Armand Ruiz

Director Data Science & AI Elite

Leading the Product Management org for the AI Portfolio of products focused on Generative AI and Traditional ML. Products include: watsonx.ai and watsonx.gov

Vice President of AI Platform

I am building the world's largest team of 𝐀𝐈 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐬 by

- Recruiting hundreds of new engineers around the globe
- Reskilling our existing talent
- Offering them top-quality training in new-generation AI

Responsible for Pre-Sales Generative AI Pilots with the new IBM watsonx.ai Platform.

Director watsonx team - Client Engineering

Director of the group IBM Data Science Elite team. We prove the value of IBM Watson solutions by co-creating pilots with our customers. I managed a team of 90+ data scientists that worked on 100s of complex AI implementations.

Director Data Science

I manage a rockstar team of Product Managers leading the product portfolio of IBM Watson AI products.

Product Director - Product Management, Watson Studio and Machine Learning

Leading new Data Science products for IBM

Lead Product Manager - IBM Data Science and Watson Machine Learning

Bring Open Source data science tech to IBM stack

Product Manager for Data Science Open Source Extensibility 

In charge of Data Science projects in EMEA

Data Science Advocate - IBM Data Science & Machine Learning

Support sales in Data Science opportunities

Technical Seller Data Science & Smarter Cities

Internship to bring new innovations to IBM

Intern - Technical Software Engineer, Extreme Blue

Vodafone

Optimize 3G network coverage using Data Science

Data scientist - Radio Optimization Engineering

Federació Catalana de Tennis

Tennis Coach

VP of Product - AI Platform @IBM

As the Director of AI Engineering at IBM, I lead the watsonx team, a global group of over 1,000 AI Engineers who work on cutting-edge Generative AI solutions for various industries. With more than 12 years of experience in AI, I have a passion for democratizing practical AI skills and empowering professionals to leverage AI to transform their business.

Previously, I managed IBM's Data Science and AI Elite, delivering complex AI implementations for hundreds of clients. 

I also led the product management of IBM Watson Studio and Watson Machine Learning, an AI platform used by hundreds of customers and SaaS apps powered by AI. I hold a Master of Science in Telecommunications from Universitat Politècnica de Catalunya and speak three languages: Spanish, Catalan, French, and English.

Connect with me!

✉️ JOIN MY NEWSLETTER: Every Saturday morning, you'll get 1 actionable tip to launch and grow your AI strategies in business in less than 4 minutes. → GO HERE: https://www.nocode.ai/

📧 Email: armand@nocode.ai
X: @armand_ruiz


"It is kind of fun to do the impossible"
All opinions are my own and don't represent my employer.

Called it. 🎯 The Model Context Protocol (MCP) is officially moving to the Linux Foundation under the new Agentic AI Foundation.

I’ve been saying for a while that open governance is the only viable path forward for AI infrastructure. Today’s news proves it.

This brings Anthropic, OpenAI, Microsoft, Google, and others under one neutral banner. 

10,000+ active servers. 
97M+ SDK downloads. 
Zero vendor lock-in.

If you want an ecosystem to flourish, you have to open it up. The era of Agentic AI just got a serious upgrade.

Read the news here: https://lnkd.in/g7vy5-x2

At NeurIPS2025, Google presented Titans, a new architecture that combines the speed of RNNs with the performance of Transformers. 

The trade-off between infinite context and computational cost is the biggest hurdle in AI right now.

While Transformers are accurate but expensive to scale, and linear models are fast but lose detail, Titans delivers the best of both worlds by introducing Test-Time Memorization.

The Core Innovation: Instead of a static state, Titans uses a deep neural memory module that actively updates while running, utilizing a "Surprise Metric":
- Low Surprise: Routine data is processed efficiently without clogging memory.
- High Surprise: Anomalies and key details are instantly integrated into long-term memory.

The Results:
- Scales effectively to 2M+ token context windows.
- Outperforms larger models (including GPT-4) on extreme long-context reasoning benchmarks.
- Generalizes beyond text to genomics and time-series.

This is a move from passive processing to active, efficient learning.

Jensen just dropped a masterclass on the future of AI. 

It was great to hear from him in a long-format podcast conversation. 

Three key insights he shared:

1/ Human language is the new syntax: The "tech divide" is closing. You won't need C++ to code the future; you just need to speak.

2/ The "30-Day" Mindset: Nvidia operates like they are always 30 days from bankruptcy. This paranoia fuels their innovation and resilience.

3/ Safety is an engineering problem: Forget the sci-fi movie plots. AI safety is just like cybersecurity—as capabilities rise, so do the guardrails.

Pic taken during my epic commute

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Current mood: "Joining a new company is akin to an organ transplant - and you're the new organ. If you're not thoughtful in adapting to the new situation, you could end up being attacked by the organizational immune system and rejected."

Learning fast, exploring the culture, and pushing myself to bring out the best work I’ve ever done. 

Loving the challenge. 🤩

As a leader, your job is to run a tight ship.

That doesn’t mean control. It means precision.

Clear goals. 
Clear roles. 
Clear standards.

In fast-moving teams, especially in AI, ambiguity is expensive and confusion kills momentum.  Alignment compounds it.

Gemini 3 is here and it isn’t just another model release. It’s Google firing on every AI cylinder: infra, research, product, and distribution.

A few things stand out:

1.	Full-stack advantage, finally realized.
Gemini 3 is the first model shipped into Google Search on day one. That’s not just marketing ; it’s how you put frontier AI in front of billions.

2.	The agent era is no longer theoretical.
With Deep Think mode, long context, multimodal understanding, and real-time planning, Gemini 3 moves beyond chat. It’s not a chatbot. It’s a problem-solver.

3.	AI is getting better at “reading the room.”
It reflects a core shift: models are starting to grasp intent and nuance and not just data.

Benchmarks back it up: topping LMArena, solving “Humanity’s Last Exam”, setting a new bar in math and science tasks. But that’s the sideshow.

More info here: https://lnkd.in/gWeXGwhC

I cannot wait to try it out

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Talks about #ai, #nocode, #deeplearning, #machinelearning, and #artificialintelligence

building AI systems

𝗔𝗜 𝗪𝗼𝗿𝗹𝗱 𝗠𝗼𝗱𝗲𝗹𝘀 𝟭𝟬𝟭

Current AI is often described as a "statistical correlation machine." It predicts the next word or pixel based on patterns it has seen before. World Models represent a shift toward causal understanding—giving machines a way to simulate the future.

What is a World Model? Think of it as an internal flight simulator. Instead of just recognizing an environment, the AI builds a mental model of how that environment works. It uses this model to test hypotheses ("If I drop this glass, it will break") without needing to actually perform the action.

The "𝗟𝗮𝘂𝗻𝗱𝗿𝘆" Example Imagine training a robot to fold clothes.

- 𝗪𝗶𝘁𝗵𝗼𝘂𝘁 𝗮 𝗪𝗼𝗿𝗹𝗱 𝗠𝗼𝗱𝗲𝗹: The robot must physically interact with the clothes millions of times, learning through endless trial and error.

- 𝗪𝗶𝘁𝗵 𝗮 𝗪𝗼𝗿𝗹𝗱 𝗠𝗼𝗱𝗲𝗹: The robot simulates the physics of the fabric in its head. It plans the fold internally, predicts the outcome, and only moves its arm when it is confident. This results in safer, faster, and more generalizable learning.

𝗛𝗼𝘄 𝘁𝗵𝗶𝘀 𝗱𝗶𝗳𝗳𝗲𝗿𝘀 𝗳𝗿𝗼𝗺 𝗰𝘂𝗿𝗿𝗲𝗻𝘁 𝗟𝗟𝗠𝘀: While Large Language Models (LLMs) are masters of syntax and semantics, they often struggle with physical causality. World Models differ because:

𝟭. 𝗧𝗵𝗲𝘆 𝘀𝗶𝗺𝘂𝗹𝗮𝘁𝗲, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗿𝗲𝗰𝗮𝗹𝗹: They don't just retrieve information; they run mental experiments.

𝟮. 𝗧𝗵𝗲𝘆 𝗹𝗲𝗮𝗿𝗻 𝗹𝗮𝘄𝘀, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗿𝘂𝗹𝗲𝘀: They infer the physics of their environment from data rather than being hand-coded.

𝟯. 𝗧𝗵𝗲𝘆 𝗮𝗿𝗲 𝗽𝗿𝗼𝗮𝗰𝘁𝗶𝘃𝗲: They predict "what happens next" in a state-space, not just a token-space.

𝗧𝗵𝗲 𝗥𝗼𝗮𝗱𝗺𝗮𝗽: The next frontier is the convergence of these technologies. By combining the reasoning of LLMs with the grounding of World Models, we move closer to Embodied Intelligence—software that can read, watch, plan, and act in the physical world.

Scaling laws in AI are nowhere near finished. The latest Gemini 3 results show it clearly.

Pre-training: Many believed progress had plateaued. Yet the jump from 2.5 to 3.0 is one of the biggest leaps we have seen. When you improve data, architecture, and compute together, you keep breaking ceilings. No walls in sight.

Post-training: This might be the real frontier. We are still early in how we align, steer, and specialize models. The innovation curve here is just beginning, and the gains on 3.0 prove it.

Good insights from Deepmind engineers this week.

Better models are not coming slowly. They are coming faster.

Plan for continuous capability jumps, not incremental upgrades. The disruption curve is steepening.

it is very cool to work everyday with people in person. i think  product innovation and magic really happens with real human interaction

AI is making 10X engineers 1000X, and 1X engineers 0.1X 

stealing this quote from Shadi Copty 🙃

Fortusight, Founder | AI advisor | Ex-Dir of Llama @Meta & Ex-VP of Watson @IBM

AI Evals Explainer

Generated with Nano Banana Pro

It’s insane how many hours I’ve seen senior technical leaders burn on architecture charts. 

All that time spent polishing pixels... now you just describe it in plain English and boom and nano banana AI handles the rest.

By the way, this is a solid, modern and agile AI stack. To build at x10 speed you need to have the right building blocks.

Fortusight's AI stack

A lot of people ask me this question, I'll start with the absolute core:
1. I use Agno for multi-agent framework, they're fast, elegant and robust.
2. Exa for web grounding, I consider Exa a bigger booster than LLM choice for my use case.
3. FMP for premium, clean, reliable financial data turned into tailored tools.

For LLMs, I use O3 for multi-agent orchestration and planning, GPT 4.1 for digesting web content and supporting my A1Facts flow; Flash2.5 for structured extraction and Gemini 3 pro for synthesizing investment thesis.

I constantly progress the choices of LLMs prioritizing quality over price.

For tools, I use Cursor with Opus 4.5 (recently replacing Gemini 2.5 pro); and Figma make - which I absolutely love.

For internal ops agents, (1) managing coverage requests (2) digesting user feedback (3) analyzing product analytics (4) writing my weekly newsletter -- all built with Agno and Gemini 3 pro.

Less exciting but just as critical :-) Streamlit for front end [being replaced with react], and Firebase for database/auth/analytics -- both choices have been really critical for prototyping rapidly with my users.

The "secret sauce" is secret (lol), but I will say solving factuality in evolving market dynamics is a significant effort, and using expert-system techniques and simulations augments LLMs where they are critically weak.

Happy to share more if you have any questions -- and obviously here's the link if you want to try it out (https://lnkd.in/g7eR86dr)

Introducing SAM 3D: Powerful 3D Reconstruction for Physical World Images

and it’s not your typical 3D reconstruction tool.

It does what previous models couldn’t:
- Reconstruct real-world objects and scenes from a single image.
- Handle occlusion, indirect views, and cluttered backgrounds.
- Estimate human pose and shape with surprising accuracy.

Why does this matter?
Because for the first time, we’re seeing 3D perception at the scale, quality, and accessibility of today’s 2D models.

The architecture behind SAM 3D borrows from LLMs: pre-training on synthetic data, followed by post-training on real-world images using a human-in-the-loop ranking engine. The result is a feedback loop that continuously improves both the data and the model.

The implications stretch far beyond creative media. Robotics. E-commerce. Sports medicine. Interactive avatars. You name it.

And the best part? 

It's fast. 
Real-time fast.

Meta’s already using SAM 3D to power a “View in Room” feature in Facebook Marketplace; turning static listings into immersive experiences.

The gap between virtual and physical is shrinking. SAM 3D is a serious leap forward.

Learn more:
- 𝗥𝗲𝗮𝗱 𝘁𝗵𝗲 𝗮𝗻𝗻𝗼𝘂𝗻𝗰𝗲𝗺𝗲𝗻𝘁 𝗯𝗹𝗼𝗴: https://lnkd.in/g8w6dvAB
- 𝗥𝗲𝗮𝗱 𝘁𝗵𝗲 𝗦𝗔𝗠 𝟯𝗗 𝗢𝗯𝗷𝗲𝗰𝘁𝘀 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗣𝗮𝗽𝗲𝗿: https://lnkd.in/gd_HQE9c
- 𝗥𝗲𝗮𝗱 𝘁𝗵𝗲 𝗦𝗔𝗠 𝟯𝗗 𝗕𝗼𝗱𝘆 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗣𝗮𝗽𝗲𝗿: https://lnkd.in/gp3p9jaf
- 𝗗𝗼𝘄𝗻𝗹𝗼𝗮𝗱 𝗦𝗔𝗠 𝟯𝗗 𝗢𝗯𝗷𝗲𝗰𝘁𝘀: https://lnkd.in/gfwmcKGK
- 𝗗𝗼𝘄𝗻𝗹𝗼𝗮𝗱 𝗦𝗔𝗠 𝟯𝗗 𝗕𝗼𝗱𝘆: https://lnkd.in/g9CPHEXJ
- 𝗘𝘅𝗽𝗹𝗼𝗿𝗲 𝘁𝗵𝗲 𝗣𝗹𝗮𝘆𝗴𝗿𝗼𝘂𝗻𝗱: https://lnkd.in/guSDTnU3

A sharp, modern AI tech stack for building a serious startup.

Fortusight from Shadi Copty lays out a blueprint that actually reflects where the industry is going:

multi-agent architectures, real-time grounding, premium data, and a diversified LLM strategy tuned to specific jobs rather than brand loyalty.

1/ Agno for agent frameworks.
2/ Exa for grounding.
3/  FMP for clean financial data.
4/ A portfolio of models (O3, GPT-4.1, Flash2.5, Gemini 3) each picked for its superpower.

Cursor + Opus 4.5, Figma Make, Firebase, and Streamlit/React for fast product loops.

And a layer of expert systems + simulation to fix factuality where LLMs keep failing.

This is the kind of stack that lets a small team punch far above its weight.

🚀

Open article: Financial Analysis App by fortusight.streamlit.app

Exciting project for you all to check! I tried an earlier prototype and it was very impressive

Startup life, here I come :-)

Thrilled to share with you my new adventure, Fortusight - a project I've labored on nights and weekends for the last 2 years.

It's a tool for the serious investor that wants to deeply understand a company before buying and holding for 5-10 years.

It uses AI Agents to read through filings, earning calls, analyst reports, news, press-releases - forms an opinion on a company's competitive position, management's friendliness to shareholders, and creates bull/base/bear scenarios for valuation.

To quote a friendly hedge fund manager "I used to have 5 people doing all of this" - each company is analyzed for 192 different perspectives, with A1Facts to ensure factuality for high stakes decisions.

Here's how you try it: https://lnkd.in/g7eR86dr

Let's go 🚀 🚀 🚀

🚨 Stop scrolling. The math on this is barely real.

Get a $799/mo institutional AI research platform for just $50/mo.

The catch: Only 10 spots open. 

RIAs & Fund Managers—this is a complete no-brainer. 👇

https://fortusight.ai/

I need your help 🙏

I'm looking for design partners for my baby startup that just got pre-seed funded.

If you know a wealth fund manager, a small RIA, a family office that wants to reduce their equity research costs from ~$75K to less than what they pay for starbucks coffee - share this link with them: https://fortusight.ai  

For 10 design partners, I'm giving away Fortusight for $50/month instead of $800/month for a year in exchange for feedback to help guide the product's development.

The beta with our users has been incredibly successful, with recurring usage of our equity deep dives.

This will propel the company forward, and one day I will find ways to repay your kindness - many thanks ❤️

Colberta

Boutique consultancy delivering strategic business analysis and digital transformation expertise to enterprise clients.

Achieved 25% operational cost reduction by leading digital transformation for Saveera International across 3 countries, implementing cloud-based systems and streamlining end-to-end business processes.

Accelerated delivery and reduced rework by facilitating cross-functional stakeholder workshops, translating business needs into system specifications, and aligning requirements through wireframes and visual process flows.

Ensured 100% system adoption and post-go-live stability by coordinating testing, rollout, and performance monitoring across finance, sales, operations, and logistics units.

Scope: 3-country rollout | 3 stakeholder groups | Agile delivery | Tools: Jira, Mrio, FIgma,

Lead Business Analyst, Product Owner 

ERP Gold

Led product strategy and remote Agile development for a multi-module SaaS ERP, scaling core operations and integrations across CRM, finance, and partner platforms.

Drove 15% revenue growth and 25% customer retention uplift by delivering high-impact product enhancements aligned with market and user research.

Boosted team velocity by 30% by managing a fully remote cross-functional team (7 developers & QA) across 3 time zones and optimizing Agile ceremonies via Jira.

Improved system stability by 20% and reduced bug resolution time by 40% through data-driven performance monitoring and QA process refinement.

Delivered 4+ enterprise-grade implementations on time and within budget by standardizing deployment workflows, application integration, and coordinating across sales, training, and engineering.

Scope: 7-person remote team | $100k+ annual revenue impact | 1k+ users | Tools: Jira, Confluence, Figma, Google Analytics, Microsoft Teams | Agile Scrum,

Product Manager

Acqurex

Founded and scaled a custom development consultancy, driving strategic client acquisition, operational efficiency, and product innovation for enterprise clients.

Increased profit margins by 40% by establishing an offshore development model, scaling teams by 70% while maintaining product quality through standardized delivery processes.

Reduced development time by 35% by adopting modular design principles and reusable components, resulting in 100% client satisfaction and zero cancellations.

Enhanced product scalability by implementing a discovery-first methodology, enabling phased delivery and aligning future functionality with business priorities.

Scope: 7-person team | 5+ enterprise clients | Tools: Jira, Git, Slack, Trello | Agile, Waterfall, Hybrid

Emirates Group

Drove digital transformation and operational efficiency within dnata Cargo and other Emirates Group departments, delivering cost-saving solutions and process optimizations.

Achieved AED 1M annual savings by leading the transformation of dnata Cargo (DACS) to a mobile platform, optimizing workflows and reducing manual efforts, cutting turnaround times at DAFZA.

Managed end-to-end product delivery in JIRA, defining 75+ user stories and acceptance criteria, and ensuring functional and non-functional requirements alignment with engineering teams for seamless execution.

Streamlined operations by eliciting and defining business requirements for Import Cargo Delivery and build-up/break-down functions through workshops, interviews, and process analysis, resulting in more efficient processes.

Revamped processes, eliminating redundancies and securing senior management buy-in for mobility features and cross-departmental process implementations.

Scope: 15-person team | AED 1M savings impact | 4+ departments impacted | Tools: Jira, Confluence | Agile, Java, Android platform

Product Owner - dnata Cargo

Optimized ramp operations by driving digital solutions that scaled operations, improved task management, and enhanced logistics efficiency across the airport.

Streamlined 42 ramp operations processes through the development and deployment of an in-house application (AACS), managing 1600 flights, 600 drivers, and 16,000 daily jobs, reducing operational complexity and enhancing task efficiency.

Reduced operational bottlenecks in baggage and cargo handling by designing and implementing a logistics planning solution, improving task allocation and ramp resource utilization.

Collaborated with system analysis and engineering teams to implement task generation and execution improvements, increasing real-time process efficiency and operational throughput.

Achieved measurable gains in job planning efficiency and resource allocation, ensuring smoother, more reliable cargo operations and a reduction in delays.

Scope: 1600 flights/day | 600 drivers | 16,000 daily jobs | Tools: AACS, Jira |  Agile methodologies

Product Owner - dnata Airport Operations

Streamlined regulatory and maintenance workflows, delivering measurable gains in efficiency, compliance, and asset management.

Digitized AD/SB approval process in Ultramain, eliminating manual email-based workflows and providing full audit visibility, improving compliance tracking and operational speed.

Reduced parts cannibalization by 30% through the implementation of a Robbery Management Workflow, enhancing asset tracking and improving resource utilization in Line Maintenance.

Led the development and delivery of a centralized engineering order system by defining business specifications, ensuring alignment with aviation compliance standards, and improving operational efficiency.

Scope: AD/SB approvals | Parts management | Line Maintenance | Tools: Ultramain | Agile methodologies

Business Analyst - Emirates Engineering

Pakistan International Airlines

Led the modernization of legacy mainframe systems through integrated ERP and MRO solutions, driving significant operational efficiencies and unlocking PKR 50M+ in cost savings.

Spearheaded cross-functional transformation across 7+ departments, conducting business analysis, gap assessments, and value stream mapping, reducing inefficiencies by 30% and identifying 40+ process improvement opportunities.

Achieved PKR 50M in cost savings and improved procurement efficiency by 25% through redesigning workflows, optimizing inventory management, and aligning SOPs with aviation compliance standards.

Secured executive buy-in by presenting strategic roadmaps and ROI-driven business cases, leading to a 90%+ user acceptance rate for system adoption.

Mentored a team of 15 IT professionals, leading solution architecture, change management, and system rollout with minimal disruption.

Skills: ERP Implementation | Business Process Re-engineering | Change Management | Project Management | Vendor Management | Waterfall Methodology | Requirements Analysis | Vendor Contracts

Manager (ERP Solution)

Siemens

Delivered technical excellence as a certified SAP ABAP Developer, creating custom solutions that enhanced enterprise operations and reduced manual effort.

Designed and implemented ABAP-based solutions for clients, including Pakistan Petroleum Ltd., Indus Motors, and AGPR, reducing manual data processing time by 35%.

Developed and deployed comprehensive technical documentation and business blueprints, achieved a 99.8% defect-free implementation rate.

Led SAP ABAP Academy training sessions, mentoring 5+ junior developers, and enhancing in-house technical capabilities to support long-term project success.

SAP ABAP Developer

Driving Enterprise Transformation through Leadership & Technical Excellence

Senior IT Business Analyst & Product Owner with 12+ years of experience leading high-impact digital transformation initiatives for major organizations, including Emirates Airline, dnata, Emirates Transguard, Siemens, and Pakistan International Airlines. Proven track record of managing multimillion-dollar budgets ($5M+), driving business cost reductions of 15%+, and aligning 50+ stakeholders to deliver mission-critical results.

Core Expertise:

Digital Transformation Leadership: Led enterprise-wide initiatives, enhancing operational efficiency, cost savings, and customer experience.

Stakeholder & Team Leadership: Expert at navigating complex stakeholder ecosystems, including C-suite executives and technical teams, to align on business priorities and drive consensus.

Agile & Process Optimization: Transitioned teams from Waterfall to Agile, improving delivery velocity and reducing delays by 30%.

Business Analysis & Requirements Engineering: Skilled in BRDs, FRDs, process mapping, gap analysis, and solution validation.

Product Ownership: End-to-end ownership from backlog management to sprint planning and roadmap development, ensuring high-priority features deliver measurable outcomes.

Technical Tools & Methodologies: Proficient in JIRA, Confluence, Visio, FIGMA, MIRO, SAP ERP, Power BI, SQL, and familiar with AI/ML tools for business optimization.

Agile & ITIL Methodologies: Expertise in Scrum, Kanban, and BABOK frameworks for delivering high-impact solutions in complex environments.

Emerging Technology Focus:
Currently exploring AI/ML, Generative AI, and AI-augmented business analysis tools to drive innovation and business outcomes.

Passionate about leveraging emerging technologies to drive business transformation. Let’s connect to explore how we can collaborate on impactful, ROI-driven solutions.

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