, signals like who are promoters vs detractors when they show up in meetings, and enable sales teams to chase high quality leads, write better emails, run automated followups, close more deals.
Test case automation software will understand the context behind your product, write and execute test cases understanding how different parts of your product play together.
Without a doubt, project management software is up for reinvention.
How will AI-first project management software look like? Or rather, how should they like, in our AI-enabled future? These are good questions to ask today.
If we think about the state of these products today, they do just what we’ve come to expect of them - track issues, organize and triage them, get some reporting on tasks and people missing their SLA, etc.
I presume these products started off as bug tracking tools for engineering teams. Clearly, everyone from operations, facilities, IT support, etc. also had tasks to manage, and these products started building a lot to appeal for different functions and usecases horizontally.
As a result, such software got complex to manage and configure. Pages and pages of fields, rules, reports to configure - things that make it difficult to use and understand things over time. This is why Linear won with a simpler, usable experience and a strong sense of aesthetics.
Now that just a better sense of user experience and aesthetics is not enough, this is what I believe would emerge from issue tracking software in the future:
Capture data and signals from everywhere
Most early teams move at breakneck speed and struggle to capture and prioritize the right problems and issues.
At my previous workplace, there was a ton of action happening everyday. Meeting notes with customers were posted on Slack. Obviously, customers had new asks and bug fix requests on those calls. There was also a channel for capturing bugs we ourselves ran into, when using the product. Not to mention QA and engineering teams regularly capturing issues as they do their tests, on Jira.
This is true for any startup and incumbent - there’s always a lot going on and it’s always the responsibility of some people to keep track of the most important and drive those things to execution.
Project management tools from the future will capture notes from Slack, emails, Microsoft Teams, Granola, Zoom, and other similar software to first get a sense of what’s going on - like a good product manager and engineering lead would. They’d digest information and have context of the most important customers, high-intent leads and deals that are more likely to convert. They’ll take some burden off product managers and engineering leaders, who are supposed to stay on top of all of this information.
Help teams prioritize what is important
Prioritization is lots of science, some art. Product teams typically ask questions like these when figuring out what to do next:
given my current business and product strategy, is this problem worth working on, now?
what items from the backlog should I prioritize, given the constraints we have?
which parts of the product need to be desperately improved? what are some specific issues and ideas customers have shared, which I need to prioritize?
what are some things my team can pick up to help close more deals?
what are some things my team can pick up to drive growth in certain areas?
This isn’t an exhaustive list, of course. But these are definitely some questions that anyone responsible for thinking about the “why” and “what” of what a team should work on, worries about today. Beyond continuously capturing information from different sources, AI project management products should make prioritization decisions like a smart person would. AI should help hone some of that art and science behind prioritization, if not completely automate it.
Help teams execute faster
This is already happening - with tools like Cursor, WindSurf and Devin, software teams are able to automate more of their work. Things are only going to get better from here.
But it’s not just software engineering teams that use project management tools. There’s a lot of other teams that use such products to manage their internal tasks. IT uses Jira to manage upcoming changes, updates to configurations of internal tools etc. Facilities teams uses tickets to run their operations. All of that is ripe for agentic automation too.
Think calling vendors, automating reminder emails, organizing some tasks related to company events, etc. - there’s an endless list of things here that humans do that are messy but are now ripe for automation that project management tools can help drive.
Synthesize new ideas and help refine strategy
If AI can do all the above, can’t it come up with new ideas, don’t you think? :)
