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sional and job ads on and off linkedin learn more in our cookie policy select accept to consent or reject to decline non essential cookies for this use you can update your choices at any time in your settings accept reject skip to main content linkedin top content people learning jobs games join now sign in top content user experience explore top linkedin content from expert professionals andrew ng andrew ng is an influencer deeplearning ai ai fund and ai aspire 2 649 546 followers 3mo report this post loop engineering is a hot buzzphrase after mentions of it by boris cherny claude code s creator and peter steinberger openclaw s creator went viral on social media loops are now a key part of how we get ai agents to iterate at length to build software in this letter i d like to share my 3 key loops shown in the image below for building 0 to 1 products these loops guide not just how i build software but also how i decide what software to build agentic coding loop given a product specification and optionally a set of evals that is a dataset against which to measure performance we can have an ai agent write code test its work and keep iterating until the code is bug free and meets its specification this idea of closing the loop took off around the end of last year and it has been a game changer in enabling coding agents to work longer productively without human intervention for example over the weekend i was building an app for my daughter to practice typing and my coding agent could easily work for around an hour using a web browser to check what it had built multiple times before getting back to me without needing my intervention the engineering loop executes quickly every few minutes the coding agent might build and test a new version of the software i hear frequently from developers who are finding new ways to engineer more effective engineering loops this is an active area of invention developer feedback loop in this loop a developer examines the current product and steers the coding agent to improve it last year a lot of developers including me were acting as the qa quality assurance function for our coding agents manually finding bugs and then asking the agent to fix them but with coding agents much more able to test their own code the amount of time we need to spend on this function has decreased significantly this allows us to make higher level product decisions such as what key features to offer where the ui needs improvement and so on the developer feedback loop operates over time intervals between tens of minutes and hours that s how frequently a developer might review a product and give feedback in the case of the typing app i changed my mind a few times about the visual design what cat costumes she can unlock as she learns she loves cats and the user flow for a grown up to log in and steer the child s learning experience when a developer has a clear vision for what to build it is still a lot of work to translate that vision into a specification for a coding agent to implement further after the developer has seen an implementation they might update or perhaps clarify the spec to steer it toward what they want if you find that the system repeatedly runs into certain problems building a set of evals for the agent becomes useful truncated for length full text https lnkd in gkdq6h9s more no more previous content no more next content 9 215 613 comments like comment share copy linkedin facebook x brij kishore pandey ai architect engineer agentic systems rag ai infrastructure data engineering 738k linkedin 294k instagram newsletter for 250k ai builders 739 945 followers 4mo report this post 𝗡𝗮𝗶𝘃𝗲 𝗥𝗔𝗚 𝘄𝗼𝗿𝗸𝘀 𝗶𝗻 𝗮 𝗱𝗲𝗺𝗼 𝗜𝘁 𝗳𝗮𝗶𝗹𝘀 𝘁𝗵𝗲 𝗺𝗼𝗺𝗲𝗻𝘁 𝗿𝗲𝗮𝗹 𝘂𝘀𝗲𝗿𝘀 𝘀𝗵𝗼𝘄 𝘂𝗽 embed retrieve generate looks clean in a notebook real requirements break it questions whose answer is spread across many documents industry terms that embeddings get wrong bad chunks the pipeline never catches answers that live in how things connect not in any single chunk pdfs full of tables and images a text only index cannot read these 5 architectures are how serious teams stay ahead in the agentic ai era 𝟬𝟭 𝗛𝘆𝗯𝗿𝗶𝗱 𝗥𝗔𝗚 dense vectors find meaning bm25 finds exact words reciprocal rank fusion combines both ranked lists a safe baseline for almost every team 𝟬𝟮 𝗚𝗿𝗮𝗽𝗵𝗥𝗔𝗚 pull entities and their relationships into a knowledge graph retrieve subgraphs and community summaries not chunks best when the answer lives in how things connect 𝟬𝟯 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗥𝗔𝗚 a planner agent picks the right tool vector web or sql a reasoner agent keeps trying until the answer is solid retrieval becomes a plan not a single step 𝟬𝟰 𝗖𝗼𝗿𝗿𝗲𝗰𝘁𝗶𝘃𝗲 𝗥𝗔𝗚 𝗖𝗥𝗔𝗚 grade every retrieval before you trust it correct answer unclear rewrite the query wrong search the web this is what production rag actually looks like 𝟬𝟱 𝗠𝘂𝗹𝘁𝗶𝗺𝗼𝗱𝗮𝗹 𝗥𝗔𝗚 one embedding model clip colpali for text images and tables one vector index one multimodal llm no more separate pipelines for pdfs with charts i built a runnable example for each of the five patterns github link in the first comment the best teams in 2026 do not pick one they combine them hybrid retrieval inside an agentic loop with a corrective grader over a multimodal index naive rag is a starting point not a finish line that is why most enterprise genai projects stall at the demo which of these five becomes the default rag stack in the next 18 months and which stays a specialized tool more no more previous content no more next content 4 498 120 comments like comment share copy linkedin facebook x michael miebach michael miebach is an influencer chief executive officer at mastercard 198 535 followers 7mo report this post for decades buying something has relied on a simple visible sign of intent you tap your card or hit buy online and everyone knows exactly what you agreed to that clear moment of yes is what s made commerce work but what happens when that equation changes what s required is not just smarter tech but a new model of trust with privacy at the center as agents take on more tasks for us trust can t rely on a single click or tap it must be recorded verified and shared mastercard is working with partners like google adyen checkout com fiserv worldpay ibm getnet and basis theory to keep people in control and businesses confident agents are authorized to transact in a world where we delegate actions intent must be clear and easy to verify more no more previous content no more next content 8 350 435 comments like comment share copy linkedin facebook x pascal bornet 1 ai automation thought leader award winning expert best selling author recognized keynote speaker agentic ai pioneer forbes tech council 2m followers ️ 1 541 840 followers 11mo report this post when transport learns to think green i came across a concept today that stopped me an autonomous hydrogen truck trailer drone designed for long distance freight at first it looked like another futuristic vehicle but then it hit me this isn t just transport evolving it s intent evolving for decades we ve designed logistics around speed and scale now we re finally designing around sustainability this new concept merges autonomy aerodynamics and hydrogen power to do something radical eliminate carbon emissions in heavy freight cut operational energy costs through intelligent routing reduce highway congestion with coordinated drone convoys it s not just engineering it s a shift in philosophy a move from moving faster to moving responsibly we often talk about green tech as a feature but the real shift happens when sustainability becomes the invisible infrastructure behind innovation it s not an addition to progress it is progress what s needed now isn t more invention it s integration we need to build networks where clean energy and automation reinforce each other redefine efficiency to include environmental balance shift from carbon offsetting to carbon prevention at design level because the next breakthrough won t come from faster engines but from systems that make waste impossible by design that s when technology stops being an experiment in innovation and becomes an expression of intelligence so here s the question i keep returning to will the next era of transport be powered by fuel or by foresight innovation sustainability hydrogen autonomousvehicles greentech logistics futurethinking more 2 390 138 comments like comment share copy linkedin facebook x felix haas design at lovable sequoia scout angel investor 105 728 followers 1y report this post invisible ux is coming and it s going to change how we design products forever for decades ux design has been about guiding users through an experience we ve done that with visible interfaces menus buttons cards sliders we ve obsessed over layouts states and transitions but with ai a new kind of interface is emerging one that s invisible one that s driven by intent not interaction think about it you used to open spotify scroll through genres click into focus pick a playlist now you just say play deep focus music no menus no tapping no ui just intent output you used to search on airbnb pick dates guests filters scroll through 50 listings now we re entering a world where you guide with words find me a cabin near oslo with a sauna available next weekend so the best ux becomes barely visible why does this matter because traditional ux gives users options ai native ux gives users outcomes old ux here are 12 ways to get what you want new ux just tell me what you want we ll handle the rest and this goes way beyond voice or chat it s about reducing friction designing systems that understand intent respond instantly and get out of the way the ui isn t disappearing it s mainly dissolving into the background so what should designers do rethink your role going forward you ll not just lay out screens you ll design interactions without interfaces that means understanding how people express goals guiding model behavior through prompt architecture creating invisible guardrails for trust speed and clarity you are basically designing for understanding the future of ux won t be seen it will be felt welcome to the age of invisible ux ready for it more no more previous content no more next content 3 583 419 comments like comment share copy linkedin facebook x andreas horn founder human in the loop 257 049 followers 1y report this post mckinsey company 𝗯𝗹𝘂𝗲𝗽𝗿𝗶𝗻𝘁 𝗳𝗼𝗿 𝗵𝗼𝘄 𝗯𝗮𝗻𝗸𝘀 𝗰𝗮𝗻 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗲𝘅𝘁𝗿𝗮𝗰𝘁 𝗿𝗲𝗮𝗹 𝘃𝗮𝗹𝘂𝗲 𝗳𝗿𝗼𝗺 𝗔𝗜 ️ this is a full stack enterprise grade architecture built on agents orchestration and rewired workflows the ai bank stack consists out of 4 key layers ️ 𝟭 𝗘𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗟𝗮𝘆𝗲𝗿 this is the user layer customers and employees mckinsey calls for fully reimagined intelligent personalized experiences across all channels multimodal chat text voice image omnichannel ux across mobile contact center branch digital twins for customer simulation and workforce training it s all about a ui refresh and ux overhaul grounded in real ai 𝟮 𝗔𝗜 𝗣𝗼𝘄𝗲𝗿𝗲𝗱 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗠𝗮𝗸𝗶𝗻𝗴 this is the brain of the ai first bank and it s not just predictive models anymore it s orchestrated agent ecosystems ai orchestrators plan reason delegate across workflows domain agents specialize in credit policy fraud risk legal copilots embedded in workflows to guide users and automate decisions mckinsey reports 20 60 productivity gains in decision making with this approach 𝟯 𝗖𝗼𝗿𝗲 𝗧𝗲𝗰𝗵 𝗗𝗮𝘁𝗮 the foundation layer most banks underestimate until genai models stall in production vector databases llm orchestration and finops search and retrieval engines ml pipelines secure data architecture api infrastructure the goal make data accessible tools reusable and infra invisible to the business without this nothing scales 𝟰 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝗠𝗼𝗱𝗲𝗹 this is where the transformation wins or fails without rewiring the org the tech doesn t matter ai control towers to track value and set guardrails cross functional teams across business tech and ai platform operating model for speed and alignment enterprise wide reuse of ai capabilities if you re building isolated projects without shared assets or central coordination you re not transforming you re experimenting 𝗪𝗵𝗮𝘁 𝘁𝗵𝗶𝘀 𝗮𝗹𝗹 𝗮𝗱𝗱𝘀 𝘂𝗽 𝘁𝗼 the banks that win won t be the ones with the most pilots they ll be the ones that industrialize agents orchestration and rewired workflows with full stack coordination full mckinsey article https lnkd in dpajzvk4 𝗜 𝗲𝘅𝗽𝗹𝗼𝗿𝗲 𝘁𝗵𝗲𝘀𝗲 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁𝘀 𝗮𝗻𝗱 𝘄𝗵𝗮𝘁 𝘁𝗵𝗲𝘆 𝗺𝗲𝗮𝗻 𝗳𝗼𝗿 𝗿𝗲𝗮𝗹 𝘄𝗼𝗿𝗹𝗱 𝘂𝘀𝗲 𝗰𝗮𝘀𝗲𝘀 𝗶𝗻 𝗺𝘆 𝘄𝗲𝗲𝗸𝗹𝘆 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿 𝗬𝗼𝘂 𝗰𝗮𝗻 𝘀𝘂𝗯𝘀𝗰𝗿𝗶𝗯𝗲 𝗵𝗲𝗿𝗲 𝗳𝗼𝗿 𝗳𝗿𝗲𝗲 https lnkd in dbf74y9e more no more previous content no more next content 5 832 211 comments like comment share copy linkedin facebook x dr martha boeckenfeld ai governance quantum keynote speaker board director advisor human centric futurist i help boards c suites close the governance gap host the edge of tomorrow ex ubs axa 162 013 followers 1y report this post this isn t a luxury this is a 200 wheelchair redefining what s possible for millions standing wheelchairs have always been out of reach until now at r2d2 iit madras a team dared to ask what if mobility wasn t a privilege but a right their answer is a simple innovation no big tech a wheelchair that lets you stand on your terms ingenious gas spring technology for seamless movement supports up to 242 pounds priced at 200 when others cost 2 000 or more but the true breakthrough isn t just in the engineering it s in the lives transformed physical freedom is restored stand tall when you choose reach the top shelf cook your own meals keep your body strong and active health is protected standing improves circulation strengthens bones prevents pressure sores aids digestion reduces heart risks social inclusion becomes reality converse at eye level join meetings no barriers participate fully in community life experience true belonging ask yourself when was the last time you had to look up just to be heard for millions that s every day this isn t only about standing it s about dignity it s about independence it s about living fully and for the first time it s within reach for those who need it most when innovation meets accessibility lives change this is technology for humanity follow me dr martha boeckenfeld for more stories of tech that matters ️ share with your network to learn more about how simple innovation can change people s live techforgood innovation healthcare more 10 646 394 comments like comment share copy linkedin facebook x ghazal alagh ghazal alagh is an influencer chief mama co founder mamaearth thedermaco dr sheth s aqualogica bblunt staze luminéve mamashark sharktank india artist fortune forbes most powerful woman in business 752 411 followers 1y report this post not ads not influencers this is what builds a d2c brand 8 years ago when varun alagh and i launched mamaearth we weren t the biggest brand we didn t have endless budgets or massive influencer deals what we had was intent we replied to every dm ourselves took feedback personally and obsessed over what one customer was trying ...