Focus on the core problem, not the possibilities.

Product-market fit isn’t something you find. It’s something you fight for, and fight to keep. There’s no magic “click” moment where everything just works Slack started as a tool for internal chat, inside a failing game studio. →The game died. ↳The chat tool survived. That pivot wasn’t glamorous. It was survival. And it became their inflection point. Marc Andreessen once said: “You can always feel when product-market fit isn’t happening. The customers aren’t quite getting value.” That feeling? Even when growth looks “good on paper.” So we have to stop chasing a finish line. And focus on the friction. Because product-market fit isn’t a moment. It’s a moving target. Agree? #ProductMarketFit #StartupTruths #BuildInPublic #SlackStory #NoFinishLine 🔗📲 Follow me, Viktor Shumylo, for more real-life stories on the hustle of immigration, insights on Strategy, AI Products, and Operational Management! 📣 And don't hesitate to repost it, so your network can benefit from these insights too

Busy IT work is a hidden tax on your product velocity 🤖 Busy work in IT isn’t a badge of hustle. It’s a tax on speed—and founders are paying it every sprint. 🤖 At Quadcode, I’ve watched AI take routine ops off engineers’ plates so they can build revenue features, not babysit tickets. As acting GM&CCO (and a former head of RevOps), I care about time-to-value, not dashboards. The fastest path I’ve seen to compound gains is removing toil. Personal example: in one quarter we deployed an L1 triage bot + auto-remediation playbooks and cut ticket volume 38% within 60 days. The culture shift was bigger than the savings. Where to start if you’re a SaaS, FinTech, or MarTech team running lean: • Ticketing: classify, route, and answer FAQs from a vetted KB; escalate only when signals are ambiguous. • Monitoring: event correlation + self-heal scripts before paging a human. • Deployments: canary + rollback by policy; humans approve exceptions. • Onboarding/offboarding: zero-touch provisioning, RBAC by role, audit trails by default. • Environments: ephemeral test stacks spun up from IaC and nuked on merge. Make it an operating system, not a tool spree. Set owners, guardrails, and SLAs, and measure business impact (lead time, change failure rate), not bot vanity metrics. 🛠️ Common traps: automating chaos (fix processes first), shadow tooling, and “no human in the loop.” Keep a clear override path and postmortems. The upside is immediate: most teams can free 20–30% of engineering capacity and pull roadmap left while de-risking releases. Finance will see it in gross margin; Product will feel it in cycle time. That’s growth fuel, not cost-cutting. 🚀 Curious how you’re approaching this in your org? Comment below with your thoughts!

I've known Tyler for a long time and believe this webinar will be a great use of time. As a product manager, I find it difficult to get our various teams to implement AI faster. Despite AI being critical in every modern day's business, the implementation can be tricky. Development team's may be too backed up with customer and feature requests to drop everything and focus on AI initiatives for months. Even if you are able to focus on AI, no progress may be seen for months due to its complicated development nature. Voker is empowering product managers and engineers to create AI-powered technologies more efficiently. If you're interested in better leveraging AI and are experiencing similar issues that I mentioned, this could be for you!

Ever felt like the tools you're using are holding you back more than helping? One game-changer most people overlook: discovering early-stage products before they go mainstream. Here’s how finding fresh tools first has transformed the way I work: - I get access to cutting-edge features before competitors. - I often provide feedback directly to founders, helping shape the product to fit real-world needs. - I stay ahead of the efficiency curve, always optimizing my stack. Early-stage products may not be perfect — but that's where the magic happens. You experiment, iterate, and often find surprisingly powerful solutions before anyone else. Exploring new tools has become part of my weekly routine. Platforms like Aura++ make that so much easier. Discover what’s launching today → https://auraplusplus.com How are you finding and testing new tools in your workflow? Let’s compare notes. #Productivity #EarlyAdopters #WorkflowTools #StartupTools #ProductLaunches #TechForProfessionals

🚨 The Silent Killer in Growth: Onboarding Drop-offs Every growth team asks the same question: 👉 “Why are users leaving before finishing onboarding?” The painful truth: - Teams spend 20+ hours/week digging through analytics - Insights arrive too late (after users are already gone) - Most “technical errors” turn out to be confusing UX That’s the problem I’m tackling at the AI Agent Hackathon (by Product Space). Day 1 Progress: - Discovered Mockaroo (first time—mind officially blown) → spun up realistic mock user data - Locked in the workflow + tech stack (for now…subject to change, because that’s how I roll 😅) - Scrapped a time-sink idea: building a website + PostHog integration—thankfully ditched it early, working with mock dataset now - Ended the day finalizing workflow and mock dataset. Progress, but fully aware tomorrow could upend it. Key insight: Even synthetic data reveals onboarding friction. The trick isn’t perfect data—it's spotting what signals matter. ⏭ What’s next? Day 2: Building the agent’s brain. Plugging in the workflow automation. Let’s see if it actually works. Your turn: If you had an AI agent to debug onboarding flow, what’s the first problem you'd ask it to solve? Drop suggestions—I’ll feed them straight into the build. #AIAgentHackathon #ProductSpace #BuildInPublic #NoCode #AIAgents #HackathonLife #UXResearch #SyntheticData

A/B test saved my roadmap. +18% usage in 10 days-data beats opinions every time. Here’s what happened ↓ We planned a new dashboard for our EdTech platform. Everyone had a strong view on “the best layout.” → Designers wanted clean. → Sales pushed for more features. → I thought we needed better onboarding. Daily active use stayed flat.  That’s the signal I watch. So, the approach? ↳ Testing, not guessing. We set up a simple A/B test: → Version A: Minimal design, fast onboarding → Version B: Feature-heavy, lots of tooltips Talked to dozens of users. Checked heatmaps. Tracked every click. After 10 days: → Version A: +18% usage → Version B: No change That’s it. No debate. No “gut feeling.” The data spoke. We killed Version B. Shipped the winner. From this simple truth: 𝐄𝐯𝐞𝐫𝐲 𝐫𝐨𝐚𝐝𝐦𝐚𝐩 𝐟𝐢𝐠𝐡𝐭 𝐢𝐬 𝐣𝐮𝐬𝐭 𝐧𝐨𝐢𝐬𝐞 𝐮𝐧𝐭𝐢𝐥 𝐲𝐨𝐮 𝐬𝐞𝐞 𝐭𝐡𝐞 𝐧𝐮𝐦𝐛𝐞𝐫𝐬. Lesson? ↳I trust the process, not my pride. It’s hard, but it works. Now, I try A/B test every feature I can. Saves time. Saves money. Builds trust with the team. Thoughts? #ProductManagement #ABTesting #DataDriven #ProductStrategy #StartupLife #Growth #BuildMeasureLearn #Execution #ProductDesign #LeanStartup 🔗📲 Follow me, Viktor Shumylo, for more real-life stories on the hustle of immigration, insights on Strategy, AI Products, and Operational Management! 📣 And don't hesitate to repost it, so your network can benefit from these insights too

Remember when everyone agreed "ideas are worthless without execution"? We're about to learn the same painful lesson with prototypes. A working prototype without strategy is just a prettier idea. No go-to-market plan. No customer understanding. No distribution thinking. Just a thing that looks real but isn't. The dangerous part is that live prototypes create fake momentum. They feel tangible. They demo well in meetings. Everyone gets excited. Meanwhile, you're not actually any closer to building a business. I'm already seeing this with folks in my network: ↳ Beautiful AI-generated apps that no one uses ↳ Perfect prototypes solving problems no one has   ↳ Weeks spent polishing demos instead of talking to customers My prediction is that in 6-12 months, we'll see a wave of "why did our prototype fail to convert" post-mortems. We're skipping the unglamorous work that makes prototypes valuable. The customer conversations that reveal what actually needs building. The domain expertise that spots real problems. The market understanding that separates nice-to-haves from must-haves.

🔥 Day 1/5: Diving into another #Sprint with Product Space—this time, we're trading ideas for shipped impact. 🚀 Great PMs don’t chase trends—they chase outcomes. I’m teaming up with ANWESH BELLAMKONDA and going all-in on a real, pressing problem for the next #5 days—building openly, iterating daily, and leveraging AI end-to-end. Problem we’re solving: Young professionals juggle expenses across multiple apps, SMS alerts, and scattered bank statements. Insights feel vague, budgets get blown, and savings are delayed. Our solution: A smart, unified finance tracker that seamlessly auto-pulls your bank & SMS data, effortlessly auto-categorizes spending, and gently nudges at the perfect time (“You’re at 80% of your food budget, ease up!”). Target impact: +35% budget adherence, +20% savings. My personal sprint goals: Laser-focused product thinking: user clarity → precise problems → ruthless prioritization. Rapid hypothesis testing: prototype fast, measure immediately, iterate openly. Radical transparency: daily updates, visible progress, public accountability. If you’re curious about how PMs at the top 1% build—from insight → to solution → to real-world prototype, follow closely. Each day matters, every build counts. Let’s get building. 🚀 ANWESH BELLAMKONDA #ProductSpace #BuildInPublic #ProductManagement #Fintech #AI #Sprint

The stages of every product launch 10/10 visualization hahah POV: "You're a founder. You successfully raised from VC. Do you think you nailed your value proposition and positioning? There is one serious mistake that tech companies make. In their minds, how they pitch their product to investors and how they sell it to customers are the same. But they are not. Why? When pitching to investors, founders are expected to sell the vision ✨ Convince a group of skeptics that they are the ones who will grow to $100M ARR very quick. All works towards this goal: they are selling the 𝗙𝗜𝗡𝗔𝗟 vision of the product, showing how big is the market and how customers lie awake in the night dreaming of buying their solution. Founders are selling the future, what they will become when they grow up 👦 In reality? The product is often in the early stage and it can't do all that you promised to investors. When users try it, they quickly find out that your 'data powerhouse rocketship' is just a buggy, scrappy MVP. And they leave. Your positioning, messaging and value prop for users should be focused on 𝗣𝗥𝗘𝗦𝗘𝗡𝗧. What your product can do today that solves my problem? Why should I choose you over alternatives NOW? If it's valuable to me, I will buy it." Too too funny and accurate haha

𝗔𝗜 𝗵𝘆𝗽𝗲 𝗶𝘀 𝗲𝘃𝗲𝗿𝘆𝘄𝗵𝗲𝗿𝗲. 𝗧𝗵𝗲 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝘁𝗵𝗮𝘁 𝘄𝗶𝗻 𝘄𝗶𝗹𝗹 𝗽𝗿𝗼𝘃𝗲 𝗶𝗺𝗽𝗮𝗰𝘁. That was the signal from Blackbird’s Collisions conference a sharp, hands-on day with operators who are actually building. The consensus was clear: AI can’t just be a bolt-on. The companies that thrive will weave it into their core workflows to make life radically simpler for customers. At Cotiss, that means listening closely to where customers want a human in the loop, and designing workflows that reduce cognitive overload while keeping the decision points that really matter. A few themes that stuck with me:  • 𝗦𝗽𝗲𝗲𝗱 𝗼𝘃𝗲𝗿 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀. Endless functionality doesn’t win. Fast, reliable change does. The teams investing in continuous deployment, strong DevOps culture, and AI-assisted development are the ones staying in sync with customer needs.  • 𝗥𝗲𝘀𝘂𝗹𝘁𝘀 𝗼𝘃𝗲𝗿 𝗹𝗮𝗯𝗲𝗹𝘀. Nobody cares if you’re “AI-native.” They care if you help them save ten hours, cut real costs, and reduce risk. Measurable outcomes beat marketing claims every time.  • 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀 𝗵𝗼𝗹𝗱. The tech is racing ahead, but the basics haven’t changed: listen harder, move faster, focus on the outcomes that matter most to your customers. For me, conferences like Collisions are less about new buzzwords and more about clarity. They remind us that execution, customer obsession, and measurable results are what separate noise from progress. Thanks to the Blackbird team for pulling together a day that cut through the hype and went straight to the signal.