Aishwarya Srinivasan

AI@Fireworks AI | Global Speaker(100+ talks)| EB1-A Recipient| 570k+ Followers| AI Engineer| GenAI/LLM Inference| LinkedIn Top Voice| Author-What's Your Worth?| Startup AI Advisor| Angel Investor| Ex-Google,Microsoft,IBM

𝗙𝗼𝗿 𝗽𝗮𝗿𝘁𝗻𝗲𝗿𝘀𝗵𝗶𝗽 𝗶𝗻𝗾𝘂𝗶𝗿𝗶𝗲𝘀, 𝗰𝗼𝗻𝘁𝗮𝗰𝘁 𝗺𝘆 𝘁𝗲𝗮𝗺 𝗮𝘁 💌 partnerships@illuminate-ai.org

I write about:
- AI engineering
- Applied machine learning
- Generative AI Applications
- LLM/ LLMOPs (Training, post-training, inferencing)
- Fundamentals of Data science/ ML/ AI
- ML roles interview tips
- Learning roadmaps (beginner to advanced)
- Importance of personal branding for career growth

**All the posts reflect my own views and do not represent my employer.**

AI Advisor || Responsible AI Advocate || LinkedIn Top Voice - Data & AI  || Top 10 AI Influencer || EB1-A Receipt


Bio: 
Aishwarya currently leads the Developer Relations - Growth at Fireworks AI. She was previously at Microsoft for Startups as a Senior AI Advisor to help Y Combinator startups build machine learning solutions, leveraging core Microsoft/ OpenAI products. Prior to this, Aishwarya was working as a Data Scientist in Google Cloud and before that an AI & ML Innovation Leader at IBM Data & AI, where she was working cross-functionally with the product team, data science team and sales to research AI use-cases for clients by conducting discovery workshops and building assets to showcase the business value of the technology. She holds a post-graduate in Data Science from Columbia University. 

Aishwarya has been awarded Trailblazer of the Year by Women in AI in 2022 and Women of Influence by Business Journal in 2022. She was awarded EB1A - extraordinary ability visa for her contributions in the AI field.

She is an advocate for open-source technologies, and was an open source Developer Advocate for Deepchecks and Lightning AI, and a contributor to Scikit Learn. 


She holds a Patent Award (2018) for developing a Reinforcement Learning model for Machine Trading.

She has over 500,000+ follower base on LinkedIn and actively organizes events and conferences to inspire budding data scientists. She has been spotlighted as a LinkedIn Top Voice 2020 for Data Science and AI, which features Top 10 Machine Learning influencers across the world. 

She is an ardent reader and has contributed to the scholastic community. To spread her knowledge in the space of data science, and to inspire budding Data Scientists, she actively writes blogs related to machine learning on LinkedIn and Instagram: www.instagram.com/the.datascience.gal

Besides being a data junkie, she is a fitness fanatic who is into martial arts (Krav Maga) and yoga.

Senior AI Advisor

If you're feeling overwhelmed with how fast AI is evolving, you're not alone.

Every day there’s a new paper, a new framework, a new agent loop, and it’s easy to feel like you’re falling behind.

But the good news is that you don’t need to learn everything all at once. What you need is structure.

So I put together a 10-level AI Agents Learning Roadmap that takes you from foundations to production, layering your learning in a way that’s actually doable.

💡My recommendation: spend 2–3 weeks on each level. Learn the concepts, implement small projects, and build your intuition.

If you're moving faster or slower based on time or experience, that’s okay too.
And when something new drops? That can be your Level 11. Don’t let “newness” derail your plan. Just start here.

👇 Here’s the roadmap:
🔖 Level 1: GenAI & Transformer Foundations
 Tokens, embeddings, transformers, decoding, and inference with open-weight models.

🔖 Level 2: Prompting & Language Model Behavior
 Prompt types (CoT, ReAct, ToT), decoding strategies, context design, and adversarial prompting.

🔖 Level 3: Retrieval-Augmented Generation (RAG)
 Chunking, embeddings, vector DBs, RAG pipelines, and RAG evaluation.

🔖 Level 4: LLMOps & Tools
 LangChain, LangGraph, Dust, CrewAI, tool use, function calling, and synthetic data.

🔖 Level 5: Agents & Agent Frameworks
 Agent types, memory, planning, LangChain agents, LangGraph loops, and evaluation.

🔖 Level 6: Memory, State & Orchestration
 Vector and symbolic memory, episodic vs persistent state, memory compression.

🔖 Level 7: Multi-Agent Systems
 Hub-and-spoke vs decentralized, message passing, collaborative agents, agent teams.

🔖 Level 8: Evaluation & Reinforcement Learning
 LLM-as-a-Judge, RLHF, RLVR, reward modeling, and self-correcting loops.

🔖 Level 9: Protocols & Safety
 MCP, A2A, safety alignment, guardrails, traceability, and autonomous policy updates.

🔖 Level 10: Build & Deploy
 FastAPI, Streamlit, GGUF, QLoRA, caching, monitoring with LangSmith, Arize, Trulens.

📌 Bookmark this.
🛠️ Build something after every level.

And if you're wondering what tools to explore along the way → Start with Hugging Face (to explore LLMs and SLMs), you can use Ollama (to run SLMs on your laptop, like Phi-4, TinyLlama), or Fireworks AI (to run LLMs via endpoint, like Qwen 3, Kimi K2, DeepSeek R1), then explore LangChain & LangGraph (these two tools will  teach you a lot), then you can move into learning Agentic frameworks like CrewAI, AutoGen. 

💻 Pro-tip: Start with cookbooks!

〰️〰️〰️
Follow me (Aishwarya Srinivasan) for more AI insight and subscribe to my Substack to find more in-depth blogs and weekly updates in AI: https://lnkd.in/dpBNr6Jg

Hundreds of AI minds gathered in Central Park on a chilly Saturday morning, it was incredible :)

The past weekend in New York felt like one of those moments where community completely surprises you in the best way.

I was traveling to the city for a work event, and my friend Pranjal and I had a thought- What if we host a small AI meetup on Saturday morning in Central Park? Nothing fancy, just a space for people to connect.

So we put up a quick Luma link and shared it on LinkedIn. We expected maybe a handful of people. Instead, the sign ups crossed 450+. 

We put a small table with coffee, muffins, cookies and some cool swag- thanks to Teachable. We weren’t sure how it would go. We just hoped people would show up.

What happened next honestly moved me.

We reached the park at 9.20am to set up for a 10am meetup, and people were already there. In the cold. On a Saturday morning. People had traveled from Boston, Maryland, upstate New York, New Jersey, even Philadelphia. I kept talking to folks thinking, you really came all this way… for this?

The meetup was meant to last two hours. People stayed until 3pm! Almost six hours of conversations about AI, careers, ideas, and everything in between. No microphones. No agenda. Just humans connecting because they care about the same things.

This experience reminded me of something I tend to forget- community doesn’t need perfect planning. It needs intention. It needs genuine people. And it needs a space where everyone feels welcome.

I’m grateful to every single person who showed up. You made this morning unforgettable, and you reminded me why I love building in this space.

Shout-out to Aditya Suresh and Pranam Daga for helping us with putting this together ❤️

There is a quiet moment every November when life slows down just enough for reflection. I never grew up celebrating Thanksgiving. Back home in India, I didn’t even know what it meant. But after moving to the US, watching my friends celebrate, watching sitcoms where families gathered around food and gratitude, I started understanding the deeper meaning behind it.

A moment to pause.
A moment to look around.
A moment to look back.

This year, gratitude feels a little different for me. A little heavier in the best possible way.

I feel grateful for a life where I get to wake up every day and do work I genuinely love. AI is chaotic and intense and fast. Yet it gives me energy. It gives me purpose. And I feel lucky to be part of this ecosystem during a time when everything is shifting.

I feel grateful for the people who hold me steady.
A mom who pushed me when the world expected her to play it safe. A mom who defied every norm to carve space for me to choose ambition without apology.

A husband who is involved in my life in the most beautiful way supportive is honestly an understatement. He is a true partner in every single thing I do. He listens to every idea, every frustration, every new plan I dream up and he backs me with a kind of belief that strengthens my own. Chinnu amma and Chinnu appa who patiently listen to my ten year entrepreneurial plans and cheer for me with the kind of warmth only family can give.

Mentors and colleagues who let me thrive creatively who challenge me in the right ways who make every room I walk into feel lighter and more possible.

I feel grateful for health. For a body I get to take care of. For the time I carve out to move, to eat well, to nurture myself. It took years to realize that taking care of your body is also taking care of your dreams.

And I feel grateful for the little girl I used to be the one who sat with a notebook and wrote her goals on every page the one who kept believing she would get there someday. If I could talk to her today, I would tell her that she is doing great and that her stubborn belief in herself was worth it.

Thanksgiving may not be something I grew up with, but it has become a reminder to pause and appreciate the rarest gift of all the good people around you. People who are genuinely supportive, genuinely positive, and genuinely rooting for you.

I am grateful for all of it.
And grateful for everyone who has been part of my journey so far.

If you are reading this, I hope you take a moment to celebrate the smallest wins, the unexpected joys, and the people who make your life feel expansive.

li_at

JSESSIONID

What an electrifying afternoon! Absolutely delighted to have joined the Mayfield AI List honorary lunch at the beautiful Golden Gate Club in San Francisco.

The room was filled with the brightest minds in the AI VC world. it was a privilege to meet and listen to inspiring leaders like Navin Chaddha, Aparna Chennapragada and Garry Tan. 

I had the opportunity to host a focused roundtable, diving deep into the current state of the industry. We tackled the crucial discussion around Perception vs. Reality of AI, analyzing current hype cycles, and zeroing in on investment opportunities that hold real long-term potential.

It’s moments and small-group settings like these, where leaders can candidly discuss where the real value lies beyond the buzz, that drive the industry forward.

Huge thanks to the Mayfield and Startup Grind team (special shoutout to James Gee and Fadia Frangie Doumat) for hosting and for the award ♥️

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Wrapped up AI Dev 25 hosted by DeepLearning.AI

More than 1400 AI developers gathered in one space, and the energy was something you could feel instantly. Meeting so many builders and hearing what you’re creating reminded me why this community moves the needle the way it does.

Hearing Andrew Ng talk about the future of work was a standout moment. The way he encourages everyone on his team to code, regardless of background, is exactly the kind of mindset shift this era needs. AI literacy is becoming a baseline skill, and he articulated that perfectly.

Our panel with Michael Kearns, Hatice Ozen, Kay Zhu, and Josh Gordon covered how the ecosystem is evolving across the stack, from Groq , Google, and Amazon Web Services (AWS)  to Fireworks AI and how teams like Genspark are using RFT on Fireworks AI in production workflows. We also touched on multi-agent systems, practical best practices, and where developer tooling still needs to mature.

I also loved my conversation with Michael Kearns on responsible AI and how that thinking has evolved from classic ML days to the generative era. His perspective at the intersection of academia and industry always leaves me thinking differently.

Grateful for the conversations and connections today. If we met, thank you for stopping by. If we didn’t, I’m always happy to keep the discussion going. There’s a lot to build, and we’re still early.

Thank you DeepLearning.AI team for having me ❤️

When you’re an AI engineer, the worst bottleneck isn’t writing code. It’s navigating everything around the code.

Last week I tried out Rovo Dev from Atlassian and it really changed how I approach dev work, plus how I see AI agents changing the landscape of software engineering.

𝗪𝗵𝗮𝘁 𝗶𝘀 𝗥𝗼𝘃𝗼 𝗗𝗲𝘃?
RovoDev is an AI agent built to live inside your dev workflow, including your code, your issues (let’s say in Jira), your docs (let’s say in Confluence), your pull requests. 

It helps you move from idea → code → deployment with fewer context switches.

𝗛𝗲𝗿𝗲’𝘀 𝘄𝗵𝗮𝘁 𝗜 𝗻𝗼𝘁𝗶𝗰𝗲𝗱 𝗮𝗳𝘁𝗲𝗿 𝘂𝘀𝗶𝗻𝗴 𝗶𝘁:
→ I asked in plain English: “What does this module do? Where are its dependencies?” and got a clear breakdown, no digging through 3 dozen files.
→ I linked my GitHub/Bitbucket + Jira and was able to surface relevant issues, test failures and comments in one context instead of switching tools.
→ The CLI experience (yes, in my terminal) allowed me to trigger agents to draft tests, summarise PRs, or suggest refactoring ideas, without leaving my code. 

𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀?
What I realized after using Rovo Dev is that the real time-sink in engineering isn’t writing code, it’s in fact more about re-orienting yourself.

Jumping between Jira, Confluence, and your repo just to understand context.
Trying to figure out why something was built the way it was.
And then losing your train of thought before you can even start solving the problem.

Well, that's where Rovo Dev actually helps close that gap.

If you’ve ever joined a new project and spent hours just piecing together what’s going on, or if you constantly find yourself switching between tools to get one small thing done, you should try this out: fandf.co/42MTjr8 

Thank you Atlassian for partnering with me on this post, and giving me access to Rovo Dev to test it out :)

#AtlassianPartner

This is one of the best resources for aspiring AI engineers, that covers all the basics - advanced in classroom teaching: https://lnkd.in/dgr5zEve

Highly recommend saving this so you can come back to it later.

Goldmine for aspiring AI Engineers

Lately, I’ve noticed something interesting in the AI startup world.

The ones growing the fastest aren’t building the next big model.

They’re building agentic systems.
AI that doesn’t just talk, it does.
Copilots that summarize meetings.

Agents that predict churn or handle internal ops automatically.

These aren’t demos anymore. They’re real products driving revenue.

What separates the ones that scale from the ones that stall comes down to one thing : Data.
Every great agent lives and dies by how it manages memory, retrieval, and reasoning speed.
And that’s exactly why so many founders I work with build on MongoDB Atlas.

It’s not just a database.
It’s the data layer that brings structured, unstructured, and vector data together so your AI can actually reason in real time.

If you’re a startup building AI that acts, not just talks, go check out the MongoDB Startup Program: https://fandf.co/493VsD1

#MongoDBPartner

🚨Context Engineering for GenAI Workshop happening tomorrow!

In this session, we’ll dive deep into:
→ What context really means in LLMs and how it shapes performance

→ The toolkit that helps you engineer it better: Summarization, Pruning, Query Rewrite, RAG, Context Offloading, Isolation, and Memory

→ How to optimize for accuracy, cost, and reliability across use cases

→ A live demo showing how these ideas come together in real time

This workshop is for every engineer who wants to move beyond prompt tuning and start thinking like a system designer.

🧩 Context Engineering
📅 November 8
🕐 1.5 hours
🎙️ with Arvind Narayanamurthy & me

🎟️ Save your spot: https://lnkd.in/dvFmMiRr

If you’re an AI engineer today, you should absolutely get familiar with Model Context Protocol (MCP) and Responses API. These two are becoming the backbone of modern agentic systems.

Let’s unpack why 👇

1️⃣ MCP: The Connector Layer

Model Context Protocol (MCP) standardizes how models connect to external tools, APIs, and live data.

Think of MCP as the wiring system that allows your LLM to talk to the outside world, like tools, databases, vector stores, or your company APIs.

When you build or host your own MCP server, you’re giving your model new abilities to reason, act, and fetch context beyond what’s in its prompt.
This is what turns a plain LLM into an agent.

If you’re working on production-grade AI systems, you’ll often need to:
→ Integrate custom tools or data sources
→ Maintain context across multiple steps
→ Ensure reliable tool invocation and streaming

MCP makes all that possible.

2️⃣ Fireworks AI Responses API

Once your MCP setup is ready, the Responses API is how you connect it to the model.

It’s a next-generation SDK that powers conversational AI. It supports:
→ Stateful conversations (previous_response_id)
→ Real-time streaming for interactive apps
→ Tool calling and safe execution

The Fireworks Responses API follows the same schema and format as OpenAI’s Responses endpoint.

So if you’ve been using OpenAI models, you can switch to open-source models on Fireworks AI with almost zero code change.

You’ll unlock faster inference, lower latency, and broader model choice, including open models like Qwen, Mistral, Llama, and Gemma hosted natively on Fireworks AI.

You can even mix and match:
✅ Use MCP to extend model capabilities
✅ Use Responses API to orchestrate reasoning, tool use, and streaming

That’s the magic combo powering many of today’s most advanced agentic systems.

3️⃣ Why This Matters

Agentic systems aren’t built with just a model call.
They’re built with context, memory, and actions. MCP and the Responses API make that orchestration reliable, stateful, and production-ready.

If you’re serious about building enterprise-grade AI apps, start experimenting with:
→ MCP Examples (connecting to MCP servers and invoking tools)
→ Conversation Chaining (using previous_response_id to continue dialogue)
→ Streaming Output (for responsive real-time interfaces)
→ Ephemeral Mode (for privacy-friendly, non-persistent interactions)

Happy Building 🚀
〰️〰️〰️
Follow me (Aishwarya Srinivasan) for more AI insight and subscribe to my Substack to find more in-depth blogs and weekly updates in AI: https://lnkd.in/dpBNr6Jg

If you’re an AI engineer or an AI leader looking to level up your skills in LangChain and LangGraph, this one is for you.

I’m teaming up with Arvind Narayanamurthy  for a beginner–intermediate, 1.5 hour hands-on workshop where you’ll learn how to move from simple prompts to real AI applications and agentic workflows.

Why this matters
- Most engineers know how to prompt. Few know how to orchestrate.
- LangChain and LangGraph are becoming the backbone of production AI systems.
- If you want to build or lead AI engineering teams, you need these mental models.

What you’ll learn
- Foundations of LLM orchestration and where LangChain fits
- Essential building blocks: chat models, prompting patterns, structured outputs, LCEL
- Tool calling with MCP adapters
- RAG basics end to end
- LangGraph workflows and agentic architectures
- Two live labs: a micro-app and a simple agent
- Quick dive into LangSmith for debugging

The workshop is recorded, and everyone gets the replay.

If you want practical, real-world skills to build modern AI systems, this is the one to sign up for.

Grab your seats: https://lnkd.in/eW2WZdcf

Are you wondering where the AI industry is actually headed? 
Every week brings a new framework, a new toolkit, a new acronym. But beneath all the noise, one truth is becoming clearer: the real moat isn’t the model, it’s the combination of data and AI. 
 
AI is the toolkit. 
Data is the substance. 
AI gives us reasoning power. 
Data gives us understanding. 

That connection came to life at Snowflake BUILD 2025, where the  focus wasn’t on hype, it was on grounding AI in reality. 
 
We saw how Snowflake Intelligence lets teams ask complex questions in natural language and get trusted answers from governed data. How the Cortex Agents API enables developers to build domain-specific agents that reason and collaborate. And how the Managed MCP Server securely bridges external AI systems to enterprise data, turning “agentic AI” from an idea into something production-ready. 
 
Even unstructured data, the 80 % of information hidden in PDFs, chats, and documents, is now first-class and accessible through simple AISQL queries. 
 
This feels like a turning point. 
The next era of AI won’t be defined by bigger models, but by deeper integration between data and reasoning. 
 
AI without data is just potential. 
Data without AI is just storage. 
Together, they become intelligence. 
 
#SnowflakePartner #SnowflakeBUILD

If you’re an AI engineer trying to understand agentic systems, keep reading 👇

A single-agent system relies on one model to do everything: reasoning, planning, execution, and validation. It’s efficient for simple, sequential tasks but quickly breaks down as workflows grow more complex or interdependent.

A multi-agent system, on the other hand, distributes intelligence across specialized agents that collaborate. Each has its own role, memory, & context - and together, they solve problems that a single model can’t handle alone.

But here’s what most people miss: there’s no standard architecture.

A multi-agent system is like Lego blocks, you design it for your use case.

You can build:
→ a supervisor agent managing sub-agents
→ a hierarchical setup with layered control
→ or a hybrid model combining centralized planning and peer coordination
The challenge isn’t in building agents, it's in managing how they talk to each other.

Three reasons multi-agent systems often fail:

❌Memory fragments across agents.
Each agent keeps its own context. When one agent hands work to another, subtle details get lost or duplicated. Without a shared memory layer or context synchronization, agents start “forgetting” what the others already know.

❌Operational costs multiply.
What costs $0.10 for a single agent might cost $1 when ten agents coordinate. Every message, validation step, or context handoff adds latency, token cost, and complexity. At scale, coordination overhead often outweighs the benefit of specialization.

❌ Write conflicts cascade.
If multiple agents write to the same source of truth: a shared database, knowledge base, or document, their changes can collide. One agent updates a schema, another updates logic on top of the old version, and suddenly the system’s state fragments.

TL;DR: Not every workflow needs a multi-agent setup.

When tasks are independent, read-heavy, and parallelizable, multi-agent systems shine. But for sequential logic and tight dependencies, a single-agent pipeline is still faster, cheaper, and easier to maintain.

As always, Galileo has published a new phenomenal free handbook- Mastering Multi-Agent Systems.
 
If you want to go deeper into how these systems work, why they fail, how to evaluate them, explore different architectures, and even build LLMOps around them, this is one of the best reads out there: https://lnkd.in/diptdEC2

#GalileoPartner

Multi-Agent AI System Cheatsheet 

I learned Design Thinking on my first day as a data scientist at IBM, and it quietly became one of the most useful mindsets in my AI career. It taught me to slow down, understand the real problem, and build solutions that actually land with users.

Here’s how I still use it today:

→ Solve the right problem
Most AI teams jump into modeling too early. Design Thinking forces you to reframe, question assumptions, and check if the problem is even defined correctly.  

→ Diverge before you converge
Explore many possibilities, then narrow down. This prevents tunnel vision and leads to better architectures, better experiments, and better product decisions

→ Use the 2x2 grid
Am I exploring or deciding?
Am I thinking about the problem or the solution?
This simple check saves me from going down the wrong path.  

→ Observe behavior, not opinions
The real insights come from watching users, not asking them. The same applies when evaluating agents, prototypes, or internal tools.  

→ Prototype fast, assign ownership
Ideas die when nobody owns them. Execution is where Design Thinking turns into impact.  

This mindset shaped how I build AI systems then, and it still shapes how I build them now.

♻️Share this with your network

Design Thinking Framework

Last week I came home to a little surprise from OpenAI filled with their new books, 100 Chats for Studying, Career, and College Life. 

I flipped through them right away and loved how visual and genuinely interesting they’ve made each section. It feels approachable, practical, and fun in a way most tech books don’t even try for.

If you want to explore the prompts yourself, you can check them out at this link: https://lnkd.in/ddycaDAg

It’s a pretty cool resource to keep on your desk as you build, study, or just experiment with new ideas.

Here is my absolute fav one which I wish I could have used as a student 👇  
I want to understand [concept]. Explain it with an analogy to real-world items.

Let me know in the comments below which ones is your favorite?

If you’re getting started as an AI engineer, this one’s for you 👇

Here are 12 things you need to learn if you want to become a real AI engineer (or level up as one):

1️⃣ LoRA & qLoRA fine-tuning
Learn low-rank adaptation to fine-tune massive models while keeping GPU and memory usage in check.
https://lnkd.in/dxAfNJjP
https://lnkd.in/dcfhk4YB

2️⃣ Reinforcement Learning from Human Feedback (RLHF)
Understand how to align model behavior with human expectations using curated reward signals.
https://lnkd.in/da4qf5JV
https://lnkd.in/drEbQ4x2

3️⃣ Reinforcement Learning from Verifiable Rewards (RLVR)
Use simulated or programmatic reward models when human feedback is too expensive.
https://lnkd.in/dFBgDAyd

4️⃣ RAG Fundamentals
Learn how to build Retrieval-Augmented Generation systems- ingest documents, create embeddings, stitch context, and prompt LLMs.
https://lnkd.in/dFkgD6RQ
https://lnkd.in/d7v6DzEG

5️⃣ Advanced RAG Architectures
Master multi-hop retrieval, hybrid sparse-dense search, and complex reranking for multi-document use cases.
https://lnkd.in/dUrAz2D3

6️⃣ Embedding Models & Vector Databases
Benchmark sentence encoders, tune indexes (FAISS/Pinecone), and understand latency vs recall trade-offs.
https://lnkd.in/d8zeWbmn
https://learn.pinecone.io/

7️⃣ Prompt Engineering & Chain-of-Thought
Design prompts that guide reasoning step-by-step, manage templates, and dynamically inject context.
https://lnkd.in/djbJD578
https://lnkd.in/d9M75H_i

8️⃣ MCP & Agent-to-Agent Integration
Use Model Context Protocol (MCP) to coordinate LLMs with APIs and other agents for seamless A2A handoffs.
https://lnkd.in/dfjvxhvP
https://lnkd.in/dJ5NWuaK

9️⃣ Long-Context Window Strategies
Handle 100k+ token sequences using smart chunking, hierarchical retrieval, and memory-augmented architectures.
https://lnkd.in/djgkXGaZ

🔟 Model Efficiency: Quantization & Distillation
Shrink models with post-training quantization (4/8-bit), pruning, and knowledge distillation for faster, cheaper inference.
https://lnkd.in/d2iurEyv

1️⃣1️⃣ LLMOps & Model Monitoring
Build CI/CD pipelines for LLM deployment, track drift, monitor hallucinations, and set up alerting for cost or performance issues.
https://lnkd.in/dxik45e6

1️⃣2️⃣ Evaluation & Benchmarking
Measure with perplexity, ROUGE, F1, and human evaluations. Automate benchmarks to compare models at scale.
https://lnkd.in/dP_NJXg9

〰️〰️〰️〰️
♻️ Share this with your network 
🔔 Follow me (Aishwarya Srinivasan) for data & AI insights, and subscribe to my Substack to find more in-depth blogs and weekly updates in AI: https://lnkd.in/dpBNr6Jg

If you’re getting started with building AI agents, this Agentic AI Toolkit Cheatsheet will come in handy 👇

You’ll quickly realize it’s not just about choosing a model. You need orchestration, memory, retrieval, evaluation, and a solid deployment stack.

And if you’re not careful, your architecture turns into a mess of disconnected tools.

That’s why I put together this Agentic AI Toolkit Cheatsheet.

It organizes the full stack of what goes into building production-grade AI agents- from model hosting to feedback loops, so you can stop guessing what’s missing in your pipeline and start shipping actual systems.

Here’s what it covers:

🔧 Foundation Models & Hosting
🎛️ Model Customization (SFT, RFT, RLHF)
🤖 Agent Frameworks
🧩 Orchestration & Workflow
📥 Data Ingestion & Preprocessing
🧠 Embedding & Retrieval
🧷 Memory & Knowledge Storage
🔌 Tool Integration
🧪 Evaluation & Monitoring
🖥️ User Interfaces
🚀 Deployment & Hosting


💡 A few tips if you’re working on your first agentic stack:

→ Choose one tool per layer to start, depth over breadth.
→ Build iteratively and introduce evaluation as early as possible.
→ Use event-driven workflows to manage complexity.
→ Think about memory and feedback as first-class components, not afterthoughts.


📌 Bookmark this.
📚 Use it to audit your stack.
🛠️ Build with it.
📤 Share it with a teammate who’s lost in the sea of GenAI tooling.

〰️〰️〰️
Follow me (Aishwarya Srinivasan) for more AI insight and subscribe to my Substack to find more in-depth blogs and weekly updates in AI: https://lnkd.in/dpBNr6Jg

This Week of AI is here⚡️
Another packed week in the world of AI- here’s your quick TL;DR of everything that happened across the AI ecosystem this week 👇

- Apple Forges Billion-Dollar AI Alliance with Google for Siri Overhaul
- Anthropic Foils First Documented Large-Scale Autonomous AI Cyberattack
- World Labs Unveils Marble, A Multimodal World Model for Spatial Intelligence
- OpenAI Rolls Out GPT-5.1 with Adaptive Reasoning and Dual Personalities
- Microsoft Creates MAI Superintelligence Team Led by Mustafa Suleyman
- Google Launches ‘Agentic Checkout’ and AI Shopping Tools for Holiday Season
- IBM Joins OpenSearch Software Foundation as Premier Member

♻️ Share this with your network
🔔 Follow me (Aishwarya Srinivasan) for no BS data and AI updates and insights

This week, the AI landscape was defined by blockbuster partnerships, a major infrastructure upgrade, and a chilling preview of autonomous cyber warfar

Open article: This Week in AI: Week of 16th November 2025 by Aishwarya Srinivasan • 3 min read

This Week in AI: Week of 16th November 2025

Thanksgiving week, yet a lot happening in this week in AI!
Catch everything you need to know here 👇

Vision-Language Models connect what AI sees with what it reads and reasons.

They’re the foundation of AI systems that can interpret charts, medical images, retail shelves, or product catalogs.

But a generic VLM doesn’t understand your domain’s visual language.
That’s where fine-tuning becomes essential.

𝐖𝐡𝐲 𝐟𝐢𝐧𝐞-𝐭𝐮𝐧𝐢𝐧𝐠 𝐚 𝐕𝐋𝐌 𝐦𝐚𝐭𝐭𝐞𝐫𝐬

A pretrained VLM already knows the basics of visual-text reasoning.
Fine-tuning helps it specialize for your domain.

→ In healthcare, it learns to detect anomalies in MRIs and X-rays.
→ In retail, it interprets shelf images and product layouts.
→ In enterprise, it extracts structured data from invoices and reports.

You’re not rebuilding intelligence, you’re refining perception to fit your use case.

𝐇𝐨𝐰 𝐋𝐨𝐑𝐀 𝐦𝐚𝐤𝐞𝐬 𝐢𝐭 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐭

Full model fine-tuning is expensive and compute-heavy.
Low-Rank Adaptation (LoRA) keeps the base model frozen and trains only small adapter layers.

That means:
→ Faster training cycles
→ Smaller memory footprint
→ Lower compute costs
→ Domain adapters that are easy to swap in and out

You can maintain one base model and multiple lightweight adapters for each use case such as invoices, medical forms, or retail analytics.

𝐈𝐧𝐬𝐢𝐝𝐞 𝐚 𝐕𝐢𝐬𝐢𝐨𝐧-𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐌𝐨𝐝𝐞𝐥

A VLM has three main components:
→ 𝐕𝐢𝐬𝐢𝐨𝐧 𝐄𝐧𝐜𝐨𝐝𝐞𝐫 converts pixels into visual tokens.
→ 𝐅𝐮𝐬𝐢𝐨𝐧 𝐋𝐚𝐲𝐞𝐫 combines visual and text context for reasoning.
→ 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐃𝐞𝐜𝐨𝐝𝐞𝐫 generates captions, summaries, or structured responses.

Each layer introduces potential failure modes like poor resolution, misaligned regions, or verbose hallucinations. Fine-tuning improves alignment and reliability across these components.

𝐓𝐡𝐞 𝐟𝐢𝐧𝐞-𝐭𝐮𝐧𝐢𝐧𝐠 𝐥𝐢𝐟𝐞𝐜𝐲𝐜𝐥𝐞

→ 𝐃𝐚𝐭𝐚 𝐝𝐞𝐬𝐢𝐠𝐧: Collect diverse, high-quality, clearly labeled visuals.
→ 𝐓𝐚𝐬𝐤 𝐝𝐞𝐟𝐢𝐧𝐢𝐭𝐢𝐨𝐧 : Choose the right setup: captioning, VQA, extraction, or localization.
→ 𝐋𝐨𝐑𝐀 𝐭𝐫𝐚𝐢𝐧𝐢𝐧𝐠: Train adapters for each domain efficiently.
→ 𝐄𝐯𝐚𝐥𝐮𝐚𝐭𝐢𝐨𝐧: Use both quantitative metrics and human review for grounding and accuracy.

Always evaluate across different slices such as document type, lighting, and template to surface hidden biases.

𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 𝐚𝐧𝐝 𝐫𝐞𝐥𝐢𝐚𝐛𝐢𝐥𝐢𝐭𝐲

Each domain adapter should have its own dataset lineage, version, and evaluation score.
Reliability requires attention to fairness, privacy, consistency, and uncertainty handling.
Fine-tuning doesn’t just improve accuracy, it strengthens governance and ethical alignment.

LoRA fine-tuning makes VLMs faster to adapt, cheaper to deploy, and more aligned with your real-world data. 

〰️〰️〰️
Follow me (Aishwarya Srinivasan) for more AI insight and subscribe to my Substack to find more in-depth blogs and weekly updates in AI: https://lnkd.in/dpBNr6Jg

Digital Transformation Strategist

Creating, offering, designing, directing, and/or implementing part of the Digital Transformation strategy for several organizations. The main ones were for:
•	A group of companies that integrate services focused on the automotive sector, which included credit, leasing, and insurance products, where an ecosystem/platform was conceived.
•	A company in the Agricultural Sector, with operations in the USA and Mexico, where an ERP and Big Data architecture were designed to operate flawlessly.
•	A Mexican family-owned retail consumer company, where an e-Commerce solution (including digital payments) was defined.
All of the above:
•	Focused on the customers and using data science to understand when they interact, what they interact with, with whom they interact, how they interact, and where they interact to predict and offer them what they need and when they need it to meet their expectations. Creating a new business model and processes while capturing new value opportunities and innovation.
•	Enabling an open architecture based on flexible technologies (applying cybersecurity) like cloud computing, Big Data, predictive analytics, Cognitive / Artificial Intelligence / Machine Learning solutions, APIs, Biometrics, Bots-RPA, e-Commerce, Omnichannel, and remote collaboration tools.

I have also been a speaker on:
•	"Digital Transformation and the HR area" and “1st Digital Transformation Symposium: How to accelerate its implementation” for the Latam Business School. Such good acceptance that I am part of the professors for the Digital Transformation Specialization program.
•	“Change Management as a Key to Success in the Organizations’ Digital Transformation” for the Peru Digital e-Summit and “Talent Management in an Era of great challenges and high uncertainty” for the Peru eCommerce e-Summit of the Lima Chamber of Commerce.

CEO - CIO - CDO Consultant - Advisor | Digital Transformation Director | Fractional Executive

Back to Business

B2B is a company specializing in Outplacement and Retirement, Assessment, and Organizational Development services that supports the strategic function of Human Resources within companies.
✔ Lead the Financial Services and Information Technology industries within the organization.
✔ Help organizations in finding solutions to current Culture, Processes, and Technology issues by being able to design, direct, and implement their Digital Transformation Strategy.

Fractional Director for Financial Services & IT Industries

ICB Consulting® - Consultoría de Estrategia y Operaciones 

Expert Consultant in Digital Transformation.

Fractional Digital Transformation Consultant

Progredi Human Capital Consulting

✔ Lead the Financial Services (including Fintech) and Information Technology industries within the organization.
✔ To be the "voice of the client" into the organization to be able to design, direct, and implement the Digital Transformation Strategy.

Client Experience Fractional Director for Financial Services (including Fintech) & IT Industries

Latam Business School

Fractional Professor

Innovate/improve Strategy, Business Processes, and Technology in Digital Transformation projects for the Financial Services industry, exceeding the expectations of its customers.

Challenge: Analyze the needs of the business areas creating technological solutions that allow re-organizing the life experience of clients in the Financial Sector.

✔	Redesigned the enterprise data warehouse (Big Data) by integrating standardized business concepts to reduce subsequent expenses for upgrades to zero.
✔	Developed the proposals for the definition of master data management, establishing its standardization and governance, removing the duplication of corporate data, and improving the quality of customer data by 100%.
✔	Structured the cognitive solution that minimizes operational errors and fraud regarding transactions, Know your Customer (KYC) / employees, and Anti Money Laundering (AML); improving annual claims, current due loans, and loan reserve figures up to 75%, AML’s false positives by up to 30%, and the costs of handling alerts by up to 60%.

Financial Services / Banking SME (Subject Matter Expert)

Created, offered, designed, directed, and/or implemented part of the Digital Transformation strategy for several organizations. The main ones were:
✔ Bizzon Info Solutions (P) Ltd
✔ Demar
✔ MARSH LatAm & Caribbean

CIO - CDO Consultant – Advisor

Bizzon Info Solutions (P) Ltd.

Bizzon is a private software development company with headquarters based in India.	
Member of Bizzon's business leadership & executive management team.

Challenge: New business development (sales, product development, marketing strategy, customer relationship, alliances, and negotiations, among others).

✔	Controlled the design, testing, and marketing of the commands and inventory of ingredients application for restaurants by innovating the user experience (UX), achieving control in processing times, minimizing waste, and lack of supplies by up to 80%.
✔	Directed the Business Case that led to the decision not to open a local office in Mexico.

Group Strategic Advisor

Demar Instaladora y Constructora S.A. de C.V.

Demar is a Mexican family-owned enterprise dedicated to building, installing, and connecting oil & gas platforms within shallow waters. Its main customer is PEMEX.

Challenge: Transformation from a family-based business into a corporation, establishing the controls and administrative systems required, and coordinating up to 2,500 people.

✔	Structured and integrated the Governance and Transformation Program that controlled and supervised the strategic initiatives applied to employees, business processes, and technology, achieving a reduction in operating costs of 35% and minimizing its risk by 75%.
✔	Planned and directed the rationalization of the processes and records of human resources through the integration of an Electronic Clinical Record and Mobile Tele-Health Services system, minimizing 99% of medical errors and individualizing the treatment of each employee.
✔	Improved collaboration by establishing: ERP (SAP) systems; remote working tools; the migration of data, applications, and hardware towards a hybrid cloud scheme; reaching 100% of the administrative staff, including off-shore.

COO | CIO (Administration Director)

Marsh

Marsh is an insurance and risk broker company part of the global Marsh & McLennan group.

Challenge: Shaped the Operational Efficiency Program for Latin America.

✔	Led the implementation of the regional process transformation and reengineering program, based on Lean, Kaizen, and Change Management methodologies in Latin America, improving customer service times by up to 65% and policy payment processing by 85%.

Change Delivery & Transformation LAC (Latin America & Caribbean) SVP

I help organizations in finding solutions to current Culture, Processes, and Technology issues through Digital Transformation by transforming the business to become more Agile and centered on the Customer (data-informed)

CDO, CIO & Digital Transformation Director focused on helping organizations navigate the digital age. I partner with leaders to develop and execute strategies that resolve critical business issues related to culture, processes, and technology, ensuring a human-centric approach to innovation and growth.

Dynamic and results-driven Executive with 25+ years of experience leading strategic change in global organizations and SMBs. Proven expertise in consulting, designing, and implementing business-transformative initiatives that drive cultural, process, and technological change. Skilled in optimizing business processes through innovative technology solutions. Strong track record of building high-performance teams and ensuring organizational effectiveness. Experienced in business units, IT, operations, and professional services/consulting areas. Adept at delivering results, driving efficiency, and leveraging cutting-edge technologies. Excels in strategic planning and execution, collaborating with stakeholders across the organization to drive Digital Transformation. Effective communicator and relationship builder, fostering collaboration and innovation. Demonstrated ability to establish data and information strategies, governance, and policy development to create business value. A human-centric leader committed to driving organizational effectiveness and success in the digital age.

You can reach me at https://dtstrategist.com

Manuel Barragan

The Unseen Engine: Why Process is Your Digital Transformation's True Powerhouse

Imagine a highly skilled manufacturing company still battling late deliveries and confused support calls 📞. Their problem wasn't the product; it was their tangled, spreadsheet-and-email-based order fulfillment process. This story proves that a great product is nothing without a great process to deliver it.

In the article, you will learn how to:
✔️ Avoid the "paving cowpaths" peril: automating a flawed process only accelerates the flaws and magnifies existing inefficiencies into costly failures.
✔️ Recognize the major roadblocks created by siloed operations (e.g., sales vs. finance) and lagging administrative functions that delay critical decision-making.
✔️ Build a resilient digital core by prioritizing people, then process, then technology, starting with engaging employees to uncover bottlenecks.
✔️ Apply invaluable methodologies like Lean (eliminating waste), Kaizen (rapid improvement), and Value Stream Mapping (VSM) to rigorously analyze and redesign workflows before applying automation tools like RPA or Agentic AI.

Your process is the unseen engine of your Digital Transformation. When processes are lean and optimized, automation delivers impressive, measurable results like cost reduction and faster reporting. This dedication to process excellence builds the agility and resilience needed today.

Ready to transform your operations and empower your teams? Let’s talk with Digital Transformation Strategist about how optimizing your processes can unlock your organization’s full potential.

View newsletter: Digital Transformation Stories

I once discussed with some colleagues about a manufacturing company. They built incredible, custom components. Yet, their customers often faced late d

Open article: The Unseen Engine: Why Process is Your Digital Transformation's True Powerhouse by Manuel Barragan • 3 min read

The Unseen Engine: Why Process is Your Digital Transformation's True Powerhouse

Beyond Titles: Why Digital Transformation Demands True Leadership

I once saw a major software overhaul sputter because the CEO was absent from the conversation. Then I saw a similar project thrive because the leader was visibly involved, sharing their own learning curve. This difference proves that Digital Transformation isn't about code or cloud; it’s about people, and leadership is its heartbeat.

In the article, you will learn how to:
➖ Recognize the Leadership Gap, where failures occur because behaviors do not support the change, leaders act as managers, and the critical "why" of transformation gets lost.
➖ Cultivate a Transformative Leadership style that demands a shift from focusing on the stable to embracing change and new opportunities.
➖ Implement a Human-Centric Blueprint by defining a clear vision, practicing empathy and psychological safety, and openly communicating the transformation's personal relevance.
➖ Champion a Data-Informed vision by visibly using new tools, breaking data silos, and empowering teams to co-create innovation based on merit and expertise.

True leadership demands more than just a title; it requires a fundamental mindset shift and concrete actions. You must invest in your leaders and empower your teams to build a resilient, adaptive future that drives operational excellence and manages risk.

Is your organization ready to empower its leaders for digital success? Let Digital Transformation Strategist help you craft a leadership development strategy that truly transforms. Connect with us to explore how.

Every organization talks about Digital Transformation. They buy new tools. I once saw a team facing a major software overhaul. The technology was impr

Open article: Beyond Titles: Why Digital Transformation Demands True Leadership by Manuel Barragan • 3 min read

Beyond Titles: Why Digital Transformation Demands True Leadership

Digital Leadership: Human-Centric, Accountable, and Always Learning

Leadership is defined by actions, not titles. It's about serving your people. Effective leaders prioritize human well-being. They ease team members' physical, cognitive, and emotional burdens. Empathy, trust, and clear communication are key behaviors. Leaders foster psychological safety. This allows teams to innovate and raise issues openly. Integrity means consistent actions. Leaders live the company's core values.

Visibility from the top matters. Leaders must communicate the "why" and "what's in it for me" of transformation. They lead by example. This means actively using new digital tools. They also share their own learning curves. This builds trust. It reinforces the new ways of working.

Leadership is a skill developed over time. CIOs and CDOs belong at the strategic table. They align with peers. They drive cross-functional collaboration. Investing in development is crucial. This includes training and mentorship. Leaders address culture gaps head-on. They embody desired cultural shifts. They value employee input.

These leadership qualities drive operational excellence. They improve EX and CX. They secure cost efficiency. They also manage risks. This positions organizations for sustainable strategic growth.

Ready to cultivate transformative leaders? Let's connect with Digital Transformation Strategist.

Talent Transformation: A Digital Imperative for Growth

Your organization's ability to find and keep top talent is its biggest competitive edge. Slow, costly hiring processes waste money. They also drive away the very people you want. We envision a new talent journey. This journey is strategic and engaging. It delivers the best talent efficiently. We aim for faster hires. We want data-driven selection. Our goal is also to reduce bias and better candidate experiences.

Imagine an internal talent marketplace. Your employees discover new opportunities there first. This boosts morale and retention. For internal or pre-qualified talent, a "Talent Pool Express Challenge" speeds things up. This ensures objective, skill-based assessment. It cuts bias further.

For external candidates, we replace old job descriptions with "Un-Job Descriptions". These focus on real problems to solve. Candidates show their skills, reducing bias. We also build talent pipelines through community engagement. This finds skilled people before needs arise.

Our selection process uses "Real-World Challenges". Candidates present solutions to actual business problems. This replaces multiple interviews. We get unmatched insight into their performance and communication.

This Digital Transformation of talent isn't just about HR. It improves every part of your organization. You get higher-quality hires faster. Your teams are happier and more productive. This drives strategic growth. It also manages costs and reduces risk effectively. We help you create this future.

What steps will you take to transform your talent journey? Connect with Digital Transformation Strategist to discuss your strategy.

Closing the Skills Gap for Digital Resilience

Many organizations are pushing for digitization, yet often forget a critical piece: their people. It is not enough to simply adopt new technology; you must also cultivate a workforce ready to use it. This often means facing a significant skills gap. Neglecting to reskill current employees or recruit new talent with essential mindsets and toolsets creates vulnerabilities. This oversight limits competitive advantage and hinders true organizational resilience.

Understanding your team's capabilities is key. Without up-to-date and in-depth employee skills profiles, leaders make deployment decisions in the dark. How can you optimally use talent if you don't know who has what skills? This lack of insight leads to inefficiencies and missed opportunities for strategic growth. We help organizations build these crucial profiles, ensuring every talent decision is informed and effective.

True professional development means personalized learning. Training should allow employees to grow, offering digital platforms that provide tailored opportunities. This human-centric approach develops individual skills and aligns your entire workforce with future business needs. By investing in continuous professional development, you are managing risk, improving efficiency, and enhancing both employee and customer experiences. This strategic approach ensures your organization stays competitive and thrives in a rapidly changing world.

Ready to build a future-ready workforce? Reach out Digital Transformation Strategist for a consultation.

Training: Your Unsung Hero for Risk and Culture

Many organizations focus solely on technology for Digital Transformation, overlooking a powerful tool: effective training. Without it, even the best tech stacks can crumble under human error or resistance. Consider cybersecurity: advanced systems are vital, but without continuous employee education, your organization remains vulnerable to threats like Business Email Compromise. Training builds a security-conscious culture, drastically cutting cyber risks and protecting your digital innovation.

Transforming processes also demands a trained workforce. In dynamic industries, moving to multichannel operations requires employees to master new skills, such as effective digital presentations. Training tackles resistance to change and closes skill gaps, making your company truly data-informed and agile. This human-centric approach ensures operational excellence, not just technological adoption.
 
A strong organizational culture, ready for digital change, is built on consistent training. A finance sector case study revealed a crisis failure due to a lack of training, showing how Digital Transformation must integrate with business continuity plans. Training instills data literacy and encourages a culture of collaboration, experimentation, and adaptability. This proactive approach manages risks, improves efficiency, and drives strategic growth by empowering your people.

Is your training strategy truly supporting your digital goals? Contact Digital Transformation Strategist to strengthen your culture and mitigate risks.

Process Optimization: The Engine of Digital Transformation

Process optimization is not just about tweaks. It is about maximizing resources and achieving operational excellence. This directly boosts performance and financial health. It also elevates customer and employee satisfaction.

Consider the impact. Optimized processes can slash operational costs. Some programs even cut costs by 35%. Improving and automating processes can lift a company's revenue by 4% to 8%. That is a significant financial gain.

Think about productivity. Streamlined workflows eliminate redundancies. Automating tasks frees employees. They can then focus on higher-value work. Robotic Process Automation (RPA) and Agentic AI are tools for this. It significantly increases efficiency. It also boosts overall productivity.

Quality and speed also improve. Process optimization enhances precision. It improves traceability in routine tasks. One financial firm, for example, cut reporting time by 53%. They did this by removing re-processes and recaptures. This is the power of optimized processes.

Process improvement drives continuous gains. It fosters agility. It makes organizations adaptable. This is crucial for innovation and strategic growth.

Ready to unlock these benefits for your organization? Let's discuss your process optimization journey.

Your customers are talking. Are you listening and acting? If not, contact Digital Transformation Strategist to help you with listening and acting. This focus is your competitive edge.

Optimizing Processes: Lean, Kaizen, Agile, and AI-Powered

Process optimization drives true Digital Transformation. We use proven methodologies and cutting-edge tools. Lean and Kaizen, for example, eliminate waste. They streamline processes through continuous improvement. These methods boost flexibility, quality, and responsiveness. We often combine them with Design Thinking. This creates powerful, continuous improvement programs.

Value Stream Mapping (VSM) is another key tool. It is a Lean technique. VSM identifies waste and redundancies. It analyzes the flow of materials, data, and requirements. This helps pinpoint inefficiencies.

Agile practices are essential. They use cross-functional teams. They enable rapid iteration. This improves speed-to-market. Agile collaboration needs structured processes and governance. This ensures efficiency.

Automation technologies are game-changers. Robotic Process Automation (RPA) automates low-value tasks. Agentic AI takes this a step further. Integrating AI into your Business Process Management (BPM) strategy empowers teams. It redefines efficiency. It also drives continuous improvement.

These methods lead to operational excellence. They enhance employee and customer experiences. They also create significant cost efficiencies. They strengthen risk management. This positions your organization for strategic growth.

Ready to transform your processes? Let's explore with Digital Transformation Strategist these powerful methodologies and tools.

Digital Leadership: Shaping Data, Empowering Change, Mastering Hybrid

Leaders navigate complex digital shifts. Their impact spans data, change, and the new world of work. True Digital Transformation thrives on data. Leaders champion this shift. They frame data as an ally. This eases fears, building excitement for new capabilities. Breaking down data silos is important. Leaders ensure data guides decisions. This moves companies beyond intuition. This builds long-term growth for the entire enterprise.

Digital change is human change. Leaders are key agents. They empower teams to innovate. They encourage co-creation. Delegating based on skill, not just loyalty, is key. This drives organizational growth. Leaders must map initiatives. They gather perspectives from all levels. This reduces uncertainty and builds trust.

The hybrid work model demands new leadership skills. Multimodal leaders excel. They act as conductors, catalysts, coaches, and champions. Remote strategies need clear communication. Technology use is central. Virtual engagement maintains team cohesion. Agile leadership keeps organizations ahead.

These leadership actions lead to operational excellence. They improve employee and customer experiences. They also create cost efficiencies. This strengthens risk management. It positions organizations for strategic growth in a competitive marketplace.

Ready to elevate your leadership? Let’s discuss with Digital Transformation Strategist how we can help you.

Reinventing Talent Acquisition: The Human Cost of Outdated Hiring

Searching for talent often feels like looking for a needle in a haystack while blindfolded! 😩 The reality is, when your Selection, Recruiting, and Onboarding processes drag on for months, you're not just losing candidates, you're racking up huge costs. This agonizingly slow pace is a critical blind spot in many Digital Transformation efforts.

In the article, you will learn how to:
· Quantify the significant financial and operational burdens of slow decisions, where a single critical role can cost up to $7,000 per day and a bad hire over 30% of the first-year salary.
· Implement a Smarter Talent Journey by moving from passive job posts to proactive sourcing through creating an internal talent marketplace and using "Un-Job Descriptions".
· Build an objective assessment process using the "Real-World Challenge: The Candidate's Pitch" to replace multiple subjective interviews and quickly validate skills for high-potential candidates.
· Revolutionize Onboarding with a human-centric approach using an "Onboarding Success Dashboard", a gamified "Pre-Boarding Adventure Map," and a "First Project Sprint" to drive immediate contribution and high retention.

The current state of talent acquisition is simply unsustainable. Transforming your talent journey is a strategic investment with quantifiable returns: faster hiring, better quality hires, and a stronger employer brand. It’s time to truly embrace Digital Transformation for your people.

Let Digital Transformation Strategist partner to transform your talent journey into a strategic advantage, securing your future through human-centric journeys.

Finding the right people can feel like searching for a needle in a haystack while blindfolded. At almost any organization, this story is the same. The

Open article: Reinventing Talent Acquisition: The Human Cost of Outdated Hiring by Manuel Barragan • 4 min read

Reinventing Talent Acquisition: The Human Cost of Outdated Hiring

AI and HR: Enhancing the Human Touch

Technology in HR must always serve people, not replace them. I point out that tools like AI can transform HR, but only if they enhance the human element.

Automation frees up valuable time. By automating mundane tasks, HR professionals can focus on strategic work, like developing talent and improving employee experience. As well, AI support employees from all areas by automating boring tasks. This leads to cost savings, better risk management, and a more engaged workforce. Technology should simplify, not complicate.

AI also changes how we give feedback, giving managers the right data for making it more personal and efficient. This helps build a culture where everyone grows.

Organizations need real-time data on employee skills. Knowing who can do what ensures we deploy talent optimally, make smart employment decisions, and quickly respond to unexpected challenges. This helps us keep skilled employees and maintain operational agility.

Ready to strategically apply technology in your HR function? Let Digital Transformation Strategist help you discover how AI and data can empower your HR team.

Seamless Onboarding: The Digital Key to Talent Retention

Bringing new talent into your organization often feels like a gamble. Almost 20% of new hires leave within 45 days, wasting resources and disrupting teams. This early turnover highlights a critical gap in many organizations. 

With an "Onboarding Success Dashboard", it streamlines everything else. It automates legal forms, IT setup, and HR documents. This eliminates paperwork for new hires and stakeholders. It ensures all necessary tools are ready on day one. This digital system frees your teams for higher-value work. It saves time and prevents frustration.

We must ensure new hires feel connected, productive, and supported from day one, with a "Pre-Boarding Adventure Map" that builds excitement. This personalized digital guide starts at offer acceptance. It clarifies expectations and introduces company culture. It reduces first-day jitters. Additionally, "Reverse Mentoring" pairs new hires with senior leaders. This shares fresh insights and builds early connections. Short "Cross-Functional Immersions" provide a holistic business view.

Then, each new hire starts with a "First Project Sprint". This immediate, tangible task allows them to contribute within weeks, not months. It accelerates learning and fosters a sense of purpose. This approach moves new talent to full productivity faster.

These human-centric strategies drive real operational excellence. They significantly improve retention. They accelerate productivity and enhance both employee and customer experiences. They also manage costs and risks tied to talent acquisition. This transforms onboarding from a compliance exercise into a strategic growth engine.

How do you ensure your new talent thrives? Let Digital Transformation Strategist discuss them with you.

Bridging the Digital Divide: Why Training is Your Best Transformation Tool

That moment of asking a colleague, "How do I even change this feature?". That initial bewilderment perfectly illustrates the chasm between grand Digital Transformation ambition and operational reality. We pour money into AI and analytics, but if our people lack the familiarity (the training) that technology becomes an expensive paperweight. True transformation is a human endeavor, not just a tech one.

In the article, you will learn how to:
✔️ Analyze the critical oversight of adopting sophisticated AI platforms and analytics dashboards without equipping teams with the necessary skills, leading to integration issues and wasted financial investment.
✔️ Understand why traditional, feature-focused training falls short and how this gap impedes operational excellence and is a critical cybersecurity vulnerability.
✔️ Implement targeted training programs for AI collaboration, emphasizing human oversight, and launch robust, practical data literacy initiatives across all departments.
✔️ Revolutionize training design by building programs around real-world scenarios, using a blended learning approach, and treating workforce development as a strategic, ongoing imperative.

Stop viewing training as an expense or a compliance checkbox. It’s your most strategic investment. Investing in comprehensive, human-centric upskilling directly translates into unparalleled operational excellence, better customer experiences, and robust risk mitigation. Let's collaborate to build a workforce that is not just prepared for the future but actively engaged in shaping it.

Reach out Digital Transformation Strategist today to explore how we can partner to tailor a transformative training strategy that empowers your people and drives your organization's success.

Remember the early days of smartphones? Many of us, myself included, handed our new devices to a tech-savvy child or a younger colleague, asking, "How

Open article: Bridging the Digital Divide: Why Training is Your Best Transformation Tool by Manuel Barragan • 4 min read

Bridging the Digital Divide: Why Training is Your Best Transformation Tool

Digital Transformation Leadership: The Mindset Shift

Great post by Digital Transformation Strategist. True change needs consistent leader commitment first. This sets the pace for the whole culture shift. You cannot buy a Digital Transformation mindset.

Strong leadership turns change into progress. When leaders model curiosity and steady action, teams stay engaged and the transformation gains real traction across daily work.

Effective leaders drive operational excellence. They boost employee experiences. They also improve customer journeys. This creates real cost efficiency. It strengthens risk management. Strong leadership sets a firm foundation. It secures future strategic growth.

We partner with leaders. We help them build this foundation. Our approach empowers your team. It secures your organization’s growth. Connect with us to discuss your leadership transformation.

View company: Digital Transformation Strategist

Digital Transformation Leadership: The Mindset Shift

Digital Transformation starts with people. Leaders are the cornerstone of this shift. They define the future vision for the company. They also steer the organizational strategy. Many transformations stumble. A key reason is leadership behavior. In fact, a third of failures link directly to poor leader commitment.

Moving people and culture needs a leader's touch. Leaders must embrace a growth mindset. They guide their teams through change. This journey is often the hardest part. Without strong leadership, employees disengage. Progress slows to a crawl. The entire transformation faces severe risk.

Effective leaders drive operational excellence. They boost employee experiences. They also improve customer journeys. This creates real cost efficiency. It strengthens risk management. Strong leadership sets a firm foundation. It secures future strategic growth.

We partner with leaders. We help them build this foundation. Our approach empowers your team. It secures your organization’s growth.

Connect with Manuel Barragan to discuss your leadership transformation.

Talent Transformation: Why Your Hiring Process Needs a Digital Overhaul

Digital Transformation Strategist shows how slow hiring drains cash and focus, and it pushes leaders to rebuild the process with clear data and simple tools so teams stay strong and work moves on time. Vacant seats always stop strategic project launch. Digital Transformation requires rethinking talent processes. Better processes reduce hiring costs and turnover risk.

Imagine filling key roles faster with the right people. This saves hundreds of thousands of dollars each year. Projects launch on time. Innovation thrives. Your employer brand shines. A strong talent strategy is not a luxury; it is a business imperative. It improves employee and customer experiences. It ensures strategic growth. It manages costs and reduces risks.

What are your biggest talent acquisition hurdles? DM me to help you on tackling them.

Talent Transformation: Why Your Hiring Process Needs a Digital Overhaul

Every vacant critical role drains between $500-$7,000 from your budget daily. The traditional 3-6 month hiring process is not just slow; it's costly and alienates top talent. A bad hire can equal 30% of a first-year salary. Nearly 20% of new hires leave within 45 days due to poor onboarding. These numbers show a clear problem that affects your bottom line and future growth.

This isn't just about HR; it's a strategic challenge. Lengthy vacancies delay critical projects. They stifle new ideas and slow down market entry. Competitors move faster while your teams remain understaffed. This also damages your employer brand. Over 70% of candidates with bad experiences share them widely. Current employees also feel the strain. They face burnout and decreased morale covering for empty seats. This drives up internal turnover risk.

True Digital Transformation tackles these talent challenges head-on. It reshapes how you find, hire, and keep people. We rethink processes, leveraging data and smart tools. We focus on a human-centric approach that respects candidates and supports your team. This creates a better experience for everyone. It drives operational excellence.

Imagine filling key roles faster with the right people. This saves hundreds of thousands of dollars each year. Projects launch on time. Innovation thrives. Your employer brand shines. A strong talent strategy is not a luxury; it is a business imperative. It improves employee and customer experiences. It ensures strategic growth. It manages costs and reduces risks.

What are your biggest talent acquisition hurdles? Manuel Barragan can help you on tackling them.

Digital Transformation: Process Before Technology

Great post by Digital Transformation Strategist. Digital Transformation starts with understanding human work. Strong process work saves money and avoids chaos. Fast automation makes poor processes worse quickly. When teams fix pain points before buying tools, the tech delivers real gains instead of faster trouble. Good governance aligns teams and lowers project risk.

In the end, Organizations must have a focus on process to drive operational excellence. It improves both employee (EX) and customer experiences (CX). This leads to true cost efficiency. It strengthens risk management. It sets your organization for strategic growth.
 
Ready to optimize your processes before investing in new tech? Just DM me.

Digital Transformation: Process Before Technology

Digital Transformation begins with people, then process, then technology. Many companies rush to buy new software. This often creates more problems. Automating a broken process just makes it broken faster.

Before any tech investment, analyze current workflows. Find bottlenecks. Understand where work stops. Talk to the people doing the daily tasks. They uncover hidden delays. They know the workarounds. This input is gold. Use it to redesign processes. Remove dead ends. Automate high-impact tasks.

Standardization is vital. Processes need a common logic. This creates efficiency. Strong governance frameworks are necessary. They enable agile collaboration. This aligns business and technology teams. It avoids wasted investments.

A focus on process drives operational excellence. It improves both employee and customer experiences. This leads to true cost efficiency. It strengthens risk management. It sets your organization for strategic growth.

Ready to optimize your processes before investing in new tech? Let’s talk with Manuel Barragan.

Bridging the AI and Data Literacy Gap

AI success starts with your people, not your platforms. Many organizations invest in AI tools but overlook the foundation: data literacy. When teams understand how to interpret data, ask the right questions, and apply insights, AI becomes a multiplier, not a mystery.

Organizations must empower their workforce to thrive in the AI era. Train for curiosity, not just compliance. That’s where transformation truly begins.

Are your teams AI-ready? Contact Digital Transformation Strategist if you are having trouble in doing it.

Bridging the AI and Data Literacy Gap

Many organizations struggle with AI adoption, and it’s not always the tech itself. Often, the missing piece is human readiness. We see this all the time: companies invest heavily in AI tools but overlook the vital step of training their people. Without proper human oversight and interpretation, even the most advanced AI can create more problems than it solves. This oversight often leads to integration headaches and missed opportunities.
 
Building a truly data-informed culture starts with empowering your team. Data literacy isn't just for analysts; it’s a must-have skill for everyone. Imagine a workforce where every employee can interpret key performance indicators and make informed decisions. This isn't a pipe dream; it's achievable through tailored data literacy programs. These programs go beyond basic features, offering hands-on training and workshops built around real-world tasks and daily operational scenarios.

Effective training moves past abstract concepts. It focuses on what employees truly need to succeed, ensuring systems align with their actual experiences. A blended learning approach works best, combining live workshops, on-demand courses, and practical, hands-on exercises. This builds collective capability, fuels innovation, and drives organizational growth. Investing in your people's AI and data literacy skills manages risk, improves efficiency, and boosts customer and employee experiences. This human-centric approach turns technological investments into strategic advantages.

Ready to empower your team for the AI era? Contact Manuel Barragan today to learn how.

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The Battle

Aishwarya Srinivasan

Manuel Barragan

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Posts

Engagements

Likes

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);}Aishwarya Srinivasan's LinkedIn Performance

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Performance ScoreAishwarya Srinivasan's LinkedIn Performance