Tech Product Lifecycle

𝗗𝗮𝘁𝗮 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗶𝘀𝗻'𝘁 𝗮 𝘀𝗶𝗻𝗴𝗹𝗲 𝗰𝗵𝗲𝗰𝗸 －it's a continuous contract enforced across the various data layers to avoid breakage. Think about it. Planes don’t just fall out of the sky when they land. Crashes happen when people miss the little signals that get brushed off or ignored. Same thing with data. Bad data doesn’t shout; it just drifts quietly—until your decisions hit the ground. When you bake quality checks into every layer and, actually use observability tools, You end up with data pipelines that hold up. Even when things get messy. That’s how you get data people can trust. Why does this matters? Bad data costs money → Failed ML models, wrong decisions. Good monitoring catches 90% of issues automatically. → Raw Materials (Ingestion)  • Inspect at the dock before accepting delivery.  • Check schemas match expectations. Validate formats are correct.  • Monitor stream lag and file completeness. Catch bad data early.  • Cost of fixing? Minimal here, expensive later.  • Spot problems as close to the source as you can. → Storage (Raw Layer)  • Verify inventory matches what you ordered.  • Confirm row counts and volumes look normal.  • Detect anomalies: sudden spikes signal upstream issues.  • Track metadata: schema changes, data freshness, partition balance.  • Raw data is your backup plan when things go sideways. → Processing (Transformation)  • Quality control during assembly is critical.  • Validate business rules during transformations. Test derived calculations.  • Check for data loss in joins. Monitor deduplication effectiveness.  • Statistical profiling reveals outliers and distribution shifts.  • Most data disasters start right here. → Packaging (Cleansed Data)  • Final inspection before shipping to warehouse.  • Ensure master data consistency across all sources.  • Validate privacy rules: PII masked, anonymization works.  • Verify referential integrity and temporal logic.  • Clean doesn’t always mean correct. Keep checking. → Distribution (Published Data)  • Quality assurance for customer-facing products.  • Check SLAs: freshness, availability, schema contracts met.  • Monitor aggregation accuracy in data marts.  • ML models: detect feature drift, prediction degradation.  • Dashboards: validate calculations match source data.  • Once data is published, you’re on the hook. → Cross-Cutting Layers (Force Multipliers)  • Metadata: rules, lineage, ownership, quality scores  • Monitoring: freshness, volume, anomalies, downtime  • Orchestration: dependencies, retries, SLAs  • Logs: failures, patterns, early warning signs Honestly, logs are gold. Don’t sleep on them. What's your job? Design checkpoints, not firefight data incidents. Quality is built in, not inspected in. Pipelines just 𝗺𝗼𝘃𝗲 data. Quality 𝗽𝗿𝗼𝘁𝗲𝗰𝘁𝘀 your decisions. Image Credits: Piotr Czarnas 𝘌𝘷𝘦𝘳𝘺 𝘭𝘢𝘺𝘦𝘳 𝘯𝘦𝘦𝘥𝘴 𝘪𝘯𝘴𝘱𝘦𝘤𝘵𝘪𝘰𝘯.  𝘚𝘬𝘪𝘱 𝘰𝘯𝘦, 𝘳𝘪𝘴𝘬 𝘦𝘷𝘦𝘳𝘺𝘵𝘩𝘪𝘯𝘨 𝘥𝘰𝘸𝘯𝘴𝘵𝘳𝘦𝘢𝘮.

The Medical Device Iceberg: What’s hidden beneath your product is what matters most. Your technical documentation isn’t "surface work". It’s the foundation that the Notified Body look at first. Let’s break it down ⬇ 1/ What is TD really about? Your Technical Documentation is your device’s identity card. It proves conformity with MDR 2017/745. It’s not a binder of loose files. It’s a structured, coherent, evolving system. Annexes II & III of the MDR guide your structure. Use them. But make it your own. 2/ The 7 essential pillars of TD: → Device description & specification → Information to be supplied by the manufacturer → Design & manufacturing information → GSPR (General Safety & Performance Requirements) → Benefit-risk analysis & risk management → Product verification & validation (including clinical evaluation) → Post-market surveillance Each one matters. Each one connects to the rest. Your TD is not linear. It’s a living ecosystem. Change one thing → It impacts everything. That’s why consistency and traceability are key. 3/ Tips for compiling TD: → Use one “intended purpose” across all documents → Apply the 3Cs: ↳ Clarity (write for reviewers) ↳ Consistency (same terms, same logic) ↳ Connectivity (cross-reference clearly) → Manage it like a project: ↳ Involve all teams ↳ Follow MDR structure ↳ Trace everything → Use “one-sheet conclusions” ↳ Especially in risk, clinical, V&V docs ↳ Simple, precise summaries → Avoid infinite feedback loops: ↳ One doc, one checklist, one deadline ↳ Define “final” clearly 4/ Best practices to apply: → Add a summary doc for reviewers → Update documentation regularly → Create a V&V matrix → Maintain URS → FRS traceability → Hyperlink related docs → Provide objective evidence → Use searchable digital formats → Map design & mfg with flowcharts Clear TD = faster reviews = safer time to market. Save this for your next compilation session. You don't want to start from scratch? Use our templates to get started: → GSPR, which gives you a predefined list of standards, documents and methods. ( https://lnkd.in/eE2i43v7 ) → Technical Documentation, which gives you a solid structure and concrete examples for your writing. ( https://lnkd.in/eNcS4aMG )

For the longest time, we all thought building the product was the hardest part, but that has changed significantly. With AI, products can be built, tested, and launched faster than ever before. Which means the real challenge now is no longer about can you build this? but about how do we get people to care about this? I've conducted many workshops with product builders - be it PMs, sales, engineers, and designers. When you ask who the product is truly for, what it meaningfully replaces, and why a customer would choose it over their current way of doing things, the answers are different. Sales will often describe competition based on recent deals. Product will frame it in terms of where the roadmap is headed. Marketing will respond to what the market appears to reward. And let's be honest, a user doesn't look at the product like that! So then, I ask this one question: If this product did not exist, what would the customer do instead? Would they rely on an existing tool? Would they create a workaround? Or would they continue with the status quo? Positioning, then, is not about describing the product in isolation. It is about defining it in direct relation to that default choice. It requires identifying the specific context in which the product creates a form of value that is immediately comprehensible to the customer it is intended for. And that specific context is especially helpful when the teams are building internally! Ofcourse, this narrows the scope more than teams are initially comfortable with, but it is precisely this specificity that creates clarity. Remember, it is not what you build that's the differentiator. It's how much clarity you have on it that separates you from the rest.

Is Product Positioning really a Marketing problem? Think Again. Let me share why positioning is fundamentally a CEO's responsibility, not just another marketing or sales initiative. 1. THE TRIPLE INSIGHT REQUIREMENT Effective positioning demands deep understanding of: - Customer pain points and aspirations - Competitive landscape dynamics - Company's long-term vision Only the CEO sits at the deepest intersection of all three. 2. WHY MARKETING ALONE CAN'T OWN IT Marketing teams excel at execution, but they: - Lack full competitive intel - Miss strategic board-level discussions - Don't have complete revenue visibility - Cannot make fundamental product decisions 3. WHY SALES CAN'T DRIVE IT EITHER Sales teams are closest to customers, but: - Focus on short-term wins - See only their territory view - Miss the broader market context - Cannot influence product roadmap 4. THE CEO'S UNIQUE POSITION The CEO is the only one who: - Holds all the strategic cards - Can align all departments - Makes final product decisions - Shapes company vision - Has complete market view 5. THE RIGHT APPROACH Success comes when: - CEO drives the positioning strategy - Marketing crafts the message - Sales validates with customers - Product delivers on the promise At PipeBagger, we've seen this pattern repeatedly. Companies struggling with positioning often have delegated it too far down the chain. Want to build authority in your market? Start by getting positioning right at the top. Interested in learning more about building market authority through strategic positioning? Let's connect. This is exactly what we help B2B founders achieve - turning their unique market position into sustainable growth. Positioning is a business strategy. Revenue is a business strategy. Sales is a revenue strategy. And so is marketing. #SaaS #RevenueGrowth #Positioning

The recent CrowdStrike update causing widespread outages is deeply troubling. With over 25 years of experience leading critical systems releases, I understand the challenges, but outages of this magnitude demand answers. Even the most talented programmers encounter defects, some frustratingly elusive. This is why robust quality assurance (QA) processes are an absolute necessity, especially for software entrusted with safeguarding our systems. Throughout my career, I've championed a multi-layered QA approach that acts as a safety net, scrutinizing software from every angle. This includes: ➡️ Code Reviews: Regular peer reviews by fellow developers identify potential issues early. ➡️ Testing Pyramid: A range of tests, from focused unit tests to comprehensive system and integration tests mimicking real-world use, are employed. ➡️ Stress and Capacity Testing: Pushing software beyond its normal limits helps expose vulnerabilities that might otherwise remain hidden. ➡️ Soak Testing: Simulating extended periods of real-world use uncovers bugs that only manifest under prolonged load. By implementing these techniques, QA teams significantly increase the likelihood of catching critical defects before they impact users. CrowdStrike owes its customers transparency. A thorough investigation and a clear explanation of how such a disruptive bug bypassed safeguards are crucial. Understanding this will help prevent similar incidents in the future. This outage serves as a stark reminder for both software providers and buyers. Providers must prioritize rigorous QA processes. But buyers also have a role to play. I urge all software buyers to carefully audit their vendors' QA practices. Don't settle for anything less than a robust and multi-layered approach. Our security depends on it. Our economy and indeed our life today, depends on software. We cannot allow this type of outage to disrupt us in the future! By prioritizing rigorous testing and demanding transparency, we can work together to ensure the software we rely on remains a source of security, not disruption. _______________ ➡️ About Me: I'm Talila Millman a fractional CTO and a management advisor, keynote speaker, and executive coach. I empower CEOs and C-suites to create a growth strategy, increase profitability, optimize product portfolios, and create an operating system for product and engineering excellence. 📘 Get My Book: "The TRIUMPH Framework: 7 Steps to Leading Organizational Transformation" launched as the Top New Release on Organizational Change 🎤 Invite me to Speak at your Event about Leadership, Change Leadership, Innovation, and AI Strategy https://lnkd.in/e6E4Nvev

While you were perfecting your product, your competitor already launched, dropped prices, and stole your users. Want to know how they moved faster? I have seen this happen too often. Teams spend months perfecting what they think is a breakthrough product. Meanwhile, a competitor quietly makes their move. They launch early. Adjust pricing to undercut the market. Flood ads that grab attention. By the time others react, the shift has already happened. But here’s the thing….these moves aren’t random. The signals are out there. You just need a system to spot them before they become headlines. This is how I do it. The growth hack: Build a competitive radar that never sleeps Manual tracking can’t keep pace today. I rely on AI-powered tools that scan constantly: -Crayon tracks product launches, pricing, and messaging updates in real time -Kompyte by Semrush monitors campaigns, website changes, and hiring patterns that hint at future priorities -Similarweb reveals traffic spikes, shifting audiences, and emerging channels early With these, I don’t just stay informed, I see where the market is heading. Turning signals into action faster Having data is one thing. Acting before anyone else? That’s the edge. I use ChatGPT with a simple prompt: “Analyze competitor activity. Find three patterns and suggest counter strategies for a SaaS company.” It helps me cut through noise and get to clear next steps. When this becomes your system: -Spot competitor moves 3–6 months early -Adjust pricing or features before market shifts -Launch campaigns to lead, not react To make it stick: -Set up automated alerts -Assign owners for each signal -Review trends weekly and act fast Data alone isn’t power. Acting first is. #AI #GrowthHacks #ProductStrategy #CompetitiveIntelligence

𝗬𝗼𝘂𝗿 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗜𝘀𝗻’𝘁 𝗕𝗼𝗿𝗶𝗻𝗴—𝗬𝗼𝘂𝗿 𝗣𝗼𝘀𝗶𝘁𝗶𝗼𝗻𝗶𝗻𝗴 𝗠𝗶𝗴𝗵𝘁 𝗕𝗲. I once worked with a client who sold notebooks. Plain, brown, recycled-paper notebooks. And he came to me saying, Geeta, I don’t know how to market this. It’s just… a notebook. But here’s the thing—products aren’t born boring. They’re just misunderstood. We flipped the script: • Not just a notebook → a mindfulness tool • Not just recycled paper → zero-guilt creativity • Not just stationery → a daily reset button We sold the emotion, not the object. The identity, not the item. Six months later? He had built a cult-like customer base that didn’t just buy notebooks—they told stories about them. This applies beyond business. Your skills, your brand, your offers— They’re not boring. You might just be telling the wrong story. Positioning isn’t about exaggerating. It’s about uncovering what already makes you valuable, and leading with that. Because in a noisy world, how you say something is as important as what you’re saying. What’s something you thought was “boring”… until you looked at it differently?

MULTI-LEVEL QUALITY CHECKLIST: DAILY TASKS FOR INSPECTION, CONTROL, AND ASSURANCE LEVEL 1: Operator / Technician Level Focus: Task Execution & Self-Inspection Conduct equipment/tool pre-checks before starting work Verify correct raw materials or components are used Perform visual inspection for defects (scratches, contamination, etc.) Carry out first article inspection at the start of production Record process data and inspection results accurately Report any abnormalities, deviations, or non-conformities immediately LEVEL 2: Supervisor / Line Leader Level Focus: Process Monitoring & Quality Control Perform random spot checks on product quality throughout the shift Verify machine settings and process parameters at shift start Review and validate operator logs for completeness Monitor for trends or recurring defects Initiate corrective actions for any process or product issues Provide regular feedback and quality reminders to team members LEVEL 3: Quality Control (QC) / Inspection Team Focus: Product Verification & Defect Prevention Inspect incoming raw materials or components against specifications Conduct in-process inspections during production runs Perform final product inspections before packaging or shipping Check calibration status of measuring and inspection equipment Log and escalate all non-conformances using NCR forms Analyze daily quality data for trends or high-risk issues LEVEL 4: Quality Assurance (QA) / Management Level Focus: System Oversight & Continuous Improvement Audit production and QC records for compliance Review daily quality performance metrics (e.g., defect rates, yield) Track and address customer complaints and feedback Review process data to identify improvement opportunities Follow up on CAPAs to ensure resolution and effectiveness Confirm training and certification status of staff is up to date

The most important element of your positioning strategy is the use case you choose. A quick definition: Use Case — workflow(s) performed by potential customers that could be supported by your product The "width" of your use case determines your positioning strategy. If you position for a very narrow use case, the competitive alternatives and your differentiation will be very different than if you position for a very broad use case. When a company like Lavender 💜 says they can help SDRs "write better emails" (i.e. the use case), they are positioning AGAINST writing emails manually and showing how their AI email coach drives better reply rates. If you position for a very wide use case, your competitive landscape changes — and should your differentiation strategy. When Apollo.io says they are "the only solution you need to run a world-class sales organization," they are trying to own the end-to-end workflow/use case of "doing sales." Obviously, this a HUGE set of workflows that are accomplished by a variety of tools, manual processes, etc. And so they must back up their claim with strong product differentiation and social proof. A few takeaways: → If you own a wide use case that is very important to companies, you can command a higher ACV... yet your market is likely "smaller" in the true TAM sense. This is the problem with software companies relying too heavily on marquee design partners in the early days. They can end up functioning as high-paid consultants building software that serves one enterprise and one enterprise alone. → If you own a very narrow use case, your target market is likely "larger" in the pure TAM sense... though you'll likely need to take a more PLG approach with a lower ACV. → There is huge success to be found in positioning on very narrow use cases AND very wide use cases, as demonstrated from the diagram below. Additionally, being most known for a narrow use case (i.e. with a company like Gong being known for call recording) does not mean you can't also cover adjacent use cases. The diagram below does not fully summarize what all these companies CAN do... it's simply a quick stab at what most people associate with them.

If I had to start my QA career all over again in 2025... I’d do it completely differently. When I started, I thought QA was just about “breaking things.” Now I know — it’s really about understanding how things break, and why. So here’s exactly how I’d begin today 👇 🔹 Step 1: Learn what “Quality” actually means It’s not about perfection — it’s about trust. Learn validation vs verification. Ask: “Does it work?” Then ask: “Would I use it?” — that’s the real test. 🔹 Step 2: Get your toolkit right Forget trying to learn everything. Start with: 🧠 Jira / Confluence — for structure 🧪 Postman — for APIs 🧰 Git & GitHub — for collaboration 🌐 Cypress / Playwright — for automation (you’ll thank yourself later) 🔹 Step 3: Understand Testing Types Manual ➡️ Integration ➡️ Regression ➡️ E2E Then peek into TDD and BDD — it’s like learning how devs think (and argue 😅). 🔹 Step 4: Design isn’t “extra” Learn Figma. The best QA engineers don’t just click buttons — they question user logic. (“Wait… why is the ‘Cancel’ button red?” 🤔) 🔹 Step 5: Grow with advanced tools Appium → Mobile testing JMeter → Performance Docker → Environment setup Cucumber → BDD Zephyr → Test management ✨ Bonus wisdom: Anyone can test features. But real QA engineers test assumptions. That’s where true product quality begins. 💬 If I were mentoring a fresher today, I’d tell them — Don’t chase tools. Chase clarity, communication, and critical thinking. Those are the skills AI can’t replace.