Engineering

Roadmap to Learn Agentic AI This roadmap breaks down the journey into 12 focused stages: – Grasp the core differences between traditional AI and autonomous agents – Build a solid foundation in ML, LLMs, and frameworks like LangGraph, CrewAI, and AutoGen – Understand how agents use memory, plan actions, and collaborate – Learn to implement retrieval-augmented generation (RAG) and adaptive reinforcement learning – Deploy agents in real-world scenarios with performance monitoring and continuous improvement If you're building AI that goes beyond chat interfaces, this roadmap will help you architect systems that are capable, contextual, and action-oriented. Feel free to save or share if you find it valuable.

Scaling from 50 to 100 employees almost killed our company. Until we discovered a simple org structure that unlocked $100M+ in annual revenue. In my 10+ years of experience as a founder, one of the biggest challenges I faced in scaling was bridging the organizational gap between startup and enterprise. We hit that wall at around 100~ employees. What worked beautifully with a small team suddenly became our biggest obstacle to growth. The problem was our functional org structure: Engineers reporting to engineering, product to product, business to business. This created a complex dependency web: • Planning took weeks • No clear ownership  • Business threw Jira tickets over the fence and prayed for them to get completed • Engineers didn’t understand priorities and worked on problems that didn’t align with customer needs That was when I studied Amazon's Single-Threaded Owner (STO) model, in which dedicated GMs run independent business units with their own cross-functional teams and manage P&L It looked great for Amazon's scale but felt impossible for growing companies like ours. These 2 critical barriers made it impractical for our scale: 1. Engineering Squad Requirements: True STO demands complete engineering teams (including managers) reporting to a single owner. At our size, we couldn't justify full engineering squads for each business unit. To make it work, we would have to quadruple our engineering headcount. 2. P&L Owner Complexity: STO leaders need unicorn-level skills: deep business acumen and P&L management experience. Not only are these leaders rare and expensive, but requiring all these skills in one person would have limited our talent pool and slowed our ability to launch new initiatives. What we needed was a model that captured STO's focus and accountability but worked for our size and growth needs. That's when we created Mission-Aligned Teams (MATs), a hybrid model that changed our execution (for good) Key principles: • Each team owns a specific mission (e.g., improving customer service, optimizing payment flow) • Teams are cross-functional and self-sufficient,  • Leaders can be anyone (engineer, PM, marketer) who's good at execution • People still report functionally for career development • Leaders focus on execution, not people management The results exceeded our highest expectations: New MAT leads launched new products, each generating $5-10M in revenue within a year with under 10 person teams. Planning became streamlined. Ownership became clear. But it's NOT for everyone (like STO wasn’t for us) If you're under 50 people, the overhead probably isn't worth it. If you're Amazon-scale, pure STO might be better. MAT works best in the messy middle: when you're too big for everyone to be in one room but too small for a full enterprise structure. image courtesy of Manu Cornet ------ If you liked this, follow me Henry Shi as I share insights from my journey of building and scaling a  $1B/year business.

Exciting updates on Project GR00T! We discover a systematic way to scale up robot data, tackling the most painful pain point in robotics. The idea is simple: human collects demonstration on a real robot, and we multiply that data 1000x or more in simulation. Let’s break it down: 1. We use Apple Vision Pro (yes!!) to give the human operator first person control of the humanoid. Vision Pro parses human hand pose and retargets the motion to the robot hand, all in real time. From the human’s point of view, they are immersed in another body like the Avatar. Teleoperation is slow and time-consuming, but we can afford to collect a small amount of data.  2. We use RoboCasa, a generative simulation framework, to multiply the demonstration data by varying the visual appearance and layout of the environment. In Jensen’s keynote video below, the humanoid is now placing the cup in hundreds of kitchens with a huge diversity of textures, furniture, and object placement. We only have 1 physical kitchen at the GEAR Lab in NVIDIA HQ, but we can conjure up infinite ones in simulation. 3. Finally, we apply MimicGen, a technique to multiply the above data even more by varying the *motion* of the robot. MimicGen generates vast number of new action trajectories based on the original human data, and filters out failed ones (e.g. those that drop the cup) to form a much larger dataset. To sum up, given 1 human trajectory with Vision Pro  -> RoboCasa produces N (varying visuals)  -> MimicGen further augments to NxM (varying motions). This is the way to trade compute for expensive human data by GPU-accelerated simulation. A while ago, I mentioned that teleoperation is fundamentally not scalable, because we are always limited by 24 hrs/robot/day in the world of atoms. Our new GR00T synthetic data pipeline breaks this barrier in the world of bits. Scaling has been so much fun for LLMs, and it's finally our turn to have fun in robotics! We are creating tools to enable everyone in the ecosystem to scale up with us: - RoboCasa: our generative simulation framework (Yuke Zhu). It's fully open-source! Here you go: http://robocasa.ai - MimicGen: our generative action framework (Ajay Mandlekar). The code is open-source for robot arms, but we will have another version for humanoid and 5-finger hands: https://lnkd.in/gsRArQXy - We are building a state-of-the-art Apple Vision Pro -> humanoid robot "Avatar" stack. Xiaolong Wang group’s open-source libraries laid the foundation: https://lnkd.in/gUYye7yt - Watch Jensen's keynote yesterday. He cannot hide his excitement about Project GR00T and robot foundation models! https://lnkd.in/g3hZteCG Finally, GEAR lab is hiring! We want the best roboticists in the world to join us on this moon-landing mission to solve physical AGI: https://lnkd.in/gTancpNK

#Diversity in high-tech fields remains critically low. The Equal Employment Opportunity Commission (EEOC) recently reported that #Black and #Latino professionals are underrepresented in high-tech roles, especially in leadership. These numbers highlight ongoing structural barriers in hiring, promotion and retention. This gap is a missed opportunity to tap into a wealth of diverse talent and perspectives essential to the future of tech. However, addressing and thoroughly fixing these challenges will require time, consistent effort and a long-term commitment to systemic change. Companies can support the progression of representation in tech by investing in training, mentorship and internship opportunities that open doors for people who were historically shut out. Programs like internXL, a platform that is committed to increasing diversity and inclusion in the internship hiring process for top companies, are making a significant impact. Similarly, the expansion of STEM education at institutions like Cornell University is helping to connect talented young people from underrepresented communities with opportunities for high-tech careers. When we work together to remove these barriers, we’re fostering a more inclusive workforce and strengthening innovation, problem-solving and leadership in the industry. Let’s build a tech future that reflects the diversity of our society. https://bit.ly/3UNtOCh

5 key developments this month in Wearable Devices supporting Digital Health ranging from current innovations to exciting future breakthroughs. And I made it all the way through without mentioning AI… until now. Oops! >> 🔘Movano Health has received FDA 510(k) clearance for its EvieMED Ring, a wearable that tracks metrics like blood oxygen, heart rate, mood, sleep, and activity. This approval enables the company to expand into remote patient monitoring, clinical trials, and post-trial management, with upcoming collaborations including a pilot study with a major payor and a clinical trial at MIT 🔘ŌURA has launched Symptom Radar, a new feature for its smart rings that analyzes heart rate, temperature, and breathing patterns to detect early signs of respiratory illness before symptoms fully develop. While it doesn’t diagnose specific conditions, it provides an “illness warning light” so users can prioritize rest and potentially recover more quickly 🔘A temporary scalp tattoo made from conductive polymers can measure brain activity without bulky electrodes or gels simplifying EEG recordings and reducing patient discomfort. Printed directly onto the head, it currently works well on bald or buzz-cut scalps, and future modifications, like specialized nozzles or robotic 'fingers', may enable use with longer hair 🔘Researchers have developed a wearable ultrasound patch that continuously and non-invasively monitors blood pressure, showing accuracy comparable to clinical devices in tests. The soft skin patch sensor could offer a simpler, more reliable alternative to traditional cuffs and invasive arterial lines, with future plans for large-scale trials and wireless, battery-powered versions 🔘According to researchers, a new generation of wearable sensors will continuously track biochemical markers such as hydration levels, electrolytes, inflammatory signals, and even viruses, from bodily fluids like sweat, saliva, tears, and breath. By providing minimally invasive data and alerting users to subtle health changes before they become critical, these devices could accelerate diagnosis, improve patient monitoring, and reduce discomfort (see image) 👇Links to related articles in comments #DigitalHealth #Wearables

How much do laypersons around the world know about IP? If they know about it, do they have a positive or negative perception of it? And are these changing over time? To answer these important questions which cut right to the heart of popular views and support for IP, we launched WIPO Pulse two years ago – the first ever global survey on IP, covering 50 countries. Now we’ve launched the second edition – this time covering 35,500 laypersons from 74 countries in all regions of the world. The results are interesting and insightful. First, the world is getting savvier about IP. Awareness has grown across all main IP rights since 2023. Copyright and trademarks still lead the pack (no big surprise – music, art, entertainment are fundamental to our lives), but with patents and designs continuing to trail a bit when it comes to public understanding. Second, confidence in the positive impact of IP on the economy remains strong, with two-thirds of respondents (64%) agreeing that IP benefits the economy. Here is where there is a twist – just like in 2023, Asia, Africa and Latin America remain the regions with the most positive perception about IP’s economic benefits, with lower positive perceptions in Western Europe and North America. I welcome your views on this. Third, we were interested in understanding perception among women and youth. Here, we see some gains in awareness among both groups. In Asia-Pacific, awareness rose across all five IP rights for both groups. Western Europe also saw broad gains well. However, youth awareness dipped slightly in Latin America and Eastern Europe. The data we collected is really a wealth of insights that is begging for further investigation. They are valuable not just for WIPO, but the global IP community and local IP institutions, and we will use it to sharpen global, regional and local awareness building, outreach and engagement efforts, as well as combine it with other datasets like the Global Innovation Index to build a deeper picture of the global IP landscape. More: https://lnkd.in/eZ96P-ZJ Photos: WIPO/Berrod #WIPO #IntellectualProperty #Trademark #Patent #Design #Copyright #GeographicalIndications

When I started leading a high-powered recruiting team, I had the traits of the TYRANT leaders I now call out. Here's why: Despite my degrees, certificates, and ongoing professional development, nothing prepared me to transition into leading. I still had an individual contributor (IC) mindset, which unintentionally led me to compete with my very capable team. At the time, I engaged in behaviors like: Taking over projects instead of developing my team. Working long hours, thinking it showed commitment. Making unilateral decisions vs collaborating. Giving orders instead of providing clarity and context. Hoarding information instead of communicating transparently. Prioritizing my metrics over team goals. A month in, my boss at the time sat down with me and told me to own my transition and to stop taking over work when someone asked for help. (she's one of the best Leader's I've ever had) To transform my mindset, I sought out a few internal sponsors and observed how they managed their teams. I also asked my team for feedback on where I could do better. Once I made the changes: mindset and action, I began demonstrating new leadership behaviors: Coaching my team and developing their problem-solving skills. ↳Created an authorization matrix to empower them to make decisions. Promoting work-life balance through prioritization and delegation. ↳I stopped working on vacation to set a better example. Making collaborative decisions to increase buy-in. ↳They worked on the reqs, so I asked for their ideas and where I could implement them. Painting a vision and equipping the team to get there themselves. ↳I translated the organization's vision down to how it affected our team goals. Openly communicating to build trust and transparency. ↳I promoted democratic decision-making and explained when it needed to be autocratic. Aligning on and championing team goals over my individual metrics. ↳I held weekly reviews where I celebrated their success because it was OUR success. Here's what I want you to take from this: 1. Develop your team's skills rather than trying to be the expert. 2. Delegate decisions to increase buy-in and leverage diverse perspectives. 3. Openly share information rather than hoarding knowledge and insight. 4. Recognize and elevate your team's contributions rather than taking individual credit. #aLITTLEadvice #leadership

“𝐘𝐨𝐮 𝐝𝐨𝐧’𝐭 𝐡𝐚𝐯𝐞 𝐭𝐡𝐞 𝐫𝐞𝐥𝐞𝐯𝐚𝐧𝐭 𝐰𝐨𝐫𝐤 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞..." That’s what they told me, too. When I transitioned from taxation to Investment Banking, mergers & acquisitions, I heard it all— ❌ “You don’t have the right background.” ❌ “It’s too late to switch now.” ❌ “Start from scratch or stay where you are.” But I refused to let a job title define my future. Instead, I focused on what I did have: Analytical skills, Financial acumen, and the ability to solve complex problems. I learned, I networked, and I proved my worth. Your “irrelevant” experience is actually your secret weapon. Most people think: ❌ “I need to hide my background in marketing now that I’m going into tech.” Smart people think: ✅ “My marketing background gives me a unique edge in tech because I understand user psychology in ways pure technical people never will.” Remember, career transitions aren’t about starting over. They’re about repositioning yourself. If you're looking to make a switch, here’s how to do it without wasting years: 1️⃣ Leverage Transferable Skills – Your past experience holds value. Learn to reframe it. 2️⃣ Start creating before you apply – Proof of work speaks louder than any resume. 3️⃣ Network with Intent – The right conversations open doors faster than cold applications. 4️⃣ Position your experience strategically – A compelling story beats a perfect background. 5️⃣ Upskill smartly – Learn what actually matters for your new role. I know how tough it can be because I’ve been there. But I also know that making a career pivot is possible—without starting from scratch. If you’re looking to transition careers and don’t know where to start, let’s talk. I’d love to help. Drop a comment or DM me. Your past doesn’t define your future. You do. LinkedIn LinkedIn News India LinkedIn Guide to Creating #mindset #career #transition #knowledge #skills #upskill

Just as routine stress tests help us understand our own health, medical technology goes through its own set of trials to earn its place in a clinical setting. An MRI, for example, faces a battery of stress tests: steel balls dropped on heated surfaces to check for cracks, robotic arms repeatedly plugging and unplugging connectors to make sure all signals work properly, patient tables loaded with hundreds of kilograms to measure strength and endurance, vibrating floors to test precision and quality. Our factory teams scrutinize every detail – and imagine every scenario – to ensure the device will meet the daily demands of patient care in any kind of environment. Safety, reliability, and quality are non-negotiable. We must be absolutely confident that our systems will perform not only on day one, but also when faced with unexpected and urgent situations. This trust is more than a technical requirement – it’s fundamental to healthcare. When clinicians know their technology can handle challenges, they can fully focus on their patients and on delivering care with comfort and hope. For patients, this assurance means peace of mind and being able to focus on the truly important task at hand: healing.