Productboard now connects directly with Lovable 🎉 Ever written a product spec that seemed complete… until you actually saw the design? That's why we're bringing prototyping closer to product discovery. Just ask Spark to send your spec to Lovable, and watch it turn into a working prototype in minutes. Explore the experience, catch what you missed, and bring those learnings back into your spec before engineering starts building. And it all started as a little side quest from Tor Svendsen, Principal Product Manager at Productboard. Learn more → productboard.com/integration…

Your customer feedback is piling up. Your roadmap is already full. And somewhere in that backlog are insights your team can't afford to miss. Sound familiar? As product teams grow, the informal processes that once worked start to break down. Feedback gets scattered across tools, PMs categorize it differently, and valuable customer signals get lost in the noise. The solution isn't just collecting more feedback. It's building a system that turns feedback into evidence you can actually use to make product decisions. In our latest blog, we break down how product leaders can standardize feedback collection, identify and prioritize meaningful patterns, and use AI to connect customer needs to business impact. Read it now → productboard.com/blog/custom…

Still buzzing from a whirlwind few days at The AI Conference in San Francisco. Productboard CEO @hpalan brought his insight on what product teams need once AI is no longer the bottleneck for writing code to the stage. It was so great to see everyone at the booth. Thank you to everyone who stopped by to talk with the team. 👏

Hey product managers, do you know what's actually in your codebase? Spark does. Codebase analysis in Productboard now connects to GitHub, GitLab.com, Bitbucket Cloud, and Azure DevOps Services. Once your repos are connected, Spark can: ❓️ Answer technical questions about your product in seconds ✍️ Draft specs based on how your product is actually built 🏁 Flag existing APIs, permission checks, and edge cases before they surprise you mid-sprint Connect your repos: support.productboard.com/hc/…

how y'all sound this week

AI can summarize customer feedback in seconds. But can you trust that summary to inform your next product decision? Identifying common themes is just the beginning. Product teams need to understand which patterns are real, how widespread they are, which customers they affect, and how they connect to product strategy. As feedback volume grows, general-purpose GenAI tools often struggle to deliver that depth of analysis. In our latest blog, we explore six common challenges with AI feedback analysis, from context rot and disconnected data to weak traceability. Plus, what it takes to turn customer feedback into insights you can confidently act on. Read the full breakdown → productboard.com/blog/why-mo…

Spotting product opportunities shouldn't be a waiting game. Now, in Productboard, you can log a product idea and have Spark fill in the context—customer feedback, product strategy, competitive insights, and even how it fits into your roadmap. No more leaving your best ideas half-baked. Watch Nadia Kyle, Sr. Forward Deployed Engineer at Productboard, set up an opportunity in Productboard ⬇️

A shared visual can turn a complex idea into a shared understanding. Whether it’s a product capability or a system architecture question, sometimes the fastest way to get everyone on the same page is a diagram. Productboard CEO @hpalan explains.

On September 24, Productboard CEO @hpalan is taking to the main stage at the @PLEDalliance's Chief Product Officer Summit in San Francisco. He'll share AI lessons from the front lines of building Productboard Spark. Because every product leader is under pressure to “do AI," but few can separate what agentic AI reliably delivers from what still breaks in production. His keynote will dig into: 🔷 How to separate real gains from superficial AI productivity 🔷 What a dependable agentic PM system actually requires 🔷 Why “build it ourselves” is harder than it looks—and how to think about build vs. buy 🔷 What needs to be in place before you can safely increase product velocity with AI See you in San Francisco!

Need a specific piece of customer feedback? Stop digging. Just ask Spark. Say a customer flagged an issue with online ordering last month, but no one remembers which call it came from. Instead of scrolling through piles of feedback hoping to find it, just describe what you’re looking for to Spark. Spark can surface the relevant feedback, synthesize what it found, and link you directly back to the source. So whether you’re prepping for a QBR or backing up a prioritization decision, you can get to the actual voice of the customer faster. Learn more ⬇️

Your workspace should work the way you do. Now you can customize your Home navigation in Productboard to match your workflow. Move the sections you use most to the top, reorder items to your liking, and hide the ones you don’t need. Your setup saves automatically and follows you across devices, so the things you need are always where you expect them to be. See it in action → support.productboard.com/hc/…

Raise your hand if you've shipped an AI feature, felt good about it for a week, then watched two competitors ship the same thing ✋ That's just how it works now. Building fast stopped being the edge. It's becoming a battle for distribution: showing up in the right workflow, with the right context, at the moment someone actually needs it. Knowing which channel earns trust and which one is just noise. Join our very own Jordan Nolff for a live session with Marily Nika, Ph.D on exactly this on Wednesday, September 9th at 3pm ET. They'll cover 1️⃣How to build AI into a workflow that already exists instead of bolting it on 2️⃣ How to pick the channels and moments that actually drive adoption, and skip the ones that don't 3️⃣ How to move someone from "tried it once" to it actually becoming part of how they work RSVP ➡️ maven.com/p/8d2efb/ai-featur…

Your Skill worked perfectly yesterday. Today, something feels different. What changed? Now you can find out. With Skill version history in Spark, you can see what changed and when, browse previous versions, and roll back your own Skills when something doesn’t work as expected. It gives teams an audit trail as shared Skills evolve, so you can keep improving your workflows. Staff Product Manager Daniele Dominguez showcases it in action → support.productboard.com/hc/…

5 things you can do when you connect your coding tool to the Productboard MCP: 1. Prompt it to "Pull the spec I just wrote and build me a clickable prototype." 2. Ask "What's out of scope here?" before you start building on top of it. 3. Say "Add this to the spec: here's an edge case I just found" and have it write straight back in. 4. Push a comment back like "Should this handle partial refunds?" without leaving your coding tool. 5. Say "Mark this ready for engineering" once it's tested and the status needs to move. Now your specs keep up with you and your team, instead of getting stale the second the build starts. Learn more ➡️ support.productboard.com/hc/…

Sharing is caring. And now you can share your Spark chats with your colleagues. Great for the standup you have in 20 minutes, the handoff you're writing at 5pm, or the summary you'd otherwise paste into Slack line by line. It's opt-in rather than automatic, so you pick which chats become the team's reference point.

Celebrating summer and each other from San Francisco to Prague 😎

Catching up on product work post-vacation? Here's our team's AI workflow that makes figuring out where your product initiatives stand 1,000x easier.

A long call transcript with an important customer signal inside. Not enough time comb through it all. That’s exactly why we built AI Suggested Insights in Productboard. Spark automatically scans customer feedback and surfaces the moments worth paying attention to, without any prompting. Now, what may have taken an hour to digest takes just a few minutes. Nadia Kyle, Senior Forward Deployed Engineer, shows you how to use AI Suggested Insights to uncover what your customers really need ↓