George Firican

The University of British Columbia

Director, Data Governance & Business Intelligence

Led a team of wonderful and highly skilled people in the areas of:
- Finance
- Human Resources
- Information Systems
- Gift Processing 
- Operations
- Strategic Projects
- Prospect Research & Analytics 
- Data Governance & Business Intelligence 

To support the goals of the fundraising and alumni engagement portfolio across the university.

Chief Advancement Operations Officer (Interim)

Director of Information Technology (Interim)

• Lead the Data Governance/ Quality program and the strategy development of Development and Alumni Engagement’s (DAE) data acquisition, maintenance and dissemination while fostering innovation and long term strategic vision
• Lead the efforts to develop a business glossary as well as a business intelligence (BI) framework and program that provides user-friendly access to the right information for the right people at the right time
• Directed the development and enhancement of standards, procedures, processes, policies related to the improvement and/or maintenance of quality of data within the Blackbaud Enterprise CRM database
• Created and fostered strategic partnerships and influential relationships with DAE senior management, the broader UBC community, campus stakeholders, vendors, and external universities to secure the success of DAE’s data governance, business intelligence and information quality efforts
• Collaborated with Information Technology to manage the development of automated data validations, data cleanses, data quality issue reports, and deployment of new tools and enhancements to aid in the preservation of data quality
• Advanced the data governance and business intelligence profession by participating in professional organizations, acquiring or maintaining required accreditations, publishing articles, and giving presentations at professional events

Associate Director, Data Governance & Business Intelligence

I proudly took part of UBC's "Start an Evolution" campaign (https://startanevolution.ubc.ca/), campaign which raised $1.5 billion dollars for students, research and community engagement and to double the number of alumni involved annually in the life of the university by 2015.

• Established and led an award winning Data Governance/Quality Program to support the university’s $1.5 billion fundraising campaign and sustainable alumni engagement strategy
• Provided oversight of the Data Governance/Quality Program and kept it on track by managing the development of standards, procedures, processes, policies related to the acquisition, management, and dissemination of enterprise data impacting the Blackbaud Enterprise CRM database while leading the Advisory Council
• Developed an award winning Tracing Program through which the returned mail percentage of Development and Alumni Engagement’s Portfolio has been reduced to less than 1%
• Managed the development of business performance metrics and scorecards to monitor and communicate the status and improvement of service of the Records department
• Achieved a 92% address and phone number accuracy for Canadian records, an improvement from ~64%
• Communicated to and educated internal and external stakeholders on the results and initiatives of data governance, quality, master data management, information delivery and advised stakeholders about best practices; was the first and only department to achieve 100% on the annual client satisfaction survey on communication delivery and content

Data Quality Manager

LightsOnData

- Educational Content Creation: Develop and deliver comprehensive courses, workshops, and webinars on data governance, data management, data quality, AI, and more.
- Brand Amplification: Collaborate with data companies to enhance their brand visibility and thought leadership in the data community.
- Engagement and Outreach: Host the Lights On Data Show podcast, featuring industry leaders and experts to share their insights and experiences.

Founder

Pearson

Course Instructor

O'Reilly

iData Quality Academy

Developed course content for iData Quality Academy
- Data Profiling
- Data Quality Costs

Instructor

Self employed

• Provided project management and business analysis expertise to various projects across the different industries (BaniPePost.com, JT Business Group, SMAWS, 8p8, Ashenzi, NetPress Consulting, LTS, AHACommunity, etc).
• Designed and developed unique, highly professional web and print designs, branding and e-learning solutions as well as developing and configuring custom websites (e-stores, online communities, content management systems, blogs, brochure websites, etc.).
• Accumulated experience as a web master by installing, upgrading, performing backups, managing migrations and maintaining a series of complex websites.

Freelance Consultant

Sauder School of Business, UBC

• Served as internal Project Manager for the evaluation, build and deployment phases of a custom-built, scalable web payment gateway (WPG) that complied with the PCI standard requirements and reduced Sauder Finance’s operational time for the allocation and reporting of revenue received via card payments by 75%
• Managed the deployment of a FIPPA compliant e-newsletter tool (Industry Mailout) selected to achieve a standard for design and operational support while reducing expenses by $15k/year
• Planned and managed the development and release of a new service for personal/academic blogging through the use of the WordPress MU environment for faculty members and current Sauder students
• Managed the development of an improved content publishing process to account for 15 digital signs, each with audience specific content & emergency broadcasting capabilities
• Served as the internal project manager for the development and deployment of the Canaccord Learning Commons web presence comprised of a WordPress based website and a BuddyPress student interaction environment
• Developed solutions for integrating the business environment with web 2.0 technologies such as WordPress 3 based sites, online communities (Ning, Moodle), and collaboration tools (MediaWiki, Project Spaces, CoMapping) while providing expertise and system support for these platforms
• Identified customer requirements, analyzed and reviewed product features, integration, security, scalability and performance requirements for projects such as PPM Tool, a collaboration tool to be used between the Center of Health Care Management and BC health care authorities, Desktop Blogging Client Solution, ECM Society Online Presence, Faculty Master Calendar, Form Building Tool, Event Registration, PCI Payment Forms Conversions, and several online presences for different business areas and conferences

Project Manager / BA

Everest iTech

• Promoted to Project Manager for the Showtime Models website and web application and the All Ears accounting software development project due to excellent interpersonal, communication and leadership skills in the relationships with the client and internal development team
• Led the development of several e-commerce sites (ex: SkyHook Solar, Expressive Designs Florist, JT-Autotech) and dynamic websites (ex: Mailinglist System, Informant Zone) and also helped architect their databases
• Increased the employees' knowledgebase by developing e-learning modules and user manuals for the use of the company’s payroll and accounting software
• Enhanced the online awareness of the company’s brand by 40% by creating a new content strategy and redeveloping its website in a WordPress, SEO friendly environment
• Minimized the cost of online advertising by developing free distributed widgets that increased incoming traffic by 5k visitors/ month

Project Manager / Lead Web Developer

Event Technologies

• Developed customer support standards and procedures for the company’s e-store business and helped transition a staff of 12 to this new environment through training sessions and a knowledgebase wiki.
• Minimized the installation time of new systems by 80% by creating and managing standard desktop images based on the employees’ job roles.
• Reduced search time of hardware and software information by 50% by developing a standard for filing all the technical documentation on hardware equipment and software.

IT Consultant

WGOA

• Demonstrated strong leadership skills by acting as the team leader of a software developer group in order to successfully implement and deliver an interactive Go learning application two weeks ahead of deadline and within budget.
• Coded the backend interaction of a merchandise inventory application with a barcode scanner and also contributed to developing the MySQL database and reporting. 
• Facilitated the team members to work remotely by implementing a VPN solution and integrated the use of Subversion to enable software versioning and revision control.

Software developer

💬 Founder of LightsOnData.com and LightsOnData YouTube Channel
Focused on providing informative content such as ONLINE COURSES, templates, guides, best practices, articles, white papers, and other useful resources to help you with your data governance and data management questions and challenges

💬 Creator of online courses that are engaging, new, and thorough. 
Courses: Building an Award-Winning Business Glossary, Data Governance Maturity Models, Data Governance Fundamentals, etc. - check them out here: https://www.lightsondata.com/courses/

💬 Providing LinkedIn content strategy for data-focused companies and products, as well as those with a focus on artificial intelligence (AI), business intelligence (BI, data science, data management, and data governance areas.
Connect with me today and ask how I can help you reach the data audience.

💬 Host of Lights on Data Show - a podcast and LinkedIn Live weekly show that provides insights into the data world and showcases people that help to shape it.

💬 Get some fun data merchandise here: https://shop.spreadshirt.com/lightsondata/all

💬 International key note speaker, conference speaker, and panelist (spoken at over 60 different conferences).

💬 I love being on camera, hiking, surfing, filming, and video editing
YouTube: @LightsOnData


🏛 My experience and specialties: 
• Expertise in data governance, information quality, business intelligence & data management
• Extensive background in web and application development with experience of the full life-cycle of a project
• Strong leadership capabilities, organizational and communication skills

Specialties: 
• Enterprise information management: Information quality, data governance and stewardship, master data management, business intelligence, business process improvement
• Development: Web and application development, relational database design and development
• Planning: Budget and resource planning, agile and waterfall project management, team development and leadership
• Tools and Applications: Collibra, Tableau, MS Visio, MS Project, Premiere, Photoshop

George Firican 💡

I’m at Collibra’s Data Citizens event and really enjoying the conversations and energy. The message is clear: 

Organizations need to move from BI-ready to AI-ready data, and governance has to evolve with it.

Here’s why:
✅ AI is increasing ecosystem complexity
✅ Structured and unstructured data both need visibility and trust
✅ Governance must scale everywhere across platforms, engines and workloads

So here are some available features to help with above that got me excited:

1️⃣ Data contracts for improving consistency and transparency across data products
2️⃣ Custom rules with Text2SQL to turn natural language into precise SQL data quality checks
3️⃣ Derived relations to visualize multi-hop connections and lineage
4️⃣ Semantic Model Generation Agent to automatically generate semantic layers from physical data
5️⃣ Model Context Protocol server to give copilots and AI agents real-time governed context
6️⃣ Data recommender to guide teams toward trusted, approved data
7️⃣ AI model registry for governed model lifecycle tracking
8️⃣ Automated AI traceability across Azure AI Foundry
9️⃣ Microsoft Teams & Slack integrations for better data collaboration 

A lot of impressive innovation on display today. Interviews with Collibra leaders and partners coming soon.

Until next time, let’s keep putting the Lights On Data!
-George Firican  

#data #AI #datagovernance

💡 Award Winning Data Governance Leader | Content Creator & Influencer | Founder of LightsOnData | Podcast Host: Lights On Data Show | LinkedIn Top Voice

Navigating data challenges be like…

That’s why I recommend following these people here:

Learn Data Analytics here: Avery Smith  
Learn AI here: Christina Stathopoulos, MSc and Steve Nouri  and T. Scott Clendaniel  
Learn GenAI here: Doug Sheley  
Learn Data Engineering here: Andreas Kretz and Pooja Jain  
Learn Cybersecurity and Risk Management here: Mary Carmichael  
Learn Privacy, Risk and Compliance here: Thaïs Ramos
Learn Statistics here: Joshua Starmer PhD 
Learn Excel here: Matt Brattin  
Learn Tableau here: Donabel Santos  
Learn Data Visualization here: Kate Strachnyi  
Learn Data Literacy here: Jordan Morrow  
Learn Data Storytelling here: Brent Dykes and  Mico Yuk  
Learn How to Tell Your Data Story here: SCOTT TAYLOR
Learn Data Classification here: Susan Walsh  
Learn Digital Transformation here:⚡Achille Ettorre, MBA  
Learn Data Community Building here: Scott Stafford  
Learn Data Analytics Career Upskilling: Albert Bellamy  
Learn Business Intelligence here: Alex Freberg  
Learn Apache Iceberg here: Andrew Madson
Learn Data Management here: LightsOnData  
Learn Data Strategy here: Vin Vashishta  
Learn Data Freelancing here: Benjamin Rogojan 
Learn Data Contracts here: 🎯 Mark Freeman II  

Who else am I missing?

(Post inspired from Avery Smith)

#data #AI #datascience

It was a pleasure delivering my presentation on “Data Governance in the Age of AI” at The University of British Columbia’s Symposium 2025.

Great sessions, networking and knowledge sharing all around. 

Thank you again to the PrISM team for the invite and for putting together the month-long series of events to celebrate Cybersecurity Awareness Month.

Let’s keep putting the Lights On Data, Privacy, and Security!

—
Special thanks to Trevor Carpenter, Larry Carson, Zoe Armer and everyone involved behind the scenes to make this happen.

Thank you also to all the wonderful speakers and presenters such as Scott Baker, Maliheh Oliver, Salman Shahid, Dr. Gail Murphy, Mark Montgomery, Gráinne McElroy, Gurm Dhugga, Mawuena G., Waii Chow, Julie Le Hegarat, PhD, Tim Szigeti  and many others.

#data #privacy #AI

What if “data governance” wasn’t a checklist, but a way to ADVANCE your organization?
Here’s the 7-pillar framework I use to make it simple 👇

A – Accountability: Assign clear owners so decisions actually get made
D – Definitions: Create a shared language through glossaries and standards
V – Value Alignment: Tie every governance effort to business goals
A – Adaptability: Use governance as your engine for change
N – Necessity: Start where the value is highest and scale from there
C – Collaboration: Build cross-functional trust and shared goals
E – Education: Empower people to see governance as an enabler

If you could only strengthen one pillar right now, which one would move your organization forward the fastest?

And if you want to go deeper, my Practical Data Governance: Implementation course walks through how to apply each one (includes templates and examples): 
https://lnkd.in/gwBcYQg5

Let’s keep putting the Lights On Data.
-George Firican

#data #datagovernance #datastrategy

7 pillars of data governance

Great energy, amazing sessions, wonderful networking here at the Big Data & Analytics West Summit.

It was a pleasure catching up with the local data community, seeing old friends, and meeting new ones.

Let’s keep putting the Lights On Data!
-George Firican  

#data #ai

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There was a clear theme emerging at the Big Data and Analytics West Summit, and it showed up in the breakfast discussions, the keynote, presentations and every conversation. 👇

Reliable AI still comes down to one thing: the strength of your enterprise data foundation.

At the IBM breakfast, several roundtable discussions pointed to the same realization. As teams accelerate toward AI, the real bottleneck isn’t tooling. It is the clarity, quality, and accessibility of the data behind it.

Paul Zikopoulos, VP Technology Sales at IBM, reinforced this in his keynote. He talked about the curiosity tax that comes from gated or fragmented data, and how governance, lineage, sovereignty, and explainability aren’t administrative tasks. They are accelerators for AI.
When organizations know where data came from, how it can be used, and who owns it, the entire AI lifecycle becomes more reliable.

One point he shared stood out to me: GenAI is fundamentally an unstructured data problem. Most organizations haven’t even started unlocking the value in documents, PDFs, forms, logs, images, and everything that never makes it into a warehouse.

During my conversation with Paul, he also highlighted how leaders can start simply. Focus on automation and internal optimization use cases. Decide whether each AI initiative is meant to save money or generate money. Build from there.

Across the day, the message was consistent throughout peer discussions, panels, and other presentations. Data foundations are the reason AI works and we need to invest in getting those right. Governance, security, quality, stewardship and so much more... they all need to be in place.

How's your data foundation?

#ibmpartner #IBMCanada #data #AI

Key takeaways from Big Data Analytics West Summit

Did you know that AWS announced 60 AI Competency Partners across 3 NEW categories that will define the next era of intelligent systems:

✅ Agentic AI Applications
✅ Agentic AI Tools
✅ Agentic AI Consulting Services

These organizations represent innovation, scale and real world impact.
They are building autonomous systems, enabling smarter workflows, and helping enterprises activate their AI strategy with confidence and speed.

Do you have a favourite category or partner you are most excited about?

I will add the full list of partners in the comments so you can explore their work, follow their updates and connect with leaders who are shaping the future. 

You can also read more about all this here: https://lnkd.in/g-g7T22Z

Until next time, let’s keep putting the Lights On Data and Agentic AI.
-George Firican

#AI #agenticAI #partnerpost

Here is my recommendation for this week.
If Agentic AI is on your roadmap, checkout this ebook  👇

It breaks down what many overlook: AI success depends on the maturity of your data architecture.
Here's what else you can find in it:
• Clear explanation of what a modern, AI-ready architecture looks like
• Practical guidance on data quality, cataloging, lineage and governance
• A real example of how a bank scaled agentic AI by modernizing its foundation

So if you are leading data initiatives or planning for AI adoption, this is a good resource to read.

Until next time, let's keep putting the Lights on Data!
-George 
#data #AI #partnerpost

Modernize Data Architectures for  Agentic AI Success

What are your thoughts on AI generated videos or art?
Here’s a good example, in my opinion, on what happens when human creativity and AI-powered implementation come together.

Credit: Le Voyage (Paint World 28)


#ai #artificialintelligence

Data quality starts at the source… kind of  like good coffee.

I visited a shop that roasted its own beans, and the difference was undeniable. Fresh, intentional, crafted with care.

When we source data with the same level of attention, everything that comes after becomes smoother. Analytics flow better, insights become richer, decisions become clearer.

What do you think?
Happy weekend everyone! Let’s keep putting the Lights On Data!
-George Firican 

#data #dataquality

What do you think? Is AI making Master Data Management and Data Governance obsolete... or more essential than ever?

I’m looking forward to sitting down with Bruno Billy, President of APGAR North America, and Ken Brown, Head of Customer Success, to explore how AI is reshaping MDM and Data Governance, plus...

...how these disciplines influence the success of AI itself.

From practical examples of AI-augmented governance to rethinking stewardship roles and making MDM truly AI-ready, we will unpack how leading organizations are using AI to strengthen their data foundations, not replace them.

WHEN: Dec 11 at 8 AM PT | 11 AM ET | 4 PM GMT
WHERE: Here on LinkedIn and LightsOnData YouTube channel

More details in the comments.

#datagovernance #AI #MDM

how is AI reinventing MDM and data governance

Tomorrow I’ll be at the Big Data & Analytics West Summit, and there’s something I’m genuinely looking forward to:

I love conversations that bring clarity to where data and AI are headed next, and IBM is putting a spotlight on a topic I care deeply about:
 👉 How organizations can build reliable AI by strengthening their enterprise data foundation.

A major highlight for me will be hearing Paul Zikopoulos share practical lessons and thoughtful perspectives on:
✅ Preparing enterprise data for agentic AI applications
✅ Combining retrieval approaches to improve AI reliability
✅ Real-world strategies for scaling trusted AI across teams 

Paul consistently brings insights that elevate how we think about data and AI, and I’m excited to learn from his session.

These are the kinds of insights I’m excited to learn from, explore, and share.
And of course the discussions, networking, and the exhibitor lounge where there’s always something new to discover.

You can explore the agenda here: https://lnkd.in/gkDXmrnq

If you’re attending #BDW2025, please let me know as I’d be happy to connect.
You’ll find me capturing moments throughout the day, and yes, I’ll also be hanging out at IBM’s booth as their #ibmpartner for the event.

#data #IBMCanada

IBM Big Data Analytics West George Firican

Oh wow, what a day!
Excited to have been part of the Big Data Analytics West Summit in Vancouver as an #ibmpartner for the event.

Grateful for the energizing discussions and sessions, especially the great session on preparing enterprise data for AI from Paul Zikopoulos (VP, IBM Technology Sales).

It was great catching up with fellow data professionals and having a day of learning.
Thank you again IBM! 

#AI #IBMCanada #data

What are the biggest misconceptions business leaders still have about AI?

I sat down with Stijn (Stan) Christiaens, Co-founder of Collibra, at Data Citizens to unpack what AI readiness really means for organizations. 

Here are 5 takeaways from our chat:

1. Many leaders still see AI as “a chat in the cloud.”
2. Organizations need the right foundations around AI
3. AI ready data requires more than quality
4. Unstructured data is no longer optional
5. Unified governance is becoming essential

If you want a clear picture of what it truly takes to prepare your organization for AI, this interview delivers.
Full conversation in the video below.

Until next time, let’s keep putting the Lights On Data.
-George Firican

#data #datagovernance #AI

I took a photo of my latte this morning.
A simple image…
Completely unstructured, yet full of information if you know how to look at it.

Here is the interesting part…
Unstructured data is everywhere in our organizations:
- Images
- Screenshots
- Videos
- PDFs
- Logs
- Messages

All of them packed with value
But without metadata, that value stays hidden.

Metadata tells us:
- Who created the content
- When it was captured
- What it represents
- How it should be used
- Where it fits in our ecosystem

Suddenly an image is not just an image.
It becomes
- Searchable
- Discoverable
- Reliable

This is why unstructured data is such a huge opportunity.
The insights are already there.
Metadata is what turns those insights into something we can trust and act on.

Curious to hear from you:
Where do you see the biggest metadata gaps today?
- Search
- Ownership
- Retention
- Context
- Priority
Or something else entirely

Let’s keep putting the Lights On Data and its Metadata!
-George Firican 

#data #metadata #dataquality

Why are we still managing data on week-long cycles while our AI expects answers every second? 
As a data management professional, that mismatch is the bottleneck I see most often. That is why I’m paying attention to Acceldata’s Agentic Data Management.

Here’s what stood out to me after watching some of their demos:
✅ Natural language use to diagnose data quality issue AND trigger the proper fixes
✅ Autonomous agents that observe, reason, and act across your data pipelines, lineage & policies
✅ Dynamic and context aware governance that interprets regulations and applies controls to the right data
✅ A reasoning layer (xLake Architecture) that turns metadata into business meaning
✅ Learns from incidents so issues don’t repeat

If you are exploring how to make data AI ready, this is worth a look. Start here and tell me what you think of the agent driven workflow:
https://lnkd.in/gVwUQQwy

Question for you: where do you lose more time today:
1. Detection or 
2. Resolution?

Let’s keep putting the Lights On Data!

#datamanagement #AI #partner

Every December I look ahead… and this year, one prediction feels very safe:

I'll be attending Subsurface Live on December 10, coffee in hand, curious about how Agentic AI and open lakehouse patterns will shape 2026.

The agenda lines up well with questions many of us are exploring right now:
➡️ How will agent-based execution reshape data workflows?
➡️ What signals are emerging around performance, formats and multi-cloud patterns?
➡️ Where is the Apache Iceberg ecosystem pushing innovation next?

For anyone designing data systems or planning next-year priorities, this feels like a valuable moment to absorb ideas and future direction.

Registration is free: https://lnkd.in/gmDPiaES
Where: Virtual
Date: Dec 10, 2025 
Time: 8AM - 2PM PT / 4PM - 10PM GMT / 5PM - 11PM CET

See you there!

#data #AI

As organizations deploy AI, how should master data management and data governance programs evolve, or be reinvented, to stay relevant?

Join George Firican and Bruno Billy, President of APGAR North America, and Ken Brown, Head of Customer Success as they will explore how MDM and Data Governance are being redefined for a world shaped by machine learning, generative models, and data products.  
Drawing on APGAR’s experience helping organizations define, build, and run their enterprise data programs, Bruno and Ken will share how AI is transforming the purpose and practice of master data management and data governance.
Tune in to hear how leading organizations are using AI to strengthen their MDM and Data Governance foundations. And why these disciplines could be even more important than before.

#datagovernance #AI #MDM

How Is AI reinventing MDM and Data Governance?

Greg Coquillo

Product Leader @AWS | Startup Investor | 2X Linkedin Top Voice for AI, Data Science, Tech, and Innovation | Quantum Computing & Web 3.0 | I build software that scales AI/ML Network infrastructure

Product leader with a passion for solving business use cases such as Growth, Go-to-Market, and Price Optimization. I owned P&L for commodity-based products, and leveraged AI to increase the average customer contract values across business industries. As a Product Leader at Amazon, I own a roadmap that drives the adoption of AI products through the Media Automation charter, which supports Private Brands’ YOY growth. I work with Data Scientists, Software Engineers and Business Intelligence Engineers to leverage Machine Learning and Big Data Analytics to design predictive models that enhance business decision-making and performance to accelerate growth, reduce Time to Market of products, monitor cross-geo compliance and import requirements, and ensure customer safety.

I am always curious and eager to learn how new technology affects our daily lives, and I love to support communities on their quest to adopt Artificial Intelligence across industries. Feel free to contact me if you have Data Science projects that you’d like to be showcased on this platform for visibility.

🌐I am a Global Business Leader with 12 years of experience and skills including Product Management, P&L management, Global Networking, EBITDA Optimization, Pricing Management, Margin Management, Product Management, Program Management, Operations and Supply Chain Management, Lean Manufacturing, Six Sigma, and Continuous Improvement.

🧘🏽‍♂️Soft Skills include: Communication, Collaboration, Lateral Thinking, Adaptability, Inspiration, Innovation, Empathy, Listening, Diplomacy, Organization, Responsibility, Leadership...

🎬🎥🎞 I really enjoy watching movies, and if I could redo it all over, I’d be a Sci-Fi script writer so I can be bounded by the limits of imagination.

(Opinions are my own)

Product Management, Media Automation

Owner of the AI vision and roadmap for Private Brand’s Compliance Division. Driving adoption of new technology, allowing my customers to scale their processes and increase productivity. Core responsibilities include:

-Building cross-functional teams consisting of Data Scientists, Software Engineers, Data Engineers, Product Managers and Program Managers, to plan and implement sophisticated AI projects
-Manage the New Initiative Intake Process
-Gather Business requirement artifacts
-Communicate roadmap definition and prioritization
-Coordinate User Acceptance Testing
-Manage Launch Announcements
-Prepare and communicate annual planning artifacts

Building Agentic AI systems beyond connecting APIs or LLMs is complicated, but not impossible.

This architecture lays the foundation for how AI agents think, communicate, and improve, covering everything from testing and observability to deployment and memory management.

Here’s a breakdown of the key layers and components that make up a scalable Agentic AI Architecture :

1.🔸Decomposition
Break down complex systems by domain (e.g., Coding Agent, Data Agent), by cognitive capability (Reasoning, Planning, Execution), or by agent role (Planner, Executor, Memory Manager, Communicator).

2.🔸Communication
Enable message passing between agents using inter-agent protocols or A2A (Agent-to-Agent) orchestration.
Support both single-agent and multi-agent setups for small or distributed workflows.

3.🔸Deployment
Deploy agents in containerized or serverless environments using Docker or Modal.
Support orchestrators like CrewAI or AutoGen for collective intelligence in multi-agent workflows.

4.🔸Data & Discovery
Integrate knowledge bases (like vector databases for RAG), memory stores (FAISS, Redis, Pinecone), and APIs for dynamic data access.
Context is passed using Model Context Protocol (MCP) for structured and real-time reasoning.

5.🔸Testing & Observability
Validate workflows end-to-end, test reasoning logic, and evaluate performance under real conditions.
Monitor using Weights & Biases, LangFuse, and track metrics like latency and task success rate.

6.🔸UI & Style
Provide intuitive feedback loops through visualization layers, dashboards, and self-reflective modes.
Enable collaborative, proactive, and goal-driven reasoning among multiple agents.

7.🔸Security
Protect access with token-based authorization and data encryption.
Include Trust Layers for human-in-the-loop validation and Policy Enforcement for safe execution.

8.🔸Cross-Cutting Concerns
Handle configuration, secrets, and environment management.
Support flexible frameworks like LangChain, AutoGen, or CrewAI for runtime execution and modular design.

Agentic AI is the future of automation - where AI doesn’t just assist but collaborates and learns.

Save this post to understand the architecture that powers the next generation of AI systems

#AgenticAI

AI agents are great at working alone. However, they can also be effective when operating within networks of collaboration.

The real power of AI lies in how these agents communicate, coordinate, and complement each other’s abilities.

Orchestration patterns define this collaboration which turns isolated agents into intelligent, goal-driven systems capable of solving complex tasks together.

Here are 6 orchestration patterns that power the next generation of AI systems :

1.🔸Sequential Orchestration
Agents work one after another - each passing its result to the next.
Perfect for structured, step-by-step tasks like data pipelines or analysis chains.

2.🔸Concurrent Orchestration
Multiple agents work in parallel, handling different parts of a problem simultaneously.
This boosts speed, scalability, and overall task efficiency.

3.🔸Group Chat Orchestration
Agents communicate in a shared conversation, refining ideas together.
Useful for brainstorming, collaborative decision-making, or generating consensus.

4.🔸Maker–Checker Loops
One agent creates or proposes; another verifies, corrects, or approves.
Ideal for maintaining accuracy, compliance, and quality assurance in workflows.

5.🔸Handoff Orchestration
Agents transfer control dynamically based on context or expertise.
Best suited for adaptive workflows like support systems or multi-step automation.

6.🔸Magnet Orchestration
A central “manager” agent dynamically assigns tasks to the right specialists.
Enables fluid, context-aware collaboration across multiple intelligent agents.

AI Agents are evolving fast and orchestration is what makes them powerful.

Learning how these patterns can help you build smarter, more collaborative AI systems can be a huge advantage.

#AIAgent

AI Agent Orchestration Patterns

📚LLMs in the Enterprise are finally getting the playbook they deserve… LLMs in Enterprise by Ahmed Menshawy and Mahmoud Fahmy provides practical guides for building real AI systems that operate at scale.

Most teams talk about LLMs in theory. This book focuses on execution. It bridges foundational concepts with the hands-on design patterns that matter when you are integrating models into production environments.

Here are the insights that stood out👇

1.🔸Enterprise LLM integration is a data architecture problem
The book breaks down how to design pipelines, tune retrieval, and structure data so models operate with consistency and low latency in real workloads.

2.🔸Scaling LLMs requires pattern-level thinking
They go deep on architectural patterns that reduce complexity, improve efficiency, and streamline deployment. This includes RAG frameworks, fine-tuning strategies, segmentation techniques, and evaluation patterns that teams often overlook.

3.🔸Performance is not just about bigger models
The authors show how to optimize model behavior with advanced inferencing engines, contextual model customization, and monitoring systems that keep applications predictable.

4.🔸Real enterprise value comes from operational rigor
Security, fairness, transparency, and accountability are not afterthoughts. They are part of the design process, especially when LLMs touch business workflows and customer data.

5.🔸AI teams win by mastering both concepts and impact
The flow of the book reflects the real enterprise lifecycle: Concept → Customization → Impact
A clear, structured way to think about turning LLM capabilities into business outcomes.

If you are building production AI systems, leading an LLM program, or preparing for the next wave of enterprise adoption, you should definitely get a copy of this book.

Enterprise AI is evolving fast. Understanding these design patterns early puts at a career advantage which allows you to shape the next generation of intelligent applications.

#LLM

Check out this simple breakdown of the four core LLM architectures shaping most of today’s advanced systems.

Not all LLMs reason the same way. Building reliable AI systems, or choosing the right model for a workflow requires a clear mental model of the architectures that drive them.

Let’s review:

1.🔸Decoder Only (GPT, LLaMA, Grok)
Generates text by predicting one token at a time using previous context.

Best for generative workloads, conversational systems, and multi step reasoning.

2.🔸Encoder Only (BERT, RoBERTa)
Processes text with full bidirectional context to learn dense semantic representations.

Best for classification tasks, retrieval, and embedding generation.

3.🔸Encoder Decoder (T5, FLAN T5, BART)
Separates understanding from generation. The encoder builds meaning, the decoder transforms it.

Best for translation, summarization, and any structured text to text transformation.

4.🔸Mixture of Experts (Mixtral, Gemini 1.5)
Routes each input to a subset of specialized expert networks.

Best for scaling model capacity while controlling compute cost.

These architectures go beyond academic details to determine latency profiles, context handling, fine tuning strategies, and how models behave under real workloads. A clear grasp of them helps you design better pipelines, choose the right foundation models, and understand why two LLMs can produce very different outcomes on the same task.

Let me know your thoughts!

#LLM

I believe the next wave of AI systems will not be defined by bigger models but by smarter orchestration. Salman Paracha got my attention on Arch Router, which introduces a routing approach that aligns model selection with human preferences instead of benchmark scores. You should absolutely check it out, as I know machine alignment is one of the most talked about challenges at enterprise. 

Arch Router treats routing as a semantic matching problem between a user query and a set of natural language policies built from a Domain and Action taxonomy. This design gives teams direct control over how queries should be handled and removes the need to retrain routers whenever new models are added. 

The authors trained a compact 1.5B model that outperforms top proprietary models in multi-turn routing while running at a fraction of their latency. The result is a practical blueprint for multi-model systems that are fast, interpretable, and aligned with real usage rather than synthetic metrics.  

Let me know your thoughts on this one. 

Salman and I will be sharing more on the subject.

#LLM

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The Battle

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}George Firican 💡's LinkedIn Performance

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