Project Management

Working with multiple LLM providers, prompt engineering, and complex data flows requires thoughtful organization. A proper structure helps teams: - Maintain clean separation between configuration and code - Implement consistent error handling and rate limiting - Enable rapid experimentation while preserving reproducibility - Facilitate collaboration across ML engineers and developers The modular approach shown here separates model clients, prompt engineering, utils, and handlers while maintaining a coherent flow. This organization has saved many people countless hours in debugging and onboarding. Key Components That Drive Success Beyond folders, the real innovation lies in how components interact: - Centralized configuration through YAML - Dedicated prompt engineering module with templating and few-shot capabilities - Properly sandboxed model clients with standardized interfaces - Comprehensive caching, logging, and rate limiting Whether you're building RAG applications, fine-tuning foundation models, or creating agent-based systems, this structure provides a solid foundation to build upon. What project structure approaches have you found effective for your generative AI projects? I'd love to hear your experiences.

Writing software, especially prototypes, is becoming cheaper. This will lead to increased demand for people who can decide what to build. AI Product Management has a bright future! Software is often written by teams that comprise Product Managers (PMs), who decide what to build (such as what features to implement for what users) and Software Developers, who write the code to build the product. Economics shows that when two goods are complements — such as cars (with internal-combustion engines) and gasoline — falling prices in one leads to higher demand for the other. For example, as cars became cheaper, more people bought them, which led to increased demand for gas. Something similar will happen in software. Given a clear specification for what to build, AI is making the building itself much faster and cheaper. This will significantly increase demand for people who can come up with clear specs for valuable things to build. This is why I’m excited about the future of Product Management, the discipline of developing and managing software products. I’m especially excited about the future of AI Product Management, the discipline of developing and managing AI software products. Many companies have an Engineer:PM ratio of, say, 6:1. (The ratio varies widely by company and industry, and anywhere from 4:1 to 10:1 is typical.) As coding becomes more efficient, teams will need more product management work (as well as design work) as a fraction of the total workforce. Perhaps engineers will step in to do some of this work, but if it remains the purview of specialized Product Managers, then the demand for these roles will grow. This change in the composition of software development teams is not yet moving forward at full speed. One major force slowing this shift, particularly in AI Product Management, is that Software Engineers, being technical, are understanding and embracing AI much faster than Product Managers. Even today, most companies have difficulty finding people who know how to develop products and also understand AI, and I expect this shortage to grow. Further, AI Product Management requires a different set of skills than traditional software Product Management. It requires: - Technical proficiency in AI. PMs need to understand what products might be technically feasible to build. They also need to understand the lifecycle of AI projects, such as data collection, building, then monitoring, and maintenance of AI models. - Iterative development. Because AI development is much more iterative than traditional software and requires more course corrections along the way, PMs need be able to manage such a process. - Data proficiency. AI products often learn from data, and they can be designed to generate richer forms of data than traditional software. - ... [Reached length limit; full text: https://lnkd.in/geQBWz6s ]

Every organization needs to innovate. But what type of innovation to give priority to? This simple matrix with four types of innovation may help. Innovation basically means introducing something new (‘nova’). This “something new” can be anything and that’s where the problem starts. In two ways. - First, by an overemphasis on product (or service) innovation, thereby not giving enough attention to other types - Second, by getting overwhelmed by all the innovation opportunities that are out there. To solve both problems at the same time, it helps to gain some clarity on what types of innovation there are. To that end, I’ve created this simple 2x2 matrix containing what I think are the four most important types of innovation for every organization. Let me first explain the two axes. The first is the inward-outward axis. Outward-oriented innovations are those innovations that are mostly targeted at the market, at doing something new for customers. Inward-oriented innovations, on the other hand, are innovating the organization itself. On the second axis, Operational innovations are typically quite technical and tangible, and focused on the practical work and output. Strategic innovations, on the other hand, regard how the organization is functioning overall and how it creates value. This leads to the following four types of innovation: 1. Product Innovation. The most well-known type of innovation in which you change, improve or renew an organization’s products and/or services, or create new ones. 2. Process Innovation. Often efficiency and quality-driven to improve the way the organization works on a day-to-day basis. This can concern any type of process. 3. Business Model Innovation. A newer type, focused on changing how the organization creates and captures value. Often focused on developing new revenue models. 4. Management Innovation. Less commonly known but critical, this type concerns innovating how an organization is organized, managed, and led. Often implies decentralization. All four types are important and with this matrix you can start managing your innovation portfolio. Ask yourself questions like: Do I have sufficient initiatives in all quadrants? And, which type of innovation should get priority now? [Featured in The Strategic Leadership Playbook. Originally published in June, 2023] More of this? For 63 more tools like this, plus step-by-step instructions for using them, get The Strategic Leadership Playbook. See link in the comment below. #innovationmanagement #processimprovement #productdesign #businessmodel

As we enter 2024, remember how tempting it is to pay attention to the loud, confident voices in our lives (in meetings, in teams, in families, in society). However, the deep thinkers who hold back often have the key you need to unlock our problems and move things forward. It’s not just a question of listening, it’s listening for the right things from the right people. It's not that I am picking on loud people. I am not saying, for example, that people who talk more, who are more extroverted, don't ever have the answers. Of course, they do. The thing is, when people who talk more (or more confidently, or more smoothly, or more openly) have the answer, people already know about it because it's already being expressed. Nor am I saying that everyone who is quiet has the answer. It's obviously true that someone who is not speaking may not have the answer. The thing is, when people don't talk as much (or as confidently, or as smoothly, or as openly) but they have the answer, people won't know because it isn't being expressed. It takes a particular approach to facilitation, to team dynamics, to creating team rules and expectations to make sure the best ideas win out. Here are a few ways to do this: 1. Frame the decision to be made: what the decision is, why it matters, how the decision will be made 2. Send it in advance along with the ask that each person comes prepared to share their POV with data to support it 3. Ask people to write down answers before talking i.e. a write-storm before they brainstorm 4. Set rules of the road: an obligation to speak up, a culture of listening, a rule of not dominating, and a commitment to support the decision once it’s been made 5. Facilitate the conversation: ask for quiet voices to speak up 6. Have louder voices restate what others have said before jumping in with their own opinions 7. Nobody speaks twice until everyone has spoken once 8. Divide up the group into subgroups to solve the problem separately and come together to share their different ideas 9. Ask people to switch sides and argue against their own position #listenright #decipher #discern Effortless https://lnkd.in/gizMz9U Essentialism https://lnkd.in/g82e5uGK Podcast https://lnkd.in/eaDjxm6M

If You Can’t Explain Budgeting Like This, You’re Not Ready for FP&A Interviews. Let’s assume I ask you the budget for fuel (petrol/diesel) expenses that you are going to incur next year in 2026. How would you budget using the below techniques: 1. Incremental / Traditional Budgeting You take into account the expenses on fuel you made this year. Assuming that amount is INR 50,000. Considering inflation, fuel price changes, and usage patterns, you estimate a 20% increase. Accordingly, your fuel budget for next year will be INR 60,000 (50,000 + 20%) 2. Zero-Based Budgeting Instead of taking current year’s expenses, you start from scratch. You estimate how much your car will travel next year. Then factor in expected fuel price and mileage of your vehicle. Based on this, you calculate a reasonable estimate of fuel expenses for next year 3. Activity-Based Budgeting Let’s say you use the car only to commute to and from office. For each round trip, your car consumes fuel worth INR 500. Your budgeting would be based on this activity (number of trips taken in a year). If you go to office twice a week, total trips = 52 × 2 = 104. Hence, your fuel budget = 500 × 104 = INR 52,000. 4. Flexible Budgeting Your fuel cost depends on how frequently you travel. Instead of one fixed budget, you prepare multiple scenarios. Example: 2 days/week → INR 52,000 4 days/week → INR 104,000 Your actual budget will depend on actual usage during the year. 5. Rolling (Continuous) Budgeting You don’t fix the budget once for the entire year. You keep revising it periodically (monthly/quarterly). Example: if fuel prices increase mid-year or your travel increases, you update the remaining budget accordingly. 6. Top-Down vs Bottom-Up Budgeting Top-Down: You decide a cap (say INR 55,000) and adjust your usage to stay within it Bottom-Up: You calculate expected usage (like ABB/ZBB) and arrive at the number logically 7. Value Proposition Budgeting (using the same example) Instead of focusing only on cost, you evaluate whether the expense creates value. You analyse each type of travel: Office commute - necessary Leisure / unnecessary trips - optional You may reduce or eliminate low-value trips, carpool, or use alternative transport. Hence, your budget is driven by value derived rather than just estimated usage. This way, the same fuel expense can give you very different budgets depending on the approach you use.

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

WEF's Global Risks Report 2026 is out 👉 (https://lnkd.in/eaMrdW67).. I put the findings in a 20-year perspective. I mapped 20 years of risk rankings. Two patterns stand out. Both troubling. The headline findings in this report: 🔵 geoeconomic confrontation is now the #1 risk in the short term, 🔵 economic risks are spiking, 🔵 50% of experts expect a turbulent or stormy outlook over the next two years. But the deeper signal only appears when you track the rankings over time (what I did, see 👇 ). ⚫ 𝐏𝐚𝐭𝐭𝐞𝐫𝐧 𝟏 – 𝐋𝐨𝐧𝐠-𝐭𝐞𝐫𝐦 𝐫𝐢𝐬𝐤𝐬 𝐦𝐢𝐠𝐫𝐚𝐭𝐞 𝐢𝐧𝐭𝐨 𝐭𝐡𝐞 𝐬𝐡𝐨𝐫𝐭 𝐭𝐞𝐫𝐦 Not overnight. Not mechanically. But persistently. In 2007–2010, short-term risks were concrete and immediate: asset bubbles, oil shocks, chronic diseases. Fast forward to today. The long-term top risks for 2026 are: 🌪️ extreme weather 🌍 biodiversity loss 🧠 misinformation 🤖 adverse AI outcomes What changed is not that economic risks disappeared. It’s that structural risks began to act as crisis amplifiers. Extreme weather didn’t replace financial shocks, it reshaped them. Climate risks first entered the short-term top 5 around 2014. By 2020, climate action failure topped the list. “Tomorrow’s risks” became today’s stress multipliers, and increasingly, direct crisis drivers. The future didn’t wait. ⚫𝐏𝐚𝐭𝐭𝐞𝐫𝐧 𝟐: 𝐍𝐚𝐭𝐮𝐫𝐞 𝐢𝐬 𝐛𝐞𝐢𝐧𝐠 𝐟𝐨𝐫𝐠𝐨𝐭𝐭𝐞𝐧, 𝐚𝐠𝐚𝐢𝐧 This year, environmental risks dropped sharply in the short-term rankings. More worrying: their severity scores also declined in absolute terms. Yet over the 10-year horizon, environmental risks dominate the top 10. Twenty years of WEF risk data tell the same story: we consistently recognise long-term environmental threats, then consistently deprioritise them when short-term pressures mount. It's not that we don't know. It's that our attention economy is structurally biased toward the urgent over the important. The most interconnected risk for the second year running? Inequality (👇). It fuels everything else: polarisation, migration, political instability, resistance to climate policy. Perhaps that's where to start: 𝐢𝐟 𝐰𝐞 𝐰𝐚𝐧𝐭 𝐭𝐨 𝐚𝐝𝐝𝐫𝐞𝐬𝐬 𝐥𝐨𝐧𝐠-𝐭𝐞𝐫𝐦 𝐜𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬, 𝐰𝐞 𝐧𝐞𝐞𝐝 𝐭𝐨 𝐫𝐞𝐝𝐮𝐜𝐞 𝐭𝐡𝐞 𝐬𝐡𝐨𝐫𝐭-𝐭𝐞𝐫𝐦 𝐝𝐞𝐬𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧 𝐭𝐡𝐚𝐭 𝐤𝐞𝐞𝐩𝐬 𝐮𝐬 𝐭𝐫𝐚𝐩𝐩𝐞𝐝 𝐢𝐧 𝐜𝐫𝐢𝐬𝐢𝐬 𝐦𝐨𝐝𝐞. #GlobalRisks #WEF #ClimateChange #Sustainability #SystemChange

Running LLM-powered applications shouldn't drain your budget. While you're excited about building your next GenAI project, knowing how to optimize LLM costs is essential for long-term success. LLM cost optimization involves multiple complementary strategies to reduce inference expenses while maintaining performance. Input optimization focuses on efficient prompt engineering and context pruning to minimize token usage, ensuring only essential information is processed. Model selection involves choosing right-sized models for specific tasks, preventing resource waste from oversized models while maintaining accuracy. Model optimization techniques like quantization and pruning reduce model size and computational requirements without significantly impacting performance. Distributed processing leverages distributed inference and load balancing to optimize resource utilization across multiple machines, improving throughput and cost efficiency. Caching strategies implement response and embedding caches to avoid redundant computations, storing frequently requested responses and pre-computed embeddings for quick retrieval. Output management implements token limits and stream processing to control response lengths and optimize data flow. System architecture considerations include batch processing to maximize throughput and request optimization to reduce unnecessary API calls. Together, these strategies form a comprehensive approach to LLM cost optimization, balancing performance requirements with resource efficiency. The key is implementing these strategies in combination, as each addresses different aspects of LLM deployment costs. Success requires continuous monitoring and adjustment of these strategies based on usage patterns, performance requirements, and cost metrics. Know more about such LLM cost optimization strategies and techniques in this blog: https://lnkd.in/gMvbg6Se Subscribe to my YouTube channel to know & understand more in-depth concepts on Generative AI: https://lnkd.in/gmAKSxKJ

“The main change is the Treasury discarded a bright-line 5% test for starting construction of solar projects over 1.5 megawatts and all wind projects in favor of a less clear facts-and-circumstances approach of looking at the amount of physical work done by a factory on custom-made equipment for the project or at the project site.” “The new construction-start rules apply to wind and solar projects on which construction starts on or after September 2, giving developers a short window to try to tidy up any construction-start efforts they have currently underway. Developers starting construction of new solar or wind projects during the period September 2, 2025 through July 4, 2026 will have four years to finish after the year construction starts. Thus, a project on which construction starts in early 2026 will have until the end of 2030 to finish construction.” “Distributed solar developers will still be able to use the 5% test on projects with nameplate capacities of up to 1.5 megawatts. The capacity will be measured at each inverter string. Thus, a large project could qualify in theory, but the IRS will treat multiple inverter strings as a single project if they have "integrated operations." (Strings placed in service in separate tax years are not aggregated.)”

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