Miguel Fierro
4x AI Founder • xMicrosoft • I help people bridge the gap from learning AI theory to getting AI results using my method “Reverse Learning”
United Kingdom
79K followers
500+ connections
About
You see AI everywhere — in the news, in your company, in every job posting. And there's a voice in your head saying: "I'm falling behind."
You've tried to keep up. You use ChatGPT. You've taken courses, maybe have a certificate. And yet when someone asks "what can you do with AI?", you don't have an answer.
It's not your fault. The entire AI education industry is designed to sell you knowledge, not to help you build proof.
The professionals who are actually getting ahead with AI (hired at top tech companies, getting promoted, leading projects), have one thing in common: they've built something real, a result that can be verified.
I'm Miguel Fierro. I've spent 10 years at Microsoft building production AI. I'm the creator of Recommenders (20K+ GitHub stars, used by Fortune 500s) and 4x AI founder.
After 10 years at Microsoft, I noticed a pattern nobody talks about: companies don't want people who know AI theory, they want people who build useful AI and leaders who can drive that transformation.
At Microsoft, I watched this pattern again and again. The developer who shipped one real AI project got the offer over candidates with 10 courses on their resume. The business leader who automated one workflow got the promotion over colleagues who could only talk about AI.
The gap is never knowledge. It's proof.
- Developers don't need another tutorial, they need a deployed project, a clean GitHub repo, and a README that tells a story a recruiter can follow in 30 seconds.
- Business professionals don't need to learn to code, they need one working AI workflow that saves time or makes money, and a case study that proves it.
Now I help people bridge their careers to AI, by using a method called Reverse Learning: instead of months of theory first, you start by building and learn what you need along the way.
Some people I helped:
- Daniel Labbe: from Solution Architect to AI Engineer at Microsoft.
- Nikolaos Zavitsanos: from Software Engineer to AI Engineer at AWS.
- Paolo Colecchia: from Software Engineer to AI Engineer at Microsoft.
- Tanuja Bhamidipati: from Software Engineer to AI Solution Architect at Microsoft.
- ... and hundreds more.
If you're ready to stop stop collecting courses and start building proof, send me a DM, and I'll see how I can help you.
Courses by Miguel
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Recommendation Systems: A Practical Hands-On Introduction1h 18m
Recommendation Systems: A Practical Hands-On Introduction
By: Miguel González-Fierro
Activity
79K followers
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Miguel Fierro shared thisI asked ChatGPT what you admire about humans. Its final answer was: "So if I had to choose just one thing, it would be this: your ability to imagine a better future and then work, however imperfectly, toward making it real." Let's keep building fellow humans!
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Miguel Fierro shared thisThis is the reason I dedicated my life to AI and robotics. AI is the best way to make scientific and engineering progress. 🚀 OpenAI used an unreleased model, more capable than GPT-6 Astra, to solve the Navier-Stokes problem, a 90-year-old mathematical mystery behind how liquids and gases flow. Key Facts: * The Math: Navier-Stokes equations power weather forecasting and aerodynamics. OpenAI proved that smooth fluid motion can develop a "finite-time singularity" (infinite speed under specific vortex conditions). * How AI Did It: ~10,000 autonomous agents ran for 88 hours, generating a 165-page proof verified line-by-line via Lean code. * The $1,000,000 Prize: Clay Mathematics Institute offers $1M for solving Millennium Problems (only one other has ever been solved). OpenAI stated they will not claim the money. I studied the NS equations when I was studying engineering. I remember I found them super difficult to understand. If this doesn't make you start learning IA, I don't know what else to say.
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Miguel Fierro shared thisOne of the best ways to reduce the AI bill: LLM model routing. LLMRouter is an open source project that picks the model per request. Not per project. 𝗪𝗵𝗮𝘁 𝗶𝘁 𝗱𝗼𝗲𝘀. → 16+ routing strategies: KNN, SVM, MLP, graph-based, hybrid. → Multi-turn routing that keeps the conversation in context. → Multimodal routing for text, vision, and time series. → Routing memory that reuses past query-to-model decisions. Works with OpenAI, Anthropic, NVIDIA, and local models. 𝗧𝗵𝗲 𝗽𝗮𝗿𝘁 𝗻𝗼𝗯𝗼𝗱𝘆 𝘄𝗮𝗿𝗻𝘀 𝘆𝗼𝘂 𝗮𝗯𝗼𝘂𝘁. → A router is a model, so it drifts. → Your query mix in August is not your query mix in December. → Version the router. Log every decision. → Alert when the share of cheap-model routes moves. The question stopped being "which LLM is best?". It is "which LLM is best for this request?" Link: https://lnkd.in/eV-jCJ6R Bookmark this post.
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Miguel Fierro shared thisAI is down, there is a massive outage. OpenAI, Claude and xAI are down. What do you do where there is no AI?
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Miguel Fierro shared thisFDE interview. The hiring manager: "The agent got worse. Why?" The client flagged it this week. "I would check the logs and tweak the prompt" ends the interview. You cannot explain a regression you never measured. The strategy for running AI agents in production is not a bigger model. It is an eval stack. 11 things your LLM app needs before the next deploy. 𝗤𝘂𝗮𝗹𝗶𝘁𝘆. → An eval harness that runs before every deploy. → A golden dataset with 100+ test cases. → LLM-as-a-judge with calibrated scoring. → Regression detection that blocks bad deploys. 𝗦𝗮𝗳𝗲𝘁𝘆. → Hallucination rate with factuality checks. → Grounding quality with citation validation. → Safety evals for toxic or biased outputs. 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀. → Latency percentiles: p50, p95, p99. → Cost-quality curves for model selection. → Shadow deployments and canary releases with automatic rollback. → Dashboards with quality trends and alerts when quality drops. The pattern behind all 11 items. Treat AI quality like uptime. Not a vibe. A number you watch. What would you add to this list?
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Miguel Fierro shared thisHere's a question I get a lot. Where do I start my career? PG and LeCun answered... Someone asked Paul Graham what he would do if he were 17 today. Yann LeCun answered the same question. Their advice points in opposite directions. 𝗜𝗳 𝘆𝗼𝘂 𝗯𝘂𝗶𝗹𝗱 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝘀, 𝗳𝗼𝗹𝗹𝗼𝘄 𝗚𝗿𝗮𝗵𝗮𝗺. → Learn to build LLMs from scratch. → Train the most powerful one your hardware allows. → Borrowed hardware beats hardware you wish you had. 𝗜𝗳 𝘆𝗼𝘂 𝗹𝗼𝘃𝗲 𝘀𝗰𝗶𝗲𝗻𝗰𝗲, 𝗳𝗼𝗹𝗹𝗼𝘄 𝗟𝗲𝗖𝘂𝗻. → Ask why an LLM writes your essay but cannot clean your bedroom. → Study the topics that could solve that. → Design the architectures that come after LLMs. Graham bets on the technology that already works. LeCun bets on the problem nobody has cracked. Neither said wait until you are ready. The bottom line. Whatever you prefer. Start today. Let me know how I can help.
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Miguel Fierro shared this238,000 GitHub stars. Not a model. Not a framework. A memory for your agents. It is called ECC. One repo that makes coding agents work the way the best engineers use them. 261 installable skills, 64 agents, security scanning, ready-made workflows. Built by Affaan Mustafa at the Anthropic x Cerebral Valley hackathon. With Claude Code. 𝗧𝗵𝗲 𝗽𝗮𝗿𝘁 𝘁𝗵𝗮𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀: 𝘀𝗵𝗮𝗿𝗲𝗱 𝗺𝗲𝗺𝗼𝗿𝘆. → Agents share memory with compressed context across sessions. → What one agent learns, the next one starts with. → No more re-explaining your codebase every morning. 𝗔𝗻𝗱 𝗶𝘁 𝗶𝘀 𝗽𝗼𝗿𝘁𝗮𝗯𝗹𝗲. → The same skills run on Claude Code, Codex, Cursor, Gemini and Zed. → Write the behavior once. Reuse it everywhere. → Release 2.0.0 deployed itself, bot, announcements and all. The lesson is bigger than the repo. Stop rewriting the same prompts. Turn the behavior that works into portable infrastructure.
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Miguel Fierro shared thisFDE listings are up 729%. Salaries hit $785K. Most people can't name the job. FDE means Forward Deployed Engineer. The engineer who ships AI inside the client's business. Half software engineer, half consultant, half product manager. 𝗪𝗵𝘆 𝘁𝗵𝗲 𝗿𝗼𝗹𝗲 𝗲𝘅𝗽𝗹𝗼𝗱𝗲𝗱. → Models are capable. Enterprises still cannot deploy them. → Someone has to close that gap inside the client's walls. → That someone is the FDE. 𝗪𝗵𝘆 𝗶𝘁 𝗳𝗶𝘁𝘀 𝗰𝗮𝗿𝗲𝗲𝗿 𝘀𝘄𝗶𝘁𝗰𝗵𝗲𝗿𝘀. → The job is judged on shipped outcomes, not credentials. → Your domain experience becomes an asset, not a gap. → You already speak the language of the business. Every AI lab can train models. Very few people can make them work inside a real company. That skill is where the $785K comes from. Would you be interested in learning how to become an FDE? Let me know.
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Miguel Fierro shared thisIKEA replaced 8,500 jobs with AI. Then did something unexpected. Nobody got fired. An AI bot took over their customer service calls. The standard playbook says: lay off 8,500 people. IKEA ran the opposite play. 𝗧𝗵𝗲 𝗺𝗼𝘃𝗲. → Reskilled all 8,500 customer service employees. → Turned them into remote interior design advisors. → Sold the design expertise an AI bot cannot deliver. 𝗧𝗵𝗲 𝗿𝗲𝘀𝘂𝗹𝘁𝘀. → 8,500 jobs preserved and transformed. → A massive reinvestment in human capital and expertise. → $1.4 billion in extra revenue from the new human-led advisory service. AI took the repetitive calls. Humans moved up the value chain. Revenue and compassion at the same time. This is the kind of AI strategy I respect. Who else is choosing reskilling over layoffs?
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Miguel Fierro liked thisMiguel Fierro liked thisAI will NEVER be useful for cinematics. Mmm... well... let me show you something. A while back, cinematics were unaffordable for an indie game. The production cost alone makes it a dream you learn to forget. The last Streets of Rage 4 does not even have cinematics. Just static art animated with transitions. But I wanted cinematics to tell the ninjas' story. I showed Azure Jiro's first anime scene. It was the reason to start the journey. But why do two ninjas start a fight against a crime organization... Here's the reason... Revenge! This time, it was made with just one agent orchestrating 3 MCPs. Storyboard, shots, audio and music in a single workflow. Killing your own character is not easy. Doing it in 30 seconds of anime is harder. Here it is. 30 seconds. Full anime. Stack in comments!
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Miguel Fierro reacted on thisMiguel Fierro reacted on thisHard things in life: - Finishing an ultra-marathon - Boxing with a grizzlie bear - Team vibecoding (expecting consistency)
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Miguel Fierro liked thisMiguel Fierro liked thisThis is what sharing knowledge via LinkedIn Learning looks like. More than 46K learners, a lot of engagement and recognition, and the willingness to keep helping people understand complex topics in a simple manner. Here's to many more 🥂 thanks Natalie Pao, Susan Williams, Marjorie Page, Alyssa Pratt, Minyan He, Mary Treseler, Dione Johnson, Jason Hallows, Ash Blodgett and many others who helped me convert simple words and raw videos into high-quality, à la Hollywood content ❤️ 📽️ 🎬 #AITraining #LinkedInLearning #LinkedIn #ProfessionalDevelopment
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Miguel Fierro liked thisMiguel Fierro liked thisI’m really excited about this new chapter for Cegid. 🚀 With the merger of Cegid and Silae, we are bringing together complementary expertise, technology and talent with one clear ambition: to become a European Leader in AI-Driven Business Management Solutions supporting businesses and companies of all sizes. For our customers, this means an increasingly connected experience across payroll, banking, accounting and administration helping businesses and their advisors spend less time on administrative tasks and more time on what really matters. I’m also delighted to welcome Christian Pedersen as the new CEO of the Cegid Group. I look forward to working together as we continue building a leading European technology platform. A very warm welcome to everyone joining us from Silae. We are stronger together, and I’m convinced that the best is yet to come. Thank you to Silver Lake for supporting this next step in our journey. Exciting times ahead. 🚀
Experience
Education
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Massachusetts Institute of Technology - Sloan School of Management
Business Administration, Management and Operations
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Kings College London
PhD in robotics Robotics Excellent Cum Laude and Outstanding Thesis Award
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Activities and Societies: Humanoid robots, mobile robots, computer vision, learning from demonstration, skill innovation, intelligent systems, social robots, path planning, kinematics and dynamics
PhD at Universidad Carlos III de Madrid in collaboration with King's College of London. I had over supervisor from Carlos III and another from King's.
My thesis covers non-linear control, machine learning, postural planning and control of humanoid robots. Development of computer vision algorithms, objects' localization and environment mapping. Trajectory optimization and path planning using genetic algorithms and neural networks.
I was awarded the Outstanding Thesis Award of UC3M.…PhD at Universidad Carlos III de Madrid in collaboration with King's College of London. I had over supervisor from Carlos III and another from King's.
My thesis covers non-linear control, machine learning, postural planning and control of humanoid robots. Development of computer vision algorithms, objects' localization and environment mapping. Trajectory optimization and path planning using genetic algorithms and neural networks.
I was awarded the Outstanding Thesis Award of UC3M. A list of my publications can be found in https://github.com/miguelgfierro/publications. -
Universidad Carlos III de Madrid
Master in Robotics and Automation
Activities and Societies: Humanoid robots, Mobile robots, artificial vision, intelligent systems, social robots, spacial robots, path planning, kinematics and dynamics
First class honours (top 1%). Degree finished in half the time (9 months) where the normal duration is 1 year and a half.
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Universidad Carlos III de Madrid
Industrial Engineer Electrical Enginneering
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Activities and Societies: Physics, analog and digital electronics, control and robotics. Fluids, electromagnetism, partial and differential equations, mechanics, structure analysis, management, marketing, projects management.
First class honours (top 5%)
Publications
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Link to all scientific and technical publications
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See publicationIn this github repo https://github.com/miguelgfierro/publications you will find some of the publications that I have done during my career.
Patents
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ssm library: Image recognition and similarity for the fashion industry
Issued ES M-008319/2014
The solution is a visual search engine adapted to fashion products. The algorithm, named
Fashion Recognition, is able to recognize a garment in a picture and find a set of garments with a similar
appearance. The methodology is based on a pipeline consisting of segmentation, feature extraction, feature hashing and feature comparison.
Honors & Awards
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Top 11 Creator on LinkedIn 2025
Favikon
Included among the top 20 Spanish creators on LinkedIn
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Top Voice on LinkedIn 2025
LinkedIn
Given the Top Voice award for 2025.
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Leading voice in AI 2024
SmartDev
Named one of the leading voices in AI together with leaders in the field like Demis Hassabis (Nobel laureate), Yann LeCun (Turing award winner), Andrew Ng (founder of Coursera), Thomas Wolf (founder of Huggingface), and more.
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Teaching Excelence Award at IE University
IE University
Teaching Excellence Award for the course on Chatbots and Recommendation Systems.
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Top Voice on LinkedIn 2024
LinkedIn
Given the Top Voice award for 2024.
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2nd top AI creator in Spain on LinkedIn
Favikon
I have been recognized as the 2nd top AI creator in Spain on LinkedIn. I'm also among the top 200 creators on LinkedIn in Spain.
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Top AI Voice on LinkedIn 2023
LinkedIn
Given the Top AI Voice award for 2023.
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Data Scientist of the Year
Tech Leaders Awards UK
The Tech Leaders Awards recognise UK’s top tech leaders, innovators and disruptors, who have demonstrated value from the application of technology and drived disruptive innovation in large organizations.
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University Carlos III Excellence Alumni Award
Universidad Carlos III de Madrid
The Excellence Alumni Award is the highest honor bestowed by the University Carlos III on alumni. The award recognizes individuals who have demonstrated excellence in their professional careers.
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Silver medal at Passenger Screening Algorithm Challenge
Kaggle
Silver medal in the Kaggle competition of airport passenger screening (the competition with the highest prize so far $1.5M)
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Outstanding Thesis Award
Universidad Carlos III of Madrid
Outstanding Thesis Award in the Doctorate program of Electrical Engineering, Electronics and Automation.
This award is granted by the University to the best PhD thesis of the year 2015. -
Finalist of BBVA OpenTalent
BBVA
Finalist of the international startup competition OpenTalent among more than 900 projects in the category of technology and innovation.
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First prize in the 6th Enterpise Challenge at Universidad Carlos III of Madrid
Universidad Carlos III de Madrid
First position at the University Contest, award given by a Jury formed by Private Investors, Business School members and Business Angels.
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First Prize 2020 Startup Madrid
Olympic Games Organization for Madrid2020
We were selected to represent the olympic game spirit in the candidature of Madrid 2020 for the Olympic Games. The prize was provided by the City Council of Madrid.
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Finalist of Top Seeds Lab
Top Seeds Lab
We were selected as finalist to join Top Seeds Lab accelerator.
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First Prize Madrid Emprende
Universidad Autónoma de Madrid
We won the first prize Madrid Emprende X Premio CIADE al Emprendedor Universitario of Universidad Autónoma de Madrid among 200 projects.
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Finalist RedEmprendia challenge: Ideas en Acción
RedEmprendia
International competition for Spanish, Portuguese and South American spin-offs. Finalist among more than 300 projects.
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Winner of the VI RobotChallenge 2009 European Robotics Championship
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Robotic competition of minihumanoids hosted in Vienna. We achieved the first position in the sumo competition and second position in the running competition.
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