Project Management

Stuck in an endless loop of client changes? Lost track of what revision this constitutes? Yeah. Been there. Done that. The secret? It's not about saying no. It's about saying yes to the right things upfront. Every project that goes sideways starts the same way: Vague agreements. Fuzzy boundaries. Good intentions. Six weeks later you're bleeding money and everyone's frustrated. Here's my framework after 30 years of running two 8-figure businesses: The SOW is your salvation. Not some boilerplate template. A real document that covers: • Exact deliverables (not "design work" but "3 homepage concepts, 2 rounds of revisions") • Hours of operation ("We respond M-F, 9-5 PST. Weekend requests get Monday responses") • Revision rounds spelled out ("Round 1 includes up to 5 changes. Round 2 includes 3.") • Feedback cycles defined ("48-hour turnaround for client feedback or the project may be delayed or additional fees may be incurred") But here's what most people miss— Don't work on client notes immediately. Client sends 37 pieces of feedback at 11pm Friday? Producer sends conflicting notes from the CEO? Marketing wants one thing, sales wants another? Stop. Collect everything first. Resolve the conflicts. Get on the phone and discuss it with your client to get alignment. Separate the "have to haves" from the "nice to haves". Then present unified changes. "Based on all feedback received, here are the 8 changes we'll implement. This constitutes revision round 2 of 3." Watch how fast the random requests stop. No extra work that goes unappreciated. No more feelings of being taken advantage of. Communicate before the crisis, prevents the crisis from happening. "Just so you know, we're entering round 2. You have one more included. After that, it's $X per additional round." No surprises. No awkward money conversations. No resentment. Scope creep isn't a them problem. It's a you problem. And that's good news, because that means you are in control. They're not trying to take advantage. They just don't know where the boundaries are because you never drew them. Draw the lines early. Communicate them clearly. Everyone wins. What's your most painful scope creep story? What boundary would've prevented it? Small Business Builders #projectmanagement #clientmanagement #businessgrowth

Last week, I described four design patterns for AI agentic workflows that I believe will drive significant progress: Reflection, Tool use, Planning and Multi-agent collaboration. Instead of having an LLM generate its final output directly, an agentic workflow prompts the LLM multiple times, giving it opportunities to build step by step to higher-quality output. Here, I'd like to discuss Reflection. It's relatively quick to implement, and I've seen it lead to surprising performance gains. You may have had the experience of prompting ChatGPT/Claude/Gemini, receiving unsatisfactory output, delivering critical feedback to help the LLM improve its response, and then getting a better response. What if you automate the step of delivering critical feedback, so the model automatically criticizes its own output and improves its response? This is the crux of Reflection. Take the task of asking an LLM to write code. We can prompt it to generate the desired code directly to carry out some task X. Then, we can prompt it to reflect on its own output, perhaps as follows: Here’s code intended for task X: [previously generated code] Check the code carefully for correctness, style, and efficiency, and give constructive criticism for how to improve it. Sometimes this causes the LLM to spot problems and come up with constructive suggestions. Next, we can prompt the LLM with context including (i) the previously generated code and (ii) the constructive feedback, and ask it to use the feedback to rewrite the code. This can lead to a better response. Repeating the criticism/rewrite process might yield further improvements. This self-reflection process allows the LLM to spot gaps and improve its output on a variety of tasks including producing code, writing text, and answering questions. And we can go beyond self-reflection by giving the LLM tools that help evaluate its output; for example, running its code through a few unit tests to check whether it generates correct results on test cases or searching the web to double-check text output. Then it can reflect on any errors it found and come up with ideas for improvement. Further, we can implement Reflection using a multi-agent framework. I've found it convenient to create two agents, one prompted to generate good outputs and the other prompted to give constructive criticism of the first agent's output. The resulting discussion between the two agents leads to improved responses. Reflection is a relatively basic type of agentic workflow, but I've been delighted by how much it improved my applications’ results. If you’re interested in learning more about reflection, I recommend: - Self-Refine: Iterative Refinement with Self-Feedback, by Madaan et al. (2023) - Reflexion: Language Agents with Verbal Reinforcement Learning, by Shinn et al. (2023) - CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing, by Gou et al. (2024) [Original text: https://lnkd.in/g4bTuWtU ]

🇺🇸 Terrific reference doc on Irregular Warfare, shedding light on U.S doctrine &challenges in defining irregular warfare. 116 p by the Center for Army Lessons Learned, June 2025 🔹Irregular Warfare (IW) considered central to modern conflict &recognized as more common than conventional warfare 🔹IW + conventional warfare considered complementary -NOT separate/ hybrid: can be woven together across the competition continuum 🔹“using military and nonmilitary means—overt, clandestine, or covert—to achieve policy objectives without seeking outright domination“ Key doctrine: 🔹irregular activities included during competition below armed conflict to create &exploit strategic advantages to win without fighting. 🔹During armed conflict IW adds lethal force to compel enemies, at levels that prevent escalation & help avoid high risk of conventional warfare 🔹Ongoing work emphasizes integrating irregular activities into joint campaigns, combining conventional & special ops forces with multinational, interagency& private sector actors 🔹 IW considered a core competency in National strategies: essential in countering great-power competition. DOD directives mandate equal proficiency in conventional and irregular warfare 🔹Allied perspectives: misconceptions around IW &underinvestment 🔹Information domain is decisive: ie: Ukraine’s social media strategy and Israel’s contested X narratives 1️⃣2️⃣ Irregular Warfare Operations: 1. Unconventional Warfare Support resistance or insurgent groups (covertly, overtly, indirectly) to coerce, disrupt, overthrow hostile regimes. 2. Foreign Internal Defense (FID) Assist host nations in countering internal threats (insurgency, terrorism, lawlessness) through whole-of-gov support 3. Counterinsurgency (COIN) Blend mil& civilian efforts to defeat insurgencies &address root causes, strengthening gov legitimacy 4. Counterterrorism (CT) Neutralize terrorist networks to prevent them from using violence to coerce 5. Stability Activities Restore/maintain safe environments, essential services, governance, humanitarian relief after crises 6. Security Cooperation (SC) Build partner &ally defense capacity, interoperability while advancing U.S security interests 7. Security Force Assistance (SFA) Train, equip, advise foreign security forces to develop capacity for long-term stability 8. Counter Threat Finance (CTF) Deny adversaries ability to fund operations by disrupting illicit & licit financial flows 9. Counter Threat Networks (CTN) Identify &neutralize adaptive adversarial networks that threaten U.S goals. 10. Military Information Support Operations (MISO) Influence foreign audiences’ attitudes &behaviors through tailored messaging to achieve U.S objectives 11. Civil-Mil Operations (CMO) Coordinate with civil authorities to reduce friction,build trust, support mil ops 12. Civil Affairs Operations (CAO) Conduct specialized engagements with civi populations/institutions to address instability,governance&recovery needs

𝗧𝗼𝗱𝗮𝘆, 𝗣𝗠𝗜 𝗿𝗲𝗹𝗲𝗮𝘀𝗲𝘀 𝘁𝗵𝗲 𝗳𝗶𝗿𝘀𝘁 𝗿𝗲𝘀𝘂𝗹𝘁𝘀 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗹𝗮𝗿𝗴𝗲𝘀𝘁 𝘀𝘁𝘂𝗱𝘆 𝘄𝗲’𝘃𝗲 𝗲𝘃𝗲𝗿 𝗰𝗼𝗻𝗱𝘂𝗰𝘁𝗲𝗱 - 𝗼𝗻 𝗮 𝘁𝗼𝗽𝗶𝗰 𝘁𝗵𝗮𝘁 𝗶𝘀 𝗰𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝘁𝗼 𝗼𝘂𝗿 𝗽𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻: 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗦𝘂𝗰𝗰𝗲𝘀𝘀. 📚 Read the report: https://lnkd.in/ekRmSj_h With this report, we are introducing a simple and scalable way to measure project success. A successful project is one that 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘀 𝘃𝗮𝗹𝘂𝗲 𝘄𝗼𝗿𝘁𝗵 𝘁𝗵𝗲 𝗲𝗳𝗳𝗼𝗿𝘁 𝗮𝗻𝗱 𝗲𝘅𝗽𝗲𝗻𝘀𝗲, as perceived by key stakeholders. This clearly represents a shift for our profession, where beyond execution excellence we also feel accountable for doing anything in our power to improve the impact of our work and the value it generates at large. The implications for project professionals can be summarized in a framework for delivering 𝗠𝗢𝗥𝗘 success: 📚𝗠anage Perceptions For a project to be considered successful, the key stakeholders - customers, executives, or others - must perceive that the project’s outcomes provide sufficient value relative to the perceived investment of resources. 📚𝗢wn Project Success beyond Project Management Success Project professionals need to take any opportunity to move beyond literal mandates and feel accountable for improving outcomes while minimizing waste. 📚𝗥elentlessly Reassess Project Parameters Project professionals need to recognize the reality of inevitable and ongoing change, and continuously, in collaboration with stakeholders, reassess the perception of value and adjust plans. 📚𝗘xpand Perspective All projects have impacts beyond just the scope of the project itself. Even if we do not control all parameters, we must consider the broader picture and how the project fits within the larger business, goals, or objectives of the enterprise, and ultimately, our world. I believe executives will be excited about this work. It highlights the value project professionals can bring to their organizations and clarifies the vital role they play in driving transformation, delivering business results, and positively impacting the world. The shift in mindset will encourage project professionals to consider the perceptions of all stakeholders- not just the c-suite, but also customers and communities. To deliver more successful projects, business leaders must create environments that empower project professionals. They need to involve them in defining - and continuously reassessing and challenging - project value. Leverage their expertise. Invest in their work. And hold them accountable for contributing to maximize the perception of project value at all phases of the project - beyond excellence in execution. 📚 Please read the report, reflect on its findings, and share it broadly. And comment! Project Management Institute #ProjectSuccess #PMI #Leadership #ProjectManagementToday

Most projects fail. But there’s a simple technique to give yours a fighting chance. It’s not a to-do list. It’s not a fancy tool. It’s not a 12-step system. It’s a single question that flips the way you think. Here’s how it works: It’s called a “premortem.” You’ve heard of a postmortem what went wrong after a project dies. A premortem asks: What if we ran that analysis now? Before anything dies. Before the first misstep. Before failure sets in. The premortem comes from psychologist Gary Klein. Here’s how to run one: → Gather your team. → Imagine it’s 2 years in the future. → The project has completely failed. → Ask: What went wrong? No sugarcoating. No happy talk. Start listing the causes of failure. Budget misfire? Wrong team? Lack of buy-in? Scope creep? Missed deadlines? You’ll be shocked how quickly people identify risks—once they feel safe predicting failure. Why this works: It defeats irrational optimism. • It turns hindsight into foresight. • It makes risk visible. • It aligns the team before chaos hits. Because the best time to fix a problem… is before it happens. Pre-mortems don’t require special skills. Just a shift in mindset: Don’t assume success. Assume failure—and reverse-engineer your way out. Ask: What will future-you wish you had done? Then… do that now. I run a premortem for every big project I take on. Writing a book? Premortem. Launching a podcast? Premortem. Planning an event? Premortem. It never guarantees success—but it always makes success more likely. Summary: The Premortem Playbook → Imagine future failure. → List the causes. → Turn those risks into action steps. → Adjust your plan today. It’s one of the most underrated tools in your productivity toolkit. Try it before your next project. You won’t regret it.

As Duarte grew, I’d hear feedback that decisions were made too slowly, which confused me. In reality, we didn’t have a system to recognize when the team was asking for a decision. We thought they were just informing us, so decisions would languish. We weren’t ignoring them, failing to act, or even making incorrect decisions... We just didn’t realize a decision needed to be made in the first place. It dawned on the exec team that the lack of clarity during the conversation is what slows teams down. Leaders and teams can share the same language for decision-making. Much of it is about shaping recommendations that actually lead to the right type of action and making the urgency clear. Here’s the shift that changed everything… We started mapping every decision against two factors: urgency and risk. Low risk, low urgency: Decide without me. Your team runs with it. Low risk, high urgency: Inform on progress. They update you, but keep driving. High risk, low urgency: Propose for approval. They bring a recommendation, and you decide together. High risk, high urgency: Escalate immediately. You're in it together, right now. Once my team understood which quadrant a decision lived in, they knew exactly how to approach me. And I knew exactly what my role was. The framework gave us a shared language. People can’t act on ideas if they don’t understand how decisions are made. Leaders should define how recommendations move from idea to approval to action. That transparency keeps progress from stalling. Remember: One of the biggest threats to your company isn't a lack of good ideas. It's a lack of clarity. #Leadership #ExecutiveLeadership #OrganizationalCulture #DecisionMaking

🚨 AI Privacy Risks & Mitigations Large Language Models (LLMs), by Isabel Barberá, is the 107-page report about AI & Privacy you were waiting for! [Bookmark & share below]. Topics covered: - Background "This section introduces Large Language Models, how they work, and their common applications. It also discusses performance evaluation measures, helping readers understand the foundational aspects of LLM systems." - Data Flow and Associated Privacy Risks in LLM Systems "Here, we explore how privacy risks emerge across different LLM service models, emphasizing the importance of understanding data flows throughout the AI lifecycle. This section also identifies risks and mitigations and examines roles and responsibilities under the AI Act and the GDPR." - Data Protection and Privacy Risk Assessment: Risk Identification "This section outlines criteria for identifying risks and provides examples of privacy risks specific to LLM systems. Developers and users can use this section as a starting point for identifying risks in their own systems." - Data Protection and Privacy Risk Assessment: Risk Estimation & Evaluation "Guidance on how to analyse, classify and assess privacy risks is provided here, with criteria for evaluating both the probability and severity of risks. This section explains how to derive a final risk evaluation to prioritize mitigation efforts effectively." - Data Protection and Privacy Risk Control "This section details risk treatment strategies, offering practical mitigation measures for common privacy risks in LLM systems. It also discusses residual risk acceptance and the iterative nature of risk management in AI systems." - Residual Risk Evaluation "Evaluating residual risks after mitigation is essential to ensure risks fall within acceptable thresholds and do not require further action. This section outlines how residual risks are evaluated to determine whether additional mitigation is needed or if the model or LLM system is ready for deployment." - Review & Monitor "This section covers the importance of reviewing risk management activities and maintaining a risk register. It also highlights the importance of continuous monitoring to detect emerging risks, assess real-world impact, and refine mitigation strategies." - Examples of LLM Systems’ Risk Assessments "Three detailed use cases are provided to demonstrate the application of the risk management framework in real-world scenarios. These examples illustrate how risks can be identified, assessed, and mitigated across various contexts." - Reference to Tools, Methodologies, Benchmarks, and Guidance "The final section compiles tools, evaluation metrics, benchmarks, methodologies, and standards to support developers and users in managing risks and evaluating the performance of LLM systems." 👉 Download it below. 👉 NEVER MISS my AI governance updates: join my newsletter's 58,500+ subscribers (below). #AI #AIGovernance #Privacy #DataProtection #AIRegulation #EDPB

💎 60 UX Strategy Methods And Activities (Figma) (https://lnkd.in/eCDU-vhR), a large repository of UX methods, templates and activities for ideation sessions and product sprints, from storyboards and brainwriting to 6 thinking hats, journey mapping and concept testing. Neatly put together in one single place by fine folks at Merck. The team has also put together a very thorough overview of their UX Strategy Kit (https://lnkd.in/ek5dEYn4), broken down by categories for strategy, observation, ideation and warm-up, along with detailed video walkthroughs, examples and step-by-step guides. Frankly, most of these methods are unfamiliar to me. And by no means is the point to actually study and apply all of them. What works for you works for you. To strategize, I rely on How Might We but also think about metrics that should be moved once we implement some features or refine some user flows. For event storming and brainstorming, I tend to rely on Bono’s 6 thinking hats to align brainstorming, and (of course) journey mapping. For ideation, I love using storyboards to jump right into the user’s success story, but would also use card sorting with cut-out paper cards to understand user’s mental model. And for almost every project, I’d run concept testing with tree testing or Kano model, or low-fidelity/paper prototyping to understand if we are on the right track. Once you sprinkle a bit of critical thinking, early user testing and strategic planning across the design work, you gain confidence that you are moving in the right direction. And really that’s all you need. A few of my personal bookmarks with UX methods and activities: UX Tools For Better Thinking, by Adam Amran 👏🏽 https://untools.co/ Playbook For Universal Design (+ PDF/Powerpoint templates) https://lnkd.in/ernris4g UX Methods & Projects, by Vernon Fowler https://lnkd.in/eAHaiaSm 18F Method Cards https://methods.18f.gov/ Hyperisland UX Methods Resource Kit 👍 https://lnkd.in/eDTaci7T How To Design Better UX Workshops, by Slava Shestopalov https://lnkd.in/edxqCC-n How To Run UX Workshops With Users, by yours truly https://lnkd.in/ejm7_TsS Happy designing, everyone — I hope you’ll find these guides and resources helpful to get started. Just don’t feel like you have to try out all of them. It might be much more worthwhile to get early feedback from stakeholders and end users, even if your work isn’t really “good” enough. Good luck! #ux #design

As head of our product organization at Chase, I often think about how and what we’re delivering to customers, but I recently reflected on the vital role of product managers. While some may view it as merely administrative, in my opinion this couldn't be further from the truth. Product managers are the driving force behind strategy and exceptional experiences, whether for external customers or internal users. Our role demands a deep connection to both the product and its users. Three essential qualities we all have: Customer Obsession: Go beyond empathy by diving into data and insights to understand user behavior, pain points, and opportunities. Decisions should be data-driven, ensuring the product evolves with user needs. Strategic Leadership: Product managers must define and drive the product vision, setting strategies that align with company goals. This involves fostering alignment across cross-functional teams and building strong relationships with stakeholders to ensure everyone is working toward a shared vision. Accountability: Own the outcomes, whether good or bad. Exceptional product managers embrace challenges, learn from mistakes, and continuously iterate to improve. They step into gray areas, connecting the dots to drive cohesive and successful outcomes. This role is strategic and high-impact, requiring us to lead with intention, push boundaries, and always advocate for the user. #productmanagers #productdevelopment

Don’t make these common mistakes in techno-economic assessments (and avoid misleading conclusions.) TEA is a powerful tool to assess the feasibility of emerging technologies. But even small mistakes can lead to misleading conclusions and poor decisions. Here are 5 key mistakes I’ve seen repeatedly—and how to fix them: 1. Overestimating Technology Performance Challenge: Assuming ideal or lab-scale performance when scaling up. Real-world conditions often bring inefficiencies. Fix: Use conservative assumptions, validate with experimental data, and conduct sensitivity analysis. 2. Ignoring Uncertainty Problem: Treating input values (e.g., costs, energy efficiency) as fixed leads to rigid, unreliable results. Fix: Perform sensitivity and scenario analyses to identify critical variables and explore best/worst cases. 3. Using Outdated or Poor-Quality Data The Problem: Relying on old data or inconsistent sources reduces the credibility of your TEA. Fix: Source data from updated literature, validated models, or credible industry benchmarks, and clearly document assumptions. If data is missing for new technologies, use proxy technologies and check uncertainties. 4. Oversimplifying Economic Analysis Problem: Focusing only on capital costs (CAPEX) while ignoring operating costs (OPEX), maintenance, or financing impacts. Or focusing on single metrics, like NPV. Fix: Include all cost components—CAPEX, OPEX, and life-cycle costs—and calculate key metrics like NPV, IRR, and payback period. 5. Neglecting Policy and Market Factors Problem: Ignoring factors like carbon pricing, subsidies, or fluctuating raw material costs can skew results. Fix: Integrate policy scenarios, market trends, and potential incentives to build a more realistic TEA. Techno-economic analysis is only as good as its assumptions and methods. Avoiding these mistakes will help you deliver insights that are credible, actionable, and valuable for decision-making. We’re going to discuss all these challenges with TEA and more during my workshop in Q1 2025. What challenges have you faced when conducting TEA? I’d love to hear your thoughts in the comments! #Research #ChemicalEngineering #Economics #Energy #PhD #Scientist #Professor