Modus Create

To build or buy AI solutions? It's an important question that leaders often misjudge. 📚 According to our survey of 550 product and technology leaders, nearly half are making decisions based on their teams' skills. That's a short-term lens on a long-term choice. The real question isn't whether your team has the skills to build. It's whether it should. Our VP Greg Sterndale offers a more practical approach, based on the problem you want to solve: ✅ Build when you need to differentiate your business or provide strategic value ✅ Buy when your business problem is common and time-sensitive ✅ Move fast and partner with experts if your problem is both unique and urgent Get this choice right, and AI becomes a meaningful driver of business performance, instead of another shiny tool. Check out more insights 👇 https://lnkd.in/e7zyfARh #ProductDevelopment #AIStrategy

Increase smoking quit rates by 34% — this is what one life sciences company achieved after modernizing its patient engagement app. 👀 The app had a problem: patients dropped off too early. The data was there, but the platform wasn't built to use it. By rebuilding on Amazon Web Services (AWS) with predictive ML, the company saw real results: ✅ 85% accuracy in predicting cessation outcomes ✅ 64% user recommendation rate ✅ Platform data strong enough to unlock 3 new regulatory submissions All to do what matters most: Help more people quit smoking for good. Read the full story 👇 https://hubs.ly/Q04f24Py0 #LifeSciences #AppModernization #AWSPartner

Leaders are mistaking AI activity for AI maturity. Our research finds that 84% of product and technology leaders say their organizations have integrated AI across the product development lifecycle. But dig a little deeper, and the numbers tell a different story. 👀 Only 28% report using AI for prototyping, 38% for coding features, and 43% for testing and QA. As our VP Greg Sterndale puts it, many leaders don't even have a clear definition of AI maturity, which is exactly why they overestimate it. The takeaway: True AI maturity isn't about deploying a chatbot. It's about embedding AI into workflows, processes, and decision-making across the organization. Where does your team land? The full report unpacks the gap between perceived and actual AI maturity and what it takes to close it. Check it out 👇 https://lnkd.in/euA3qFfk #AIMaturity #ProductDevelopment

Having AI-ready data is one of the biggest barriers to AI adoption, but there's a way forward. In her blog, our expert Maria Knorps outlines 20 questions every leader should ask, plus a practical, phased approach to turn a daunting prospect into manageable steps that deliver real value. 📈 Check it out 👇 https://hubs.ly/Q04dBPqk0 #AIStrategy #DataStrategy #DataReadiness

For many healthcare and life sciences professionals, AI only works when it frees people to focus on discovering life-saving treatments and improving patient care. ⚕️ In one case that our CEO Sharon Lynch shares, scientists who spent most of their time typing experiment results saw a 60% increase in productivity with automation. But intention only goes so far. According to our research, healthcare and life sciences organizations are struggling to turn AI ambition into real results. 92% of product leaders say the pressure to prove ROI is increasing, and 83% say following through on strategy is a significant challenge. What's holding teams back, and what separates successful leaders from the rest? Read the report on scaling AI in healthcare and life sciences to learn more 👇 https://hubs.ly/Q04dlcvr0 #Healthcare #LifeSciences #ProductEngineering

Your team is shipping faster with AI. But is it shipping better? This is the question every engineering leader should be asking. According to our survey of 550 product and technology leaders, 84% say that they have integrated AI in product development workflows, but only 43% use it for QA and testing. This creates a huge gap that shows up in bugs, rework, and production issues. Our latest whitepaper explains how to scale testing with AI while maintaining high-quality output. You’ll learn: ✅ Where AI actually delivers results in testing (and where it doesn’t) ✅ Where AI creates false confidence ✅ How spec quality directly impacts test accuracy ✅ How to build validation into your pipeline without slowing delivery Check it out 👇 https://hubs.ly/Q04dff860 #ProductDevelopment #QA #Engineering

#Team26 is a few weeks away. Are you going? 🖐️ Many booths will be showcasing flashy product demos that stop at implementation. But will they actually matter to your business? We’ll be at booth 321. Come talk to us about scaling smarter, modernizing intentionally, and delivering measurable results that last, like faster onboarding, shorter cycle times, and less manual reporting. See you there! Register for Team '26 today and save 20% on registration 👇 https://hubs.ly/Q04d4P4J0 #Atlassian #Modernization #AICollaboration

Instead of treating modernization as a one-time initiative, the best engineering teams build for continuous improvement. This is the key to success, says our VP Michael Hodgdon. 💡 In our survey of 550 product and technology leaders, 95% said their organizations are modernizing legacy systems, and more than half are already moving to the cloud. But rather than just focus on getting to the cloud, teams need to thrive in the cloud. As Michael points out, that’s where collaboration stops being optional. Platform decisions shape velocity. Security decisions influence trust. Engineering practices determine whether AI accelerates learning or creates noise. These are no longer separate lanes. Progress comes from teams working together. Check out the research to see what successful teams are doing differently 👇 https://hubs.ly/Q04cX1S10 #Modernization #Cloud #PlatformEngineering

We’re proud to announce that we’re an official sponsor of the San Antonio AWS Users group! 🎉 With 1,100+ members, this community is one of San Antonio's go-to spaces for cloud enthusiasts to share tools, best practices, and real-world challenges around deploying, running, and maintaining web apps and services on Amazon Web Services (AWS). We look forward to the conversations with our peers in the user community and connecting with builders. If you’re in the San Antonio area, join us! Learn more 👇 https://hubs.ly/Q04cNqsX0 #AWS #AWSPartners #SanAntonio AWS Partners

AI is reshaping product teams, but probably not in the way you expect. Many headlines focus on headcount cuts. Our research tells a different story. 📰 53% of product leaders are reskilling existing developers to work with AI tools, and 43% plan to hire more data scientists and ML engineers. Only 30% are looking to reduce traditional engineering headcount. Cutting teams for AI efficiency has long-term consequences. Without experts who know how to build, govern, and apply AI effectively, outcomes become insecure and unreliable. We surveyed 550 product and technology leaders about AI's impact on product development. See what they said 👇 https://lnkd.in/eu8EQEKc #ProductDevelopment #Engineering #AI