Tech Product Management

🏗 How To Tackle Large, Complex Projects. With practical techniques to meet the desired outcome, without being disrupted or derailed along the way ↓ 🤔 99% of large projects don’t finish on budget and on time. 🤔 Projects rarely fail because of poor skills or execution. ✅ They fail because of optimism and insufficient planning. ✅ Also because of poor risk assessment, discovery, politics. 🎯 Best strategy: Think Slow (detailed planning) + Act Fast. ✅ Allocate 20–45% of total project effort for planning. ✅ Riskier and larger projects always require more planning. ✅ Think Right → Left: start from end goal, work backwards. ✅ For each goal, consider immediate previous steps/events. ✅ Set up milestones, prioritize key components for each. ✅ Consider stakeholders, users, risks, constraints, metrics. 🚫 Don’t underestimate unknown domain, blockers, deps. ✅ Compare vs. similar projects (reference class forecasting). ✅ Set up an “execution mode” to defer/minimize disruptions. 🚫 Nothing hurts productivity more than unplanned work. Over the last few years, I've been using the technique called “Event Storming” suggested by Matteo Cavucci to capture user’s experience moments through the lens of business needs. With it, we focus on the desired business outcome, and then use research insights to project events that users will be going through towards that outcome. On that journey, we identify key milestones and break user’s events into 2 main buckets: user’s success moments (which we want to dial up) and user’s pain points or frustrations (which we want to dial down). We then break out into groups of 3–4 people to separately prioritize these events and estimate their impact and effort on Effort vs. Value curves (https://lnkd.in/evrKJUEy). The next step is identifying key stakeholders to engage with, risks to consider (e.g. legacy systems, 3rd-party dependency etc.), resources and tooling. We reserve special timing to identify key blockers and constraints that endanger successful outcome or slow us down. If possible, we also set up UX metrics to track how successful we actually are in improving the current state of UX. When speaking to business, usually I speak about better discovery and scoping as the best way to mitigate risk. We can of course throw ideas into the market and run endless experiments. But not for critical projects that get a lot of visibility — e.g. replacing legacy systems or launching a new product. They require thorough planning to prevent big disasters and urgent rollbacks. If you’d like to learn more, I can only highly recommend "How Big Things Get Done" (https://lnkd.in/erhcBuxE), a wonderful book by Prof. Bent Flyvbjerg and Dan Gardner who have conducted a vast amount of research on when big projects fail and succeed. A wonderful book worth reading! Happy planning, everyone! 🎉🥳

I’ve been working as a contractual Program/Project Manager on complex projects for the past 7 years, most of which followed Agile methodologies. While the Software Development Life Cycle (SDLC) is designed to reduce risk, poor implementation can have the opposite effect. If not executed properly, it significantly increases the risk of project failure. Here’s a quick ranking of critical failure points that commonly derail software projects: 🔴 1. Unclear or Changing Requirements Poorly defined needs or constant scope changes break alignment early and often. ✅ Fix: Involve stakeholders early, use user stories and clarify DoD (definition of done), and validate frequently; another advice: make sure to define change request in the initial contract with the client. 🔴 2. Inadequate Planning & Estimation Unrealistic timelines or budgets create pressure that leads to shortcuts and burnout. ✅ Fix: Buffer for unknowns, involve tech leads in estimation. 🟠 3. Ineffective Communication Team silos and misalignment cause costly rework and delays. ✅ Fix: Daily stand-ups, shared documentation, clear ownership. The tech team needs to understand the functional requirement to be able to implement it technically. 🟠 4. Weak Design & Architecture Hasty or shortsighted technical decisions lead to rework and scalability issues. ✅ Fix: Involving a software architect who could support drafting the best scalable architecture choices within the available projects needs, constraints and budget 🟠 5. Insufficient Testing & QA Testing cut short = bugs in production, bad UX, security holes. ✅ Fix: Invest in a QA strategy to identify tests to be run by type of release, and automate critical time-consuming tests 🟡 6. Lack of Stakeholder Involvement Software built in isolation rarely meets business goals. ✅ Fix: Demo regularly (ideally after each milestone), build feedback into the cycle. 🟡 7. Poor Change & Config Management Inconsistent environments and chaotic updates derail progress. ✅ Fix: Version control, CI/CD, and clear change protocols. 🟡 8. Inadequate Risk Management Unexpected issues become blockers when risks aren't flagged early. ✅ Fix: Ongoing risk logs, contingency planning. 🟢 9. Neglecting Post-Launch Support No plan for support = user churn and poor adoption. ✅ Fix: Monitor performance, address issues fast. 🟢 10. Lack of DevOps & Automation Manual processes delay releases and increase error rates. ✅ Fix: Embrace CI/CD and infrastructure-as-code. Strong software isn’t just about great code—it’s about clarity, communication, and continuous feedback. A strong Project Manager implements the right processes and follows each step methodically to spot weak links early and address them proactively. And when issues do arise (as they often do), they stay calm, communicate transparently, and ensure all stakeholders remain aligned throughout the journey. #SoftwareDevelopment #SDLC #TechLeadership #ProjectManagement #Agile #DevOps #ProductDelivery

It was 9:00 AM on a Tuesday in an Abu Dhabi high-rise. I was staring at a methodology binder thick enough to prop open a fire door. The PMO had dedicated tooling and an entirely certified team. But 12 of their last 15 projects had missed their delivery dates. I spent the first week reading their status reports. They were immaculate... ...and completely useless. Every project stayed green right up until the day it crashed. Earlier in my career, I thought a heavy methodology guaranteed execution. I believed a clean status report meant the project was healthy. I chose the safety of the template over the haqeeqat (ground reality) of the work. This month, I was diagnosing another stalled enterprise portfolio. And I realized that massive organizations do the exact same thing. We reward teams for looking good instead of being useful. Nobody gets credit for raising an early flag. They get credit for keeping their lane clean. When your culture teaches people to protect the report instead of the project, your PMO fails. It becomes a highly paid administrative burden. You must fix the incentives before you redesign the process. Here is the playbook we use to rebuild PMO culture: 𝐑𝐞𝐰𝐚𝐫𝐝 𝐭𝐡𝐞 𝐄𝐚𝐫𝐥𝐲 𝐑𝐞𝐝: Stop punishing PMs who report delays. Actively praise the first person to flag a blocker during the steering committee. Punishing early warnings guarantees catastrophic late-stage failures. 𝐊𝐢𝐥𝐥 𝐭𝐡𝐞 𝐆𝐫𝐞𝐥𝐥𝐨𝐰 𝐒𝐭𝐚𝐭𝐮𝐬: A project is either on track or it is at risk. Ban hybrid reporting colors that soften the truth. Allowing ambiguous statuses lets failing projects hide until they are unrecoverable. 𝐀𝐮𝐝𝐢𝐭 𝐟𝐨𝐫 𝐀𝐜𝐭𝐢𝐨𝐧: Do not review a status report for its formatting. Review it for the management decisions it forces. A beautiful report that triggers no executive action is just expensive typing. You cannot fix a culture of fear with a new software tool. Whether it is a global enterprise portfolio, or a heavy binder in Abu Dhabi. Khallas.

Stop Projects Disasters Before they Start A lot of projects don’t fail halfway. They start failing even before they even begin. I’ve seen it. You’ve probably seen it too. A “sure shot” project falls apart in slow motion. I was talking to my coachee Dan, a senior executive of a mid-sized Company. Six months earlier, he led a software migration for his finance team. He had executive buy-in. A solid vendor. A realistic timeline. Three weeks before launch, his CFO casually mentioned she needed two extra weeks to train her team. Nobody had planned for that. The answer isn’t more meetings. Or more planning. Smart teams anticipate problems. Here’s what actually works. Run a premortem. Get your team in a room. Ask one question: “It’s six months from now. The project failed spectacularly. What could have gone wrong?” Set a timer for 15 minutes. Write down all the ideas generated. You’ll hear things like: “The vendor’s software can’t handle our data.” “Legal never approved the contract in time.” “Sarah left and took all the core knowledge with her.” These aren’t random worries. They’re signals your team has already noticed but never voiced. Smart teams don’t just plan for success. They prepare for failure too. So try this tomorrow. Pick your biggest upcoming project. Set a 15-minute timer. - Ask your team to list every way it could fail. You could also run an AI model trained on projects executed earlier, to predict likely challenges. You’ll spot the real risks hiding behind your optimism. And you’ll fix them or have a risk mitigation plan before they derail everything. The best project wins? - They’re the disasters no one ever anticipated — because you stopped them early.

Last week I presented on a panel at True Blue Blazing. The subject was Lessons Learnt from the worst projects ever.   Many people told us that they would have loved to know more so here is a quick checklist of what to do if you want your next project to succeed.   1. Don’t do it on the cheap Trying to save money by using volunteers, interns, or in-house staff who’ve never touched Salesforce before is the fastest way to triple your costs later. DIY might work for flat-pack furniture, but not for enterprise technology. If you think hiring an expert is expensive, try hiring an amateur.   2. Don’t put all your eggs in one basket The classic “Train the Trainer” trap: one super-user attends training because “everyone’s busy,” and then they leave. Suddenly, no one knows how the system works, and all the process knowledge walks out the door. Spread training across all users. Document everything. Set yourself up for success.   3. Measure seven times, cut once Discovery isn’t a luxury — it’s insurance. Spend time in the problem - don’t jump right into solutions Projects that skip proper discovery and stakeholder engagement end up rebuilding halfway through. Invest the time upfront. It’s cheaper than rework later.   4. Clear ownership When everyone thinks someone else owns it, no one really does. Projects without a captain drift — decisions stall, priorities conflict, and accountability disappears. Assign clear ownership and decision-making authority from day one.   5. Executive Buy-In If leaders aren’t visibly aligned, teams won’t be either. Mixed messages from leadership create confusion and kill adoption. When executives sing from the same hymn sheet, everyone else learns the tune.   6. Check Credentials Choosing a partner or consultant based purely on price is a false economy. Choosing the right implementation partner or consultant is one of the biggest success factors in any digital transformation project. Price does matter, but value, experience, and fit matter far more. Check credentials, reference check as you would an employee, and make sure they have current happy customers who can vouch for them.   The Moral of the Story   Every failed project leaves clues. If you don’t learn from them, you’re destined to repeat them.   Because projects don’t fail — people let them.

We analyzed 70 Salesforce Commerce Cloud implementations. Only 4% achieved their promised ROI within Year 1. The difference wasn't budget, team size, or timeline. It was these 5 overlooked decisions: **1. Starting with Reference Architecture (96% success rate)** Brands that customized the Reference Architecture instead of building from scratch went live 3x faster with 60% fewer bugs. **2. API-First Integration Strategy** → Failed projects: Point-to-point integrations → Successful projects: API management layer from Day 1 Cost difference: $50K upfront, saves $500K in Year 2 **3. Phased Migration vs. Big Bang** Success rates: - Big Bang approach: 23% - Phased migration: 87% The catch? Phased takes 2 months longer but delivers value in Week 3. **4. Performance Budget Before Development** Teams that set a performance budget (2.5s page load, 500ms API response) BEFORE development achieved: - 40% better Core Web Vitals - 22% higher conversion - 50% less refactoring **5. The "Boring" Stack Wins** Successful implementations used: - OOTB features for 80% of requirements - Custom code only for competitive differentiation - Standard integrations over custom APIs - Proven patterns over latest trends The brutal reality: Every "innovative" architecture decision that failed cost an average of $400K to fix. Your stakeholders don't want innovation. They want predictable revenue growth. My advice after 10 years and 100+ implementations: Be boring with your foundation. Be innovative with your business logic. Be ruthless with your performance metrics. Save this checklist for your next SFCC project: ☐ Start with Reference Architecture ☐ Design API layer first ☐ Plan phased approach ☐ Set performance budget ☐ Default to OOTB What's your most expensive architecture mistake? 👇

Most common obstacle in mega projects - scope creep and stakeholder misalignment, and how data centers can proactively avoid it build at scale. The Core Obstacle: Scope Creep & Stakeholder Misalignment, Why? • Multiple stakeholders with competing priorities: Owners, tenants, investors, regulators, and community partners often have divergent goals. • Compressed timelines: In high-demand sectors like hyperscale data centers, speed-to-market pressures can lead to premature design freeze or rushed procurement. • Evolving technology and regulations: Shifts in cooling strategies (e.g., liquid cooling), AI/ML workloads, or ESG mandates can disrupt previously agreed-upon designs. • Lack of integrated governance: Without a unified decision-making framework, changes are made in silos, leading to rework, delays, and budget overruns. How Data Centers Can Avoid This 1. Front-End Loading (FEL) with Scenario Planning • Conduct multi-scenario modeling during FEL 2 and FEL 3 stages to anticipate future capacity, cooling, and power demands. • Use digital twins to simulate performance under different load profiles and tenant mixes. 2. Owner Requirements Document (ORD) as a Living Contract • Treat the ORD not as a static document but as a governance tool with version control, traceability, and sign-off protocols. 3. Change Management with Predictive Impact Modeling • Implement a Change Impact Matrix that quantifies downstream effects of any scope modification—on schedule, cost, risk, and operations. 4. Integrated Project Controls with Real-Time Dashboards • Align cost, schedule, procurement, and risk data in a single pane of glass using platforms like Oracle Primavera, InEight, or Procore. • Establish early warning indicators (e.g., procurement slippage, RFI backlog) to trigger proactive interventions. 5. Governance Architecture with Tiered Decision Rights • Define a RACI matrix (Responsible, Accountable, Consulted, Informed) for every major decision node. • Empower a Program Management Office (PMO) or Project Integration Team to act as the “glue” across design, construction, and operations. 6. Progressive Commissioning and Operational Integration • Shift from “end-loaded” commissioning to progressive commissioning tied to construction milestones and Involve operations and facilities teams from Day 1 for effective integration. Cultural and Leadership • Psychological safety: Encourage teams to raise red flags early without fear of blame—this is critical in high-stakes, high-speed environments. • Leadership alignment: Senior executives must model cross-functional collaboration and resist the temptation to “fast-track” decisions without full impact analysis and missing the Lessons learned loop to improve the project deliveries. Final Thought: In the high-velocity world of data center delivery, the antidote to scope creep isn’t rigidity—it’s disciplined agility. The most successful teams build adaptive frameworks that allow for change without chaos.

Most LangChain projects fail at the exact same moment: the first real user. The demo works. The notebook looks clean. Then reality hits—messy questions, missing context, inconsistent outputs, and zero visibility into what broke. LangChain’s real value isn’t “chaining prompts.” It’s using it as an LLM application framework—so you can ship something that survives production. What it helps you orchestrate (reliably): Prompts (structured, testable, reusable) Retrieval (RAG) (ground the model in your data) Tools/APIs (actions, workflows, real integrations) Memory (state where it’s actually needed) Tracing + evaluation (debugging and iteration with evidence) If you’re starting, this rule prevents 80% of rookie mistakes: Chains first. RAG next. Agents last. Before you build, answer these three questions: What must be retrieved vs what can be generated? How will you trace failures end-to-end (inputs → retrieval → prompt → output)? What’s your evaluation metric (accuracy, faithfulness, usefulness, latency, cost)? Are you using LangChain more for RAG or agents right now—and what’s the one thing breaking most often in your pipeline? #decodingdatascience #dds #LangChain #LLM #RAG #AIAgents #GenAI #MLOps #AIEngineering

Every billion-dollar data center begins long before construction starts. But the real timeline opens the moment a site is identified… Because that’s when zoning, environmental reviews, interconnection studies, and community approvals begin. These steps decide whether a project advances or stalls. A few factors define who succeeds: 1. Permitting clarity: Jurisdictions with predictable zoning and environmental timelines. 2. Interconnection feasibility: Utilities able to commit capacity without multi-year studies or upgrades. 3. Equipment procurement: Transformers, switchgear, generators, and cooling with long lead times locked in early. 4. Commissioning discipline:  System-level tests that validate redundancy, load transitions, and operational readiness. Developers that deliver on schedule have a structural advantage. Tenants plan capacity to the month. Lenders price certainty. Missed milestones cost far more than construction overruns. The model is shifting toward standardized designs, modular electrical rooms, early procurement, and deeper partnerships with utilities and regulators. Data centers are no longer built around steel and concrete they’re built around timelines, permits, and equipment availability. Whoever controls those variables controls delivery. Read the article below #datacenters

No offence intended when I say that I won't build anything on Salesforce until the business process is End-to-End Orchestrated and agreed on by all concerned teams. It’s tempting to start with screens, fields, and automation. But if the business process of how users will be employing the platform is not defined and agreed on, then 100 things can go wrong. 👉 Teams realise they had different expectations, features must be reworked or dropped. 👉 New requests keep popping up because the full picture wasn’t discussed earlier. And everything will be a top priority 👉 Handoff between the teams is not well defined, leading to confusion on who does what and when. 👉 Flows and code built on incomplete logic start failing 👉 Rework takes time. Missed scenarios need extra dev cycles, which weren’t planned for. 👉 The biggest fallout "Low User Adoption" - When the system doesn’t match how people actually work, they avoid using it, or create workarounds. But if the business owners are adamant about getting started without the process mapping, then you have to push back 👉 Don’t Rush to Build - inform the drawbacks of starting without proper process mapping. 👉 Request for a Workshop with all teams - Bring all key stakeholders into the same room. Walk through the process, start to finish. 👉 Document the End-to-End Flow - Create a simple process map. Highlight handoffs, pain points, and decision points. 👉 Ask for confirmation of agreed flow via a process map - Once aligned, get buy-in via email or shared doc. This avoids future backtracking. 👉 Translate Process to designs and to Salesforce feature mapping - Take it to the drawing board and map Salesforce features to each step. 👉 Build iteratively, take feedback more frequently and keep improving. Yes, Salesforce is simple to configure, but it should not be assumed that the rules of a good project execution don't apply to Salesforce Project. Thoughts? #Salesforce #SalesforceProject #SalesforcePartner #SalesforceImplementation #Anvisol