Education

𝗔𝟮𝗔 (𝗔𝗴𝗲𝗻𝘁-𝘁𝗼-𝗔𝗴𝗲𝗻𝘁) 𝗮𝗻𝗱 𝗠𝗖𝗣 (𝗠𝗼𝗱𝗲𝗹 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹) are two emerging protocols designed to facilitate advanced AI agent systems, but they serve distinct roles and are often used together in modern agentic architectures. 𝗛𝗼𝘄 𝗧𝗵𝗲𝘆 𝗪𝗼𝗿𝗸 𝗧𝗼𝗴𝗲𝘁𝗵𝗲𝗿 Rather than being competitors, 𝗔𝟮𝗔 𝗮𝗻𝗱 𝗠𝗖𝗣 𝗮𝗿𝗲 𝗰𝗼𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝗿𝘆 𝗽𝗿𝗼𝘁𝗼𝗰𝗼𝗹𝘀 that address different layers of the agent ecosystem: • 𝗔𝟮𝗔 is about agents collaborating, delegating tasks, and sharing results across a distributed network. For example, an orchestrating agent might delegate subtasks to specialized agents (analytics, HR, finance) via A2A25. • 𝗠𝗖𝗣 is about giving an agent (often an LLM) structured access to external tools and data. Within an agent, MCP is used to invoke functions, fetch documents, or perform computations as needed.    𝗧𝘆𝗽𝗶𝗰𝗮𝗹 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝗘𝘅𝗮𝗺𝗽𝗹𝗲: • A user submits a complex request. • The orchestrating agent uses 𝗔𝟮𝗔 to delegate subtasks to other agents. • One of those agents uses 𝗠𝗖𝗣 internally to access tools or data. • Results are returned via A2A, enabling end-to-end collaboration25.    𝗗𝗶𝘀𝘁𝗶𝗻𝗰𝘁 𝗦𝘁𝗿𝗲𝗻𝗴𝘁𝗵𝘀 • 𝗔𝟮𝗔 𝗲𝘅𝗰𝗲𝗹𝘀 𝗮𝘁:   Multi-agent collaboration and orchestration   Handling complex, multi-domain workflows   Allowing independent scaling and updating of agents   Supporting long-running, asynchronous tasks54 • 𝗠𝗖𝗣 𝗲𝘅𝗰𝗲𝗹𝘀 𝗮𝘁:   Structured tool and data integration for LLMs   Standardizing access to diverse resources   Transparent, auditable execution steps   Single-agent scenarios needing a precise tool    𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗮𝗹 𝗔𝗻𝗮𝗹𝗼𝗴𝘆 • 𝗠𝗖𝗣 is like a 𝘶𝘯𝘪𝘷𝘦𝘳𝘴𝘢𝘭 𝘤𝘰𝘯𝘯𝘦𝘤𝘵𝘰𝘳 (USB-C port) between an agent and its tools/data. • 𝗔𝟮𝗔 is like a 𝘯𝘦𝘵𝘸𝘰𝘳𝘬 𝘤𝘢𝘣𝘭𝘦 connecting multiple agents, enabling them to form a collaborative team.    𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗮𝗻𝗱 𝗖𝗼𝗺𝗽𝗹𝗲𝘅𝗶𝘁𝘆 𝗖𝗼𝗻𝘀𝗶𝗱𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 • 𝗔𝟮𝗔 introduces many endpoints and requires robust authentication and authorization (OAuth2.0, API keys). • 𝗠𝗖𝗣 needs careful sandboxing of tool calls to prevent prompt injection or tool poisoning. Both are built with enterprise security in mind.    𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝗔𝗱𝗼𝗽𝘁𝗶𝗼𝗻 • 𝗔𝟮𝗔: Google, Salesforce, SAP, LangChain, Atlassian, Cohere, and others are building A2A-enabled agents. • 𝗠𝗖𝗣: Anthropic (Claude Desktop), Zed, Cursor AI, and tool-based LLM UIs.   Modern agentic systems often combine both: 𝗔𝟮𝗔 𝗳𝗼𝗿 𝗶𝗻𝘁𝗲𝗿-𝗮𝗴𝗲𝗻𝘁 𝗼𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻, 𝗠𝗖𝗣 𝗳𝗼𝗿 𝗶𝗻𝘁𝗿𝗮-𝗮𝗴𝗲𝗻𝘁 𝘁𝗼𝗼𝗹 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻. This layered approach supports scalable, composable, and secure AI applications.

Montana, Maine, Alaska, Nevada, and Michigan recently joined the growing number of states with official AI guidance for K12—bringing us to 31 states and 1 U.S. territory. Common priority areas across these new state guidelines include: • Human-Centered Approach - Ensuring AI augments rather than replaces human capabilities, judgment, and decision-making, with educators remaining central to instruction • Data Privacy and Security - Protecting student data and ensuring FERPA, COPPA, and state laws • Ethical Use and Academic Integrity - Establishing clear policies on plagiarism, proper attribution of AI-generated content, and responsible use practices • Professional Development - Encouraging districts to prioritize professional learning for educators on AI tools, pedagogy, and classroom integration strategies • Transparency and Accountability - Communicating clearly with stakeholders about AI use, disclosing when AI is employed, and establishing responsibility for tool selection and outcomes • Equity and Fair Access - Ensuring all students and schools have access to AI technologies, preventing widening of the digital divide • Policy Development and Governance - Creating board-approved guidelines, acceptable use policies, and frameworks for ongoing evaluation and continuous improvement Notably, Maine and Nevada also include AI for Education resources like our Drafting a GenAI Academic Policy and AI in Education 101 for Parents guide. This state-level policy development reflects the need and activity already happening at the district level, with recent research showing that 68% of districts have purchased an AI-related tool. We're also hearing from partners that it serves as a catalyst where state guidance exists—motivating districts and schools to begin their own local AI policy development. For those who want to learn more, we’ve compiled all of the current state level guidance for K12 in a single resource which includes summaries and links for each individual state. There you can also find all of the AI for Education resources shared as part of various state level guidance, including: • Drafting a GenAI Academic Policy at Your School • AI in Education 101 for Parents • Top 5 Questions for GenAI EdTech Providers • An Essential Guide to AI for Educators (free course) • Prompt Framework for Educators: The Five "S" Model • Prompt Library for Educators • How to Use AI Responsibly EVERY Time • AI Adoption Roadmap for Education Institutions Link in the comments!

500 students share one computer in Niger. Yet they're conducting advanced physics experiments that students at elite schools can't access. The secret? WebAR turning basic smartphones into portable STEM labs. Think about that. In Sub-Saharan Africa, fewer than 10% of schools have internet. Student-to-computer ratios hit 500:1. Yet mobile subscriptions jumped from single digits to 80% in a decade. Students already carry the infrastructure—we just weren't using it right. Traditional EdTech Reality: ↳ VR headsets: $300+ per student ↳ Heavy apps requiring 5G speeds ↳ Labs costing millions to build ↳ Rural schools: permanently excluded The WebAR Revolution: ↳ Runs in any browser, optimized for 3G ↳ No app store, minimal storage ↳ Science scores improving 10-15% ↳ Every smartphone becomes a laboratory But here's what grabbed me: A physics teacher in rural South Africa has one broken oscilloscope. No budget. Her students scan printed markers, and electromagnetic fields pulse across their desks. They run experiments infinitely—no equipment damaged, no reagents consumed. One student told her: "Engineering is for people like me now. The lab fits in my pocket." What changes everything: ↳ Mobile-first matches actual connectivity ↳ Browser-based works offline ↳ Teachers need training, not new buildings ↳ Inequality becomes irrelevant The Multiplication Effect: 1 teacher with markers = 30 students experimenting 10 schools sharing content = communities transformed 100 districts adopting = educational equality emerging At scale = STEM education without infrastructure gaps We spent decades waiting for labs that won't arrive. Now any browser becomes one. Because when a student in rural Africa explores the same 3D molecules as someone at MIT—using the phone already in their pocket—you realize: WebAR isn't shiny technology. It's a quiet equaliser making world-class STEM education fit into 3G connections and $50 phones. Follow me, Dr. Martha Boeckenfeld for innovations where accessibility drives transformation. ♻️ Share if you believe quality education shouldn't require perfect infrastructure.

🧠 The Hidden Curriculum: Why Chores Build the Kind of Intelligence Schools Can’t Teach A Harvard study found that children who do daily chores are more likely to succeed later in life. That caught my attention — not because of what it says about children, but what it reveals about how success really forms. I’ve been thinking about this a lot. In my opinion, chores aren’t just a way to teach discipline — they’re a quiet form of systems thinking. I used to think success came from information. Now I think it comes from interaction — with effort, friction, and consequence. When a child folds clothes or washes dishes, they’re not just learning responsibility. They’re learning causality — that their actions can shape their environment. That’s the seed of agency, and in my view, the foundation of all learning. Here’s what this study really points to: → Chores connect effort to outcome. They teach the mind to see progress as earned, not given. → Screens disconnect action from effect. We react constantly, but change nothing. → Causality builds confidence. The more a child sees impact, the more they believe their effort matters. That’s not just psychology — that’s neurology. The brain builds reward loops around whatever it can control. When effort produces order, we feel grounded. When it doesn’t, we drift. Here’s how I think we can bring that loop back 👇 ✅ Reconnect effort with outcome. Let kids see what their actions change — even in small ways. ✅ Reward contribution, not compliance. Praise what they build, not what they finish. ✅ Normalize friction. The hard way isn’t punishment — it’s practice for the real world. In my view, chores don’t just prepare children for life — they simulate it. They teach the one rule that never changes: nothing improves until you act. 💭 So what do you think — are we overeducating kids in knowledge, but undertraining them in consequence? #Parenting #Education #ChildDevelopment #CognitiveGrowth #LifeSkills #FutureOfLearning

Static textbooks might be outdated soon... Learn Your Way — Google's AI-powered learning tool, is one of the most thoughtful experiments I’ve seen in AI + education. It can turn a simple PDF into five personalized learning formats in one click. And instead of one-size-fits-all lessons, it adapts to you: Pick your grade level + interests → the content reshapes itself. ---- Into space? Physics comes with rocket examples. ---- Learning to code? It adjusts to your experience level. Where it’s at now: • Live in Google Labs as an official research experiment • Built on Google’s LearnLM + Gemini (pedagogy-first AI stack) 💡What it already does well: 🔹 Converts content into multiple formats (read, listen, slides, mind maps) 🔹 Built-in quizzes + adaptive feedback 🔹 Contextual examples that actually feel relevant 🔹 Low-effort learning modes (like audio on commutes) *Still early-stage (can’t upload your own materials yet, in tester phase), but what’s there already shows what AI + education could look like. Fun to explore,  Link’s in the comments. __________ For more on AI and learning materials, plz check my previous posts. Alex Wang #education #ai #generativeai #edtech

I graduated from the Wharton MBA a year ago, and here’s what I wish someone had told me before I started about recruiting, mindset, and social life. If you're starting this fall, this is for you! 1️⃣ Business school is a buffet (and you'll get indigestion if you try everything) First few weeks - take stock of everything it has to offer. Internships, fellowships, clubs, accelerators, etc. Then ruthlessly prioritize. Take what serves you and leave the buffet. (You’ll still feel FOMO and take on more than you should because you “paid for it” - that’s all part of the process!) 2️⃣ Pivoting is harder than you think Most people don’t get this until it’s too late - employers don’t recruit from MBA programs because they care that you have an MBA. They do it because MBAs filter for experiences/skillsets they want. You need to show them why you can do the job. The degree just gets you in the door - use the network to get the experience and build the skills. More people than you'd think go back to their old industries. 3️⃣ You'll have your "maybe I should recruit for consulting" moment Or banking. Even if you swore you'd never. We all do. When everyone's doing it, you'll second-guess yourself. That's normal! Just remember why YOU came to school. Stick to your plan, not theirs. (Unless your plan was to recruit for consulting/banking) 4️⃣ The social scene is middle school, except people have money (but it’s not all bleak) Hundreds of type-A personalities in one place and a lot of bankers/consultants who didn’t have enough fun in their 20s = drama, hyper-socialization. Who's dating who, who got the Goldman interview, who wasn't invited to that trip…People will talk about you if you stand out (for good or bad reasons). First semester feels intense, especially if you’re an introvert. By second year, everyone chills out and you find your people. 5️⃣ You'll need to touch grass B-school is a bubble. If you're not careful, you'll think comparing signing bonuses and taking out loans to go on another trip with 20 people you just met are real life. See non-MBA friends. Call your family. There’s a hive-mindedness in business school. Don’t lose yourself in it. 6️⃣ The classes are hit or miss (so be strategic) You’ll keep some class notes for decades to come (If you’re going to Wharton - Negotiations, Legal Aspects of Entrepreneurship, Scaling Operations to name a few). You’ll throw away others before the semester is over. Talk to second-years about which classes are actually worth optimizing to get into. Bonus: Do something unexpected. Join the club you think you'd hate. Take the class outside your comfort zone. I signed up for a week-long backpacking trip in the Andes despite every instinct not to and ended up leading a trip to Antarctica my 2nd year (best MBA memory!). People getting an MBA: What's the one thing you're nervous about as you start your MBA? People who have an MBA: What’s the piece of advice you wish you got before you started?

This Teacher Changes 30 Lives Each Morning Here's Why This Works Every morning, a teacher greets her students one by one - not with rules, but with choice: A hug, A high-five, a nod, or quiet. A ritual so simple. Yet it tells 30 children: You are seen. You are safe. You belong. Here’s what this teaches us about leadership - and how to apply it at work: 1. Honor Autonomy (Self-Determination Theory) When people get to choose how they engage, they show up with more agency. Autonomy isn’t about letting go of structure - it’s about giving room to opt in. Try this: 🔷 Let people set their own work cadence - async, deep focus, or collaborative sprints 🔷 Ask: “What support looks best for you right now?” *** 2. Create Micro-Moments of Connection (Broaden-and-Build Theory) We don’t need hour-long one-on-ones to build trust. A genuine check-in. A name spoken with intention. That’s the glue. Try this: 🔷 Pause to celebrate effort, not just outcomes - a quick voice note, a public thank-you 🔷 Remember small details - a kid’s soccer game, a partner’s surgery - and follow up *** 3. Signal Safety in Small Ways (Polyvagal Theory) The nervous system responds before the intellect does. Safety is felt first. And safe leaders create brave spaces. Try this: 🔷 Ask: “Is now a good time?” before giving feedback or asking for decisions 🔷 Stay calm and present, especially when tensions rise - your tone sets the tone *** 4. Design for Anticipatory Joy (Affective Forecasting) The brain lights up for what’s coming next. The ritual at the door gave students a reason to show up smiling. Try this: 🔷 Drop a kind, unexpected message in the team chat - just because 🔷 Celebrate mundane milestones - 100 days in the role, 50th client call, 1st brave no *** 5. Anchor Culture in Meaningful Rituals (Harvard Research on Rituals) Rituals are memory-makers. They codify values in action - they say, this is who we are. Try this: 🔷 End each quarter with storytelling: what stretched us? what did we learn? 🔷 Welcome new hires not with logistics, but with a story of your team's "why" *** This teacher didn’t redesign the curriculum. She redesigned how people enter the day. You don’t need a big title to lead like that - Just the courage to meet people at the door. 💬 What’s one ritual you’ve seen shift the energy of a space - or want to create where you work? 🔁 Repost to inspire kind actions in the workplace. 🔔 Follow Bhavna Toor for more on conscious leadership.

✨ New resource: a PM Performance Evaluation template Throughout my 15+ years as a PM, I’ve consistently felt that ladder-based PM performance evaluations seem broken, but I couldn’t quite find the words to describe why. Early on in my PM career, I was actually part of the problem — I happily created or co-created elaborate PM ladders in spreadsheets, calling out all sorts of nuances between what “Product Quality focus” looks like at the PM3 level vs. at the Sr. PM level. (looking back, it was a non-trivial amount of nonsense — and having seen several dozens of ladder spreadsheets at this point, I can confidently say this is the case for >90% of such ladder spreadsheets) So that led me to develop the Insight-Execution-Impact framework for PM Performance Evaluations, which you can see in the picture below. I then used this framework informally to guide performance conversations and performance feedback for PMs on my team at Stripe — and I have also shared this with a dozen founders who’ve adapted it for their own performance evaluations as they have established more formal performance systems at their startups. And now, you can access this framework as an easy to update & copy Coda doc (link in the comments). How to use this template as a manager? In a small company that hasn’t yet created the standard mess of elaborate spreadsheet-based career ladders, you might consider adopting this template as your standard way of evaluating and communication PM performance (and you can marry it with other sane frameworks such as PSHE by Shishir Mehrotra to decide when to promote a given PM to the next level e.g. GPM vs. Director vs. VP). In a larger company that already has a lot of legacy, habits, and tools around career ladders & perf, you might not be able to wholesale replace your existing system & tools like Workday. That is fine. If this framework resonates with you, I’d still recommend that you use it to actually have meaningful conversations with your team members around planning what to expect over the next 3 / 6 / 9 months and also to provide more meaningful context on their performance & rating. When I was at Stripe, we used Workday as our performance review tool, but I first wrote my feedback in the form of Insight - Execution - Impact (privately) and then pasted the relevant parts of my write-up into Workday. So that’s it from me. Again, the link to the template is in the comments. And if you want more of your colleagues to see the light, there’s even a video in that doc, in which I explain the problem and the core framework in more detail. I hope this is useful.

🥦Spain is leading the way on healthy sustainable school food 🇪🇸 In 2022 Spain updated its dietary guidelines to be more in line with the latest science on healthy sustainable diets (EAT-Lancet Planetary Health Diet). Now they are pioneering implementation -- having just passed a new royal decree on school food that brings what is served in line with NDG recommendations. The aim of this decree is for all children, regardless of family income level, to have access to healthy, nutritious meals at school. 🌟Highlights 🥩Meat to be served maximum three times a week. Red meat maximum once a week, processed meats maximum twice a month 🍇Focus on local, seasonal food -- 45% fruit and veg served must be in season 🫘Ramping up legumes -- to be served 1-2 times a week minimum in a variety of ways including as primary protein source in a main, or as part of a starter or side dish. Only 14% of schools currently serve legumes once a week 🚫Limits on processed foods -- pre-prepared options like pizzas, empanadillas, and croquetas can only be served once a month, and sugar-sweetened beverages, energy drinks and processed snacks will be banned from vending machines and school cafes 🍆Fully plant-based menus available for children who want them ⏰The new decree comes into effect next term, in all 17.000 Spanish schools (primary and secondary, public and private) This is an amazing step forwards, and I'm excited to see healthy sustainable food in Spanish school canteens. To ensure the policy vision becomes a reality on the 'school floor', compliance monitoring and enforcement will be key, as well as securing catering suppliers who are able to rapidly meet these new needs. Photo credit: Manu Garcia, La voz del sur. #foodpolicy #schoolfood #healthydiets #sustainablediets #publichealth #spain

Performance Management in the Age of AI: the new 3‑Dimensional Model For decades, the 9‑box grid shaped how organizations assessed talent—mapping individuals along two familiar axes: ✔ Business performance (“what”) ✔ Behaviors or potential (“how”) Over time, many companies moved away from this model, concluding it oversimplified the complexity of human performance and sometimes reinforced bias more than it reduced it. AI is fundamentally reshaping work, shortening the lifecycle of skills and creating new capability demands at a pace conventional frameworks were never designed to keep up with. As a result, a new paradigm for performance management is emerging. Organizations are starting to consider a three‑dimensional approach to performance—one that integrates not just what people deliver and how they behave, but also how they grow. The new 3D model consists of three axis: 1. Business Results: Measures impact, delivery, and contribution to outcomes. 2. Behaviors / Ways of Working: Captures collaboration, leadership etc. and.. 3. Skills Development: Assesses capability building, learning velocity, and readiness for future roles. The third axis reflects a simple reality: In an AI‑driven workforce, continuous skills development is no longer optional—it’s strategic. IBM has begun to formalize this multidimensional view in its talent and rewards model. Their approach includes: 1. Integrating skills into pay: Base pay and equity linked to skill progression. 2. Balancing objectives: Business and skills goals carry equal weight 3. Future skills visibility: Regular communication on evolving skill requirements see: https://lnkd.in/eTDE-XmE Not every organization can replicate this model at scale, but it illustrates where performance management is heading. The central questions are shifting. Not just: “Did someone deliver results?” But also: “Are they developing the skills the organization will need next?” and “Are they learning at the speed the environment requires?” The move from a 2D grid to a 3D, capability‑driven framework may become one of the most consequential shifts in performance management in the age of AI—signaling a future where growth, adaptability, and skill relevance stand on equal footing with results.