Raj Valli

🚀 Transforming Grant Writing with AI and Behavioral Science We’re excited to share our latest work: “Implementation Plan for the Retrieval-Augmented Generation System in the GRANT-AI Trial.” This paper details how the GRANT-AI pilot integrates Retrieval-Augmented Generation (RAG) and expert human review to revolutionize NIH grant proposal development. By combining GPT-4o, a curated corpus of funded proposals, and behavioral design elements like motivational nudges and progress visualizations, GRANT-AI offers a scalable, ethical, and evidence-based approach to improving proposal quality and equity in research funding. Key innovations include: 🧠 Integration of expert human reviewers and adaptive AI feedback. 💡 Behavioral scaffolding to enhance writing motivation and completion. 🔍 A secure, NIH-aligned RAG feedback engine built for accuracy and contextual relevance. Our goal? To make grant writing more efficient, equitable, and data-driven for researchers everywhere. 📄 Read the full implementation plan here: https://lnkd.in/d69svhg5 and join the conversation on how AI can responsibly augment scientific writing and peer review. #SporeDataResearch #AIinScience #GrantWriting #RAG #OpenAI #BehavioralScience #ResearchInnovation #NIH 

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“Numbers tell, but stories sell.”- Bryan Eisenberg. A pitch deck is a concise, compelling storytelling tool that visually and verbally presents a startup’s idea, problem, solution, market, team, and opportunity. Often called the “window to a startup’s soul,” it serves as the critical first impression in venture capital and private equity, bridging vision and investor valuation.   It begins with an Introduction that sets the tone, articulating the mission and vision, like how Tesla’s early pitch emphasized accelerating the world’s transition to sustainable energy, instantly establishing purpose and ambition. The Problem Statement highlights a real pain point, such as how Airbnb identified travellers’ struggles with affordable accommodation, connecting investors emotionally and commercially to the need. The Solution showcases how the product or service uniquely addresses that problem; Dropbox, for instance, demonstrated its seamless file-sharing experience in a simple demo that won early backers.   The Market Opportunity quantifies potential using insights like TAM, SAM, and SOM, showing investors that the venture operates in a large, scalable space, for example, Uber’s multibillion-dollar mobility market. The Business Model explains revenue generation in terms of subscriptions, commissions, or freemium models, demonstrating sustainability. Traction proves validation through metrics, users, or partnerships; Zoom’s early adoption numbers reinforced its product–market fit. The Competition slide reveals how the startup stands apart through innovation, patents, or execution speed, while Marketing and Sales Strategy details how the venture will attract and retain customers, such as Spotify’s freemium approach that converted millions of users into paying subscribers.   The Team introduces the driving force behind the idea; as investors often say, “Bet on the jockey, not just the horse.” Highlighting founders with complementary skills and relevant experience builds trust. Financials present the growth story in revenue forecasts, margins, and cash flow, demonstrating both vision and realism. Finally, the Funding Ask specifies the capital required and how it will be allocated for product development, marketing, or scaling operations, followed by a Conclusion that reinforces why the opportunity is worth backing.   In the venture capital and private equity backdrop, the pitch deck bridges aspiration and investment, turning complex strategies into simple, persuasive storytelling. It is where “numbers meet narrative” and “vision meets validation.” From Airbnb’s dream of belonging anywhere to Canva’s mission of democratizing design, history shows that a powerful pitch deck can open doors to transformative funding and success. In short, a pitch deck is not just a presentation, but it is the entrepreneur’s story of conviction, the spark that turns an idea into an investment, and a roadmap connecting innovation with opportunity. #Startups #Innovation

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This HBS insight is exactly right. I fully agree that prioritizing short-term revenue at the expense of long-term capability creates what many now describe as sales debt. Like technical debt, it boosts near-term results while quietly eroding trust, customer value, and organizational resilience. From my work with boards and CEOs, I see this risk amplified in digitally driven and AI-enabled environments. Aggressive sales targets without governance often distort decision making and push leaders to optimize transactions rather than relationships. Research on long-term value creation in Harvard Business Review shows that firms that resist short-termism and align incentives with sustainable outcomes outperform over time. Sales debt rarely shows up immediately on the balance sheet, but it surfaces later through churn, reputational damage, and fragile cultures. Responsible leadership is about recognizing that cost early and choosing durability over speed. Prof Sattar Bawany Disruptive Leadership Institute LLC, New York, NY (DLI) 🌐 https://lnkd.in/gV2gNGU2

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With 88% of faculty agreeing AI literacy is essential for student success, why do 61% feel unprepared to teach it? The gap between urgency and readiness is where strategic leadership becomes critical. I used NotebookLM to make the graphic based on an Eisenhower Matrix approach for AI integration. Here are the priorities for administrators right now: 🧠 DO: Immediately adapt assignments to focus on critically evaluating AI outputs. 🚀 DECIDE: Schedule long-term curriculum redesigns for real-world AI projects. ⚙️ DELEGATE: Free up faculty time by curating approved AI tools and policies. 🗑️ DELETE: Eliminate outdated assessments like AI-vulnerable simple recall quizzes. Applying this priority matrix moves your institution from reactive fear to proactive pedagogical leadership. If you're an administrator tasked with developing a clear AI integration strategy, send me a DM to discuss building a tailored faculty development framework. #AIinEducation #HigherEd #Pedagogy #InstructionalDesign #EdTech

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How do you lead an educational system built for linear progress in a world that changes exponentially? https://buff.ly/HZqnaLP This is the tension I explore in my latest Educational Leadership newsletter post. We discuss why the convergence of AI, biotech, and quantum computing demands a fundamental shift from a reactive to an anticipatory leadership mindset. If you are a superintendent, principal, district leader, or edupreneur wrestling with how to prepare students for a future that is actively being rewritten, this reflection is for you. We'll explore: • Why our current model of "AI training" isn't enough. • The critical questions we aren't asking about "college and career readiness." • How to start cultivating true adaptive capacity in yourself and your teams.

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Spotlight: How NYU Stern Scaled AI Access from Pilot to Universal Many institutions rush to announce AI initiatives. Fewer take the disciplined path from pilot to production. NYU Stern School of Business did exactly that. They started with an administrator AI pilot, testing, learning, refining. Then they scaled deliberately. Today, every faculty member, staff member, and student has access to Gemini and NotebookLM for secure, privacy-protected AI experimentation. But universal access is just the foundation. Here's what Stern built on top of it: + The NYU Stern Fubon Center for Technology, Business and Innovation houses a dedicated Data Analytics and AI Initiative + An AI in Business Speaker Series, hosted by Professor Foster Provost, brings cutting-edge perspectives to campus + A specialized Master of Science in Business Analytics and AI provides deep technical training + The executive education program "Leading in the Age of AI" extends AI leadership development to practitioners + Comprehensive guidance for Teaching and Learning with Generative AI establishes best practices for responsible use The lesson? Pilots aren't delays, they're foundations. Stern's progression from controlled experimentation to systematic training reaching all constituencies demonstrates how elite institutions can move quickly and responsibly. This is one of 48 institutional profiles in the January 2026 report on AI integration in business education, published in partnership with AACSB, GMAC, and the Graduate Business Curriculum Roundtable. Download the full report: https://lnkd.in/gJDmihXJ #HigherEducation #ArtificialIntelligence #BusinessEducation #AIinEducation #NYU Jennifer Sparrow Roy Lee Aaricka Hellberg

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Really grateful to Ulrich Boser and The Cutting Ed for featuring LessonLoop in this “5 Questions” interview. I loved the chance to talk about how AI can strengthen (not replace) the human relationships at the heart of teaching—by helping educators understand engagement in real time, use formative insights to differentiate, and surface potential bias to support more inclusive learning environments. 🔗 Read the article → https://lnkd.in/eaw8TnhV

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Generative AI is forcing higher education to confront an uncomfortable truth. The real crisis is not assessment integrity. It is a decades old educational model built on transaction, performance and proxy credentials rather than real learning. AI did not disrupt universities. It exposed a system that had already lost its connection to mastery, intellectual growth and verifiable capability. This article articulates that tension clearly and asks the right question. Not how to control AI, but how to rethink curriculum, pedagogy and purpose. This is exactly the problem we set out to solve at Eon University. Not AI added to education, but education rebuilt as AI native infrastructure with autonomous AI professors, real time mastery tracking, and cryptographically verified skills via VeriChain. The legacy model is collapsing. A new learning architecture is emerging. Full article below. https://lnkd.in/e5B3Xyzs

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The debate over generative AI in higher education has reached a turning point. In a recent New York Times piece, we see professors like Benjamin Breyer at Barnard College leading the way, not by forbidding tools like ChatGPT, but by teaching students how to use them responsibly. The article highlights innovative approaches, such as custom chatbots designed as interactive tutors that guide students through annotation, thesis development, and critical thinking while firmly refusing to write assignments for them. This shift from fear to guided integration shows that AI isn’t the end of authentic learning—it’s becoming part of it when handled with intention and clear boundaries. For those of us in English, writing, communication, and lifelong learning spaces, this moment is an opportunity. The article eases worries by showing that embracing AI doesn’t mean abandoning rigor, it means preparing students for a world where these tools are everyday realities. Whether you’re a student, educator, or professional, the takeaway is clear: the future belongs to those who learn to collaborate with AI ethically and critically. What are your thoughts—how are you navigating AI in your own teaching, writing, or professional practice? I’d love to hear in the comments. #AIinEducation #HigherEd #WritingSkills #GenerativeAI #EnglishLanguage

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School Boards, Superintendents, Special Education Directors, & Principals: Can you afford to let unchecked AI use run rampant on IEPs, Evaluations, Accommodation Plans? Everyone is now using LLMs in the classroom, but have you laid out clear guidance for IEP Teams? Districts face many compliance risks without clear guidance. Leaving parents out of the collaboration process, sharing personally identifiable information (PII) with LLMs, and data hallucination are just a few. Only by adopting clear and concise policy can we ensure students, families, and districts are protected from "AI SLOP" (and litigation!). https://lnkd.in/gyyFw2Nu

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