Scaling agentic AI isn’t nearly having the most recent instruments — it requires clear steerage, the fitting context, and a tradition that champions experimentation to unlock actual worth. At VentureBeat’s Transform 2025, Anu Bharadwaj, president of Atlassian, shared actionable insights into how the corporate has empowered its staff to construct 1000’s of customized brokers that remedy actual, on a regular basis challenges. To construct these brokers, Atlassian has fostered a tradition rooted in curiosity, enthusiasm and steady experimentation.
“You hear loads about AI top-down mandates,” Bharadwaj stated. “High-down mandates are nice for making an enormous splash, however actually, what occurs subsequent, and to who? Brokers require fixed iteration and adaptation. High-down mandates can encourage individuals to begin utilizing it of their day by day work, however individuals have to make use of it of their context and iterate over time to appreciate most worth.”
That requires a tradition of experimentation — one the place short- to medium-term setbacks aren’t penalized however embraced as stepping stones to future development and high-impact use circumstances.
Making a protected surroundings
Atlassian’s agent-building platform, Rovo Studio, serves as a playground surroundings for groups throughout the enterprise to construct brokers.
“As leaders, it’s vital for us to create a psychologically protected surroundings,” Bharadwaj stated. “At Atlassian, we’ve all the time been very open. Open firm, no bullshit is one in all our values. So we give attention to creating that openness, and creating an surroundings the place staff can check out various things, and if it fails, it’s okay. It’s wonderful since you discovered one thing about tips on how to use AI in your context. It’s useful to be very specific and open about it.”
Past that, you need to create a stability between experimentation with guardrails of security and auditability. This contains security measures like ensuring staff are logged in once they’re attempting instruments, to creating certain brokers respect permissions, perceive role-based entry, and supply solutions and actions based mostly on what a specific person has entry to.
Supporting team-agent collaboration
“After we take into consideration brokers, we take into consideration how people and brokers work collectively,” Bharadwaj stated. “What does teamwork seem like throughout a workforce composed of a bunch of individuals and a bunch of brokers — and the way does that evolve over time? What can we do to help that? In consequence, all of our groups use Rovo brokers and construct their very own Rovo brokers. Our concept is that when that type of teamwork turns into extra commonplace, all the working system of the corporate modifications.”
The magic actually occurs when a number of individuals work along with a number of brokers, she added. As we speak numerous brokers are single-player, however interplay patterns are evolving. Chat won’t be the default interplay sample, Bharadwaj says. As a substitute, there shall be a number of interplay patterns that drive multiplayer collaboration.
“Basically, what’s teamwork all about?” she posed to the viewers. “It’s multiplayer collaboration — a number of brokers and a number of people working collectively.”
Making agent experimentation accessible
Atlassian’s Rovo Studio makes agent constructing obtainable and accessible to individuals of all ability units, together with no-code choices. One development business buyer constructed a set of brokers to cut back their roadmap creation time by 75%, whereas publishing large HarperCollins constructed brokers that diminished guide work by 4X throughout their departments.
By combining Rovo Studio with their developer platform, Forge, technical groups acquire highly effective management to deeply customise their AI workflows — defining context, specifying accessible data sources, shaping interplay patterns and extra — and create extremely specialised brokers. On the identical time, non-technical groups additionally have to customise and iterate, so that they’ve constructed experiences in Rovo Studio to permit customers to leverage pure language to make their customizations.
“That’s going to be the large unlock, as a result of basically, once we discuss agentic transformation, it can’t be restricted to the code gen situations we see right this moment. It has to permeate all the workforce,” Bharadwaj stated. “Builders spend 10% of their time coding. The remaining 90% is working with the remainder of the workforce, determining buyer points and fixing points in manufacturing. We’re making a platform by which you’ll construct brokers for each single a type of features, so all the loop will get sooner.”
Making a bridge from right here to the longer term
Not like the earlier shifts to cell or cloud, the place a set of technological or go-to-market modifications occurred, AI transformation is basically a change in the best way we work. Bharadwaj believes crucial factor to do is to be open and to share how you might be utilizing AI to alter your day by day work. “For example, I share Loom movies of recent instruments that I’ve tried out, issues that I like, issues that I didn’t like, issues the place I believed, oh, this could possibly be helpful if solely it had the fitting context,” she added. “That fixed psychological iteration, for workers to see and check out each single day, is very vital as we shift the best way we work.”
