October 7, 2025
3 minutes

The AI Automation Breakthrough: Key Insights from Our Latest Community Event

Last night, Optimal brought together an incredible community of product leaders and innovators for "The Automation Breakthrough: Workflows for the AI Era" at Q-Branch in Austin, Texas. This two-hour in-person event featured expert perspectives on how AI and automation are transforming the way we work, create, and lead.

The event featured a lightning Talk on "Designing for Interfaces" featured Cindy Brummer, Founder of Standard Beagle Studio, followed by a dynamic panel discussion titled "The Automation Breakthrough" with industry leaders including Joe Meersman (Managing Partner, Gyroscope AI), Carmen Broomes (Head of UX, Handshake), Kasey Randall (Product Design Lead, Posh AI), and Prateek Khare (Head of Product, Amazon). We also had a fireside chat with our CEO, Alex Burke and Stu Smith, Head of Design at Atlassian. 

Here are the key themes and insights that emerged from these conversations:

Trust & Transparency: The Foundation of AI Adoption

Cindy emphasized that trust and transparency aren't just nice-to-haves in the AI era, they're essential. As AI tools become more integrated into our workflows, building systems that users can understand and rely on becomes paramount. This theme set the tone for the entire event, reminding us that technological advancement must go hand-in-hand with ethical considerations.

Automation Liberates Us from Grunt Work

One of the most resonant themes was how AI fundamentally changes what we spend our time on. As Carmen noted, AI reduces the grunt work and tasks we don't want to do, freeing us to focus on what matters most. This isn't about replacing human workers, it's about eliminating the tedious, repetitive tasks that drain our energy and creativity.

Enabling Creativity and Higher-Quality Decision-Making

When automation handles the mundane, something remarkable happens: we gain space for deeper thinking and creativity. The panelists shared powerful examples of this transformation:

Carmen described how AI and workflows help teams get to insights and execution on a much faster scale, rather than drowning in comments and documentation. Prateek encouraged the audience to use automation to get creative about their work, while Kasey shared how AI and automation have helped him develop different approaches to coaching, mentorship, and problem-solving, ultimately helping him grow as a leader.

The decision-making benefits were particularly striking. Prateek explained how AI and automation have helped him be more thoughtful about decisions and make higher-quality choices, while Kasey echoed that these tools have helped him be more creative and deliberate in his approach.

Democratizing Product Development

Perhaps the most exciting shift discussed was how AI is leveling the playing field across organizations. Carmen emphasized the importance of anyone, regardless of their role, being able to get close to their customers. This democratization means that everyone can get involved in UX, think through user needs, and consider the best experience.

The panel explored how roles are blurring in productive ways. Kasey noted that "we're all becoming product builders" and that product managers are becoming more central to conversations. Prateek predicted that teams are going to get smaller and achieve more with less as these tools become more accessible.

Automation also plays a crucial role in iteration, helping teams incorporate customer feedback more effectively, according to Prateek.

Practical Advice for Navigating the AI Era

The panelists didn't just share lofty visions, they offered concrete guidance for professionals navigating this transformation:

Stay perpetually curious. Prateek warned that no acquired knowledge will stay with you for long, so you need to be ready to learn anything at any time.

Embrace experimentation. "Allow your process to misbehave," Prateek advised, encouraging attendees to break from rigid workflows and explore new approaches.

Overcome fear. Carmen urged the audience not to be afraid of bringing in new tools or worrying that AI will take their jobs. The technology is here to augment, not replace.

Just start. Kasey's advice was refreshingly simple: "Just start and do it again." Whether you're experimenting with AI tools or trying "vibe coding," the key is to begin and iterate.

The energy in the room at Q-Branch reflected a community that's not just adapting to change but actively shaping it. The automation breakthrough isn't just about new tools, it's about reimagining how we work, who gets to participate in product development, and what becomes possible when we free ourselves from repetitive tasks.

As we continue to navigate the AI era, events like this remind us that the most valuable insights come from bringing diverse perspectives together. The conversation doesn't end here, it's just beginning.

Interested in joining future Optimal community events? Stay tuned for upcoming gatherings where we'll continue exploring the intersection of design, product, and emerging technologies.

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1 min read

Top Tasks in UX: How to Identify What Really Matters to Your Users

All the way back in 2014, the web passed a pretty significant milestone: 1 billion websites. Of course, fewer than 200 million of these are actually active as of 2019, but there’s an important underlying point. People love to create. If the current digital age that we live in has taught us anything, it’s that it’s never been as easy to get information and ideas out into the world.

Understandably, this ability has been used – and often misused. Overloaded, convoluted websites are par for the course, with a common tactic for website renewal being to simply update them with a new coat of paint while ignoring the swirling pile of outdated and poorly organized content below.

So what are you supposed to do when trying to address this problem on your own website or digital project? Well, there’s a fairly robust technique called top tasks management. Here, we’ll go over exactly what it is and how you can use it.

Getting to grips with top tasks

Ideally, all websites would be given regular, comprehensive reviews. Old content could be revisited and analyzed to see whether it’s still actually serving a purpose. If not, it could be reworked or just removed entirely. Based on research, content creators could add new content to address user needs. Of course, this is just the ideal. The reality is that there’s never really enough time or resource to manage the growing mass of digital content in this way. The solution is to hone in on what your users actually use your website for and tailor the experience accordingly by looking at top tasks.

What are top tasks? They're basically a small set of tasks (typically around 5, but up to 10 is OK too) that are most important to your users. The thinking goes that if you get these core tasks right, your website will be serving the majority of your users and you’ll be more likely to retain them. Ignore top tasks (and any sort of task analysis), and you’ll likely find users leaving your website to find something else that better fits their needs.

The counter to top tasks is tiny tasks. These are everything on a website that’s not all that important for the people actually using it. Commonly, tiny tasks are driven more by the organization’s needs than those of the users. Typically, the more important a task is to a user, the less information there is to support it. On the other hand, the less important a task is to a user, the more information there is. Tiny tasks stem very much from ‘organization first’ thinking, wherein user needs are placed lower on the list of considerations.

According to Jerry McGovern (who penned an excellent write-up of top tasks on A List Apart), the top tasks model says “Focus on what really matters (the top tasks) and defocus on what matters less (the tiny tasks).”

How to identify top tasks

Figuring out your top tasks is an important step in clearing away the fog and identifying what actually matters to your users. We’ll call this stage of the process task discovery, and these are the steps:

  1. Gather: Work with your organization to gather a list of all customer tasks
  2. Refine: Take this list of tasks to a smaller group of stakeholders and work it down into a shortlist
  3. User feedback: Go out to your users and get a representative sample to vote on them
  4. Finalise: Assemble a table of tasks with the one with the highest number of votes at the top and the lowest number of votes at the bottom

We’ll go into detail on the above steps, explaining the best way of handling each one. Keep in mind that this process isn’t something you’ll be able to complete in a week – it’s more likely a 6 to 8-week project, depending on the size of your website, how large your user base is and the receptiveness of your organization to help out.

Step 1: Gather – Figure out the long list of tasks

The first part of the task process is to get out into the wider organization and discover what your users are actually trying to accomplish on your website or by using your products. It’s all about getting into the minds of your users – trying to see the world through their eyes, effectively.

If you’re struggling to think of places where you might find customer tasks, here are some of the best sources:

  • Analytics: Take a deep dive into the analytics of your website or product to find out how people are using them. For websites, you’ll want to look at pages with high traffic and common downloads or interactions. The same applies to products – although the data you have access to will depend on the analytics systems in place.
  • Customer support teams: Your own internal support teams can be a great source of user tasks. Support teams commonly spend all day speaking to users, and as a result, are able to build up a cohesive understanding of the types of tasks users commonly attempt.
  • Sales teams: Similarly, sales teams are another good source of task data. Sales teams typically deal with people before they become your users, but a part of their job is to understand the problems they’re trying to solve and how your website or product can help.
  • Direct customer feedback: Check for surveys your organization has run in the past to see whether any task data already exists.
  • Social media: Head to Twitter, Facebook and LinkedIn to see what people are talking about with regards to your industry. What tasks are being mentioned?

It’s important to note that you need to cast a wide net when gathering task data. You can’t just rely on analytics data. Why? Well, downloads and page visits only reflect what you have, but not what your users might actually be searching for.

As for search, Jerry McGovern explains why it doesn’t actually tell the entire story: “When we worked on the BBC intranet, we found they had a feature called “Top Searches” on their homepage. The problem was that once they published the top searches list, these terms no longer needed to be searched for, so in time a new list of top searches emerged! Similarly, top tasks tend to get bookmarked, so they don’t show up as much in search. And the better the navigation, the more likely the site search is to reflect tiny tasks.”

At the end of the initial task-gathering stage you should be left with around 300 to 500 tasks. Of course, this can scale up or down depending on the size of the website or product.

Step 2: Refine – Create your shortlist

Now that you’ve got your long list of tasks, it’s time to trim them back until you’ve got a shortlist of 100 or less. Keep in mind that working through your long list of tasks is going to take some time, so plan for this process to take at least 4 weeks (but likely more).

It’s important to involve stakeholders from across the organization during the shortlist process. Bring in people from support, sales, product, marketing and leadership areas of the organization. In addition to helping you to create a more concise and usable list, the shortlist process helps your stakeholders to think about areas of overlap and where they may need to work together.

When working your list down to something more usable, try and consolidate and simplify. Stay away from product names as well as internal organization and industry jargon. With your tasks, you essentially want to focus on the underlying thing that a user is trying to do. If you were focusing on tasks for a bank, opt for “Transactions” instead of “Digital mobile payments”. Similarly, bring together tasks where possible. “Customer support”, “Help and support” and “Support center” can all be merged.

At a very technical level, it also helps to avoid lengthy tasks. Stick to around 7 to 8 words and try and avoid verbs, using them only when there’s really no other option. You’ll find that your task list becomes quick to navigate when tasks begin with “look”, “find” and “get”. Finally, stay away from specific audiences and demographics. You want to keep your tasks universal.

Step 3: User feedback – Get users to vote

With your shortlist created, it’s time to take it to your users. Using a survey tool like Optimal's Surveys, add in each one of your shortlisted tasks and have users rank 5 tasks on a scale from 1 to 5, with 5 being the most important and 1 being the least important.

If you’re thinking that your users will never take the time to work through such a long list, consider that the very length of the list means they’ll seek out the tasks that matter to them and ignore the ones that don’t.

A section of the customer survey in Questions.
A section of the customer survey in Questions.

Step 4: Finalize – Analyze your results

Now for the task analysis side of the project. What you want at the end of the user survey end of the project is a league table of entire shortlist of tasks. We’re going to use the example from Cisco’s top tasks project, which has been documented over at A List Apart by Gerry McGovern (who actually ran the project). The entire article is worth a read as it covers the process of running a top task project for a large organization.

Here’s what a league table of the top 20 tasks looks like from Cisco:

A league table of the top 20 tasks from Cisco’s top tasks project.
A league table of the top 20 tasks from Cisco’s top tasks project. Credit: Jerry McGovern.

Here’s the breakdown of the vote for Cisco’s tasks:

  • 3 tasks got the first 25 percent of the vote
  • 6 tasks got 25-50 percent of the vote
  • 14 tasks got 50-75 percent of the vote
  • 44 tasks got 75-100 percent of the vote

While the pattern may seem surprising, it’s actually not unusual. As Jerry explains: “We have done this process over 400 times and the same patterns emerge every single time.”

Final thoughts

Focusing on top tasks management is really a practice that needs to be conducted on a semi-regular basis. The approach benefits organizations in a multitude of ways, bringing different teams and people together to figure out how to best address why your users are coming to your website and what they actually need from you.

As we explained at the beginning of this article, top tasks is really about clearing away the fog and understanding on what really matters. Instead of spreading yourself thin and focusing on a host of tiny tasks, hone in on those top tasks that actually matter to your users.

Understanding how to improve your website

The top tasks approach is an effective way of giving you a clear idea of what you should be focusing on when designing or redesigning your website, but this should really just be one aspect of the work you do.

Utilizing a host of other UX research methods can give you a much more comprehensive idea of what’s working and what’s not. With card sorting, for example, you can learn how your users think the content on your website should be arranged. Then, with this data in hand, you can use tree testing to assemble draft structures of your website and test how people navigate their way through it. You can keep iterating on these structures to ensure you’ve created the most user-friendly navigation.

Take a look at our 101 guides to learn more about card sorting and tree testing, as well as the other user research methods you can use to make solid improvements to your website. If you’d rather just start putting methods into practice using user research tools, take our UX platform for a spin for free here.

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UX Masterclass: The Convergence of Product, Design, and Research Workflows

The traditional product development process is a linear one. Research discovers insights, passes the baton to design, who creates solutions and hands off to product management, who delivers requirements to engineering. Clean. Orderly. Completely unrealistic in today’s modern product development lifecycle.

Beyond the Linear Workflow

The old workflow assumed each team had distinct phases that happened in sequence. Research happens first (discover users problems), then design (create the solutions), then product (define the specifications), then engineering (build it). Unfortunately this linear approach added weeks to timelines and created information loss at every handoff.

Smart product teams are starting to approach this differently, collapsing these phases into integrated workflows:

  • Collaborative Discovery. Instead of researchers conducting studies alone, the product trio (PM, designer, researcher) participates together. When engineers join user interviews, they understand context that no requirement document could capture.
  • Live Design Validation. Rather than waiting for research reports, designers test concepts weekly. Quick iterations based on immediate feedback replace month-long design cycles.
  • Integrated Tooling. Teams use platforms where research data and insights across the product development lifecycle, from ideation to optimization, all live in the same place, eliminating information silos and making sure information is shared across teams.

What Collaborative Workflows Look Like in Practice 

  • Discovery Happens Weekly. Instead of quarterly research projects, teams run continuous user conversations where the whole team participates.
  • Design Evolves Daily. There are no waterfall designs handed off to developers, but iterative prototypes tested immediately with users.
  • Products Ship Incrementally. Instead of big-bang releases after months of development, product releases small iterations validated every sprint.
  • Insights Flow Constantly. Teams don’t wait for learnings at the end of projects, but access real-time feedback loops that give insights immediately.

In leading organizations, these collaborative workflows are already the norm and we’re seeing this more and more across our customer base. The teams managing it the best, are focusing on make these changes intentional, rather than letting them happen chaotically.

As product development accelerates, the teams winning aren't those with the best researchers, designers, or product managers in isolation. They're organizations where these teams work together, where expertise is shared, and where the entire team owns the user experience.

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AI-Powered Search Is Here and It’s Making UX More Important Than Ever

Let's talk about something that's changing the game for all of us in digital product design: AI search. It's not just a small update; it's a complete revolution in how people find information online.

Today's AI-powered search tools like Google's Gemini, ChatGPT, and Perplexity AI aren't just retrieving information they're having conversations with users. Instead of giving you ten blue links, they're providing direct answers, synthesizing information from multiple sources, and predicting what you really want to know.

This raises a huge question for those of us creating digital products: How do we design experiences that remain visible and useful when AI is deciding what users see?

AI Search Is Reshaping How Users Find and Interact with Products

Users don't browse anymore: they ask and receive. Instead of clicking through multiple websites, they're getting instant, synthesized answers in one place.

The whole interaction feels more human. People are asking complex questions in natural language, and the AI responses feel like real conversations rather than search results.

Perhaps most importantly, AI is now the gatekeeper. It's deciding what information users see based on what it determines is relevant, trustworthy, and accessible.

This shift has major implications for product teams:

  • If you're a product manager, you need to rethink how your product appears in AI search results and how to engage users who arrive via AI recommendations.
  • UX designers—you're now designing for AI-first interactions. When AI directs users to your interfaces, will they know what to do?
  • Information architects, your job is getting more complex. You need to structure content in ways that AI can easily parse and present effectively.
  • Content designers, you're writing for two audiences now: humans and AI systems. Your content needs to be AI-readable while still maintaining your brand voice.
  • And UX researchers—there's a whole new world of user behaviors to investigate as people adapt to AI-driven search.

How Product Teams Can Optimize for AI-Driven Search

So what can you actually do about all this? Let's break it down into practical steps:

Structuring Information for AI Understanding

AI systems need well-organized content to effectively understand and recommend your information. When content lacks proper structure, AI models may misinterpret or completely overlook it.

Key Strategies

  • Implement clear headings and metadata – AI models give priority to content with logical organization and descriptive labels
  • Add schema markup – This structured data helps AI systems properly contextualize and categorize your information
  • Optimize navigation for AI-directed traffic – When AI sends users to specific pages, ensure they can easily explore your broader content ecosystem

LLM.txt Implementation

The LLM.txt standard (llmstxt.org) provides a framework specifically designed to make content discoverable for AI training. This emerging standard helps content creators signal permissions and structure to AI systems, improving how your content is processed during model training.

How you can use Optimal:  Conduct Tree Testing  to evaluate and refine your site's navigation structure, ensuring AI systems can consistently surface the most relevant information for users.

Optimize for Conversational Search and AI Interactions

Since AI search is becoming more dialogue-based, your content should follow suit. 

  • Write in a conversational, FAQ-style format – AI prefers direct, structured answers to common questions.
  • Ensure content is scannable – Bullet points, short paragraphs, and clear summaries improve AI’s ability to synthesize information.
  • Design product interfaces for AI-referred users – Users arriving from AI search may lack context ensure onboarding and help features are intuitive.

How you can use Optimal: Run First Click Testing to see if users can quickly find critical information when landing on AI-surfaced pages.

Establish Credibility and Trust in an AI-Filtered World

AI systems prioritize content they consider authoritative and trustworthy. 

  • Use expert-driven content – AI models favor content from reputable sources with verifiable expertise.
  • Provide source transparency – Clearly reference original research, customer testimonials, and product documentation.
  • Test for AI-user trust factors – Ensure AI-generated responses accurately represent your brand’s information.

How you can use Optimal: Conduct Usability Testing to assess how users perceive AI-surfaced information from your product.

The Future of UX Research

As AI search becomes more dominant, UX research will be crucial in understanding these new interactions:

  • How do users decide whether to trust AI-generated content?
  • When do they accept AI's answers, and when do they seek alternatives?
  • How does AI shape their decision-making process?

Final Thoughts: AI Search Is Changing the Game—Are You Ready?

AI-powered search is reshaping how users discover and interact with products. The key takeaway? AI search isn't eliminating the need for great UX, it's actually making it more important than ever.

Product teams that embrace AI-aware design strategies, by structuring content effectively, optimizing for conversational search, and prioritizing transparency, will gain a competitive edge in this new era of discovery.

Want to ensure your product thrives in an AI-driven search landscape? Test and refine your AI-powered UX experiences with Optimal  today.

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