Phygitalytics

 

Welcome to Phygitalytics!!!

Thank you to all past, present, and future customers!

Happy Responsible AI Adoption!!!

🧠 The Silent Killer of AI Adoption: Leadership-Level AI Illiteracy

The bigger problem of AI adoption isn't tooling or data, it's ‘AI illiteracy’ at the leadership level.

The kind of questions we ask reflects how much we know. And too often, the questions reveal a dangerous gap:

1️⃣ Misunderstanding ML like software engineering

“I will give you 10 samples, can you build a model?”
“You have trained a model on this data, why can't you retrain it by each category?”
“You already have the architecture, isn't that half the job?”

In software, when you build an order placement API, it’s reusable, you can lift and shift it across regions.

But in AI, the model trained on one dataset doesn’t behave the same when trained on a subset.
👉 Data imbalances matter. Feature distribution matters. What works in one set may break in another.

2️⃣ Oversimplified expectations

“Can we retrain the model every day?”
“Let’s schedule model updates at the end of each day.”

Nobody trains models every day. That’s not how MLOps, retraining windows, or data quality cycles work.

3️⃣ Confidently asking the wrong questions
The kind of questions we ask reflects our AI awareness rate.
The problem isn’t curiosity, it’s confidence in assumptions without understanding the complexity behind them.

4️⃣ Biases disguised as "opinions"
In many leadership discussions, I observe a mix of:

• Strong opinions shaped by past software patterns
• Lack of exposure to ML trade-offs
• Forcing timelines and expectations AI can't meet,  yet

🔁 This requires unlearning, openness, and re-learning.
AI won't fail because it’s flawed. It will fail when leaders assume how it works — and miss how it actually works.

Let’s not just adopt AI. Let’s understand it.
A little learning, backed by humility, goes a long way.
Titles don’t validate assumptions. Understanding does.

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#AILiteracy #AILeadership #AIAdoption #MLReality #AIExpectations #EnterpriseAI #TechAwareness #UnlearnToLearn #ResponsibleAI #AIThinking #AIProductLeadership #MLOpsReality #DataMatters

🎯 ML, DL, GenAI - What Do You Really Need?

It’s not about who knows the most models. It’s about who can solve the problem with the right approach.

🚀 In interviews and real-world projects, here’s what separates noise from value:

• Can they choose the right approach? → Classical ML, Deep Learning, or GenAI not everything needs the latest hype.
• Do they know when not to use GenAI? → It’s impressive to know LLMs. It’s smarter to know when not to call them.
• Can they debug when pre-built solutions fail? → You don’t need a model zoo, you need people who can trace the issue and fix it.
• Can they explain their trade-offs and iterate with clarity? → Choosing between latency, accuracy, explainability, and cost is real work.

💡 Skip the overly academic or overly abstract interviews. Hire those who think in problem-first, data-smart, solution-aware ways.

✅ Evaluate with real-world scenarios.
✅ Prioritize learning agility and debugging mindset.
✅ Look for clarity in reasoning, not just complexity in vocabulary.

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#MLvsDLvsGenAI #AIHiring #GenAIRealityCheck #DataDrivenEngineering #AIProductThinking #ProblemFirst #ResponsibleAI #TechRecruiting #DebuggingMatters #RealWorldAI #InterviewWisdom #EnterpriseAI #ThinkBuildLearn

 Keep Thinking!!!

 

GenAI Reality Check: That RAG Use Case?

 

Keep Thinking!!!

10 Slides in Every GCC Pitch Deck

Adding some Hard truth complementing what it means, for some pages based on observations

10 Slides in Every hashtag#GCC Pitch Deck (and What They Actually Mean)
Slide 4: “We’re Not Just a Support Center”
What it means: But we’re still taking direction from HQ for every single product decision.
✅ Hard truth: Core work may not always be there; the trust factor may not be present.

Slide 5: “India Will Drive Innovation”
What it means: We haven’t defined ‘innovation,’ but it looks great on slide titles.
✅ Hard truth: Many times, it's hackathons that never turn into product features.

Slide 6: “We’ll Scale to 200 People in 12 Months”
What it means: We haven’t built a talent pipeline or local employer brand. But growth sounds impressive.
✅ Hard truth: Sometimes the focus is not on long-term strategy or learning, but on numbers and quantity.

Slide 8: “Hiring Top 1% Engineers”
What it means: We’ll post a JD with 10 must-have skills and wonder why no one’s applying.
✅ Hard truth: Most have every listed skill, follow standard patterns, and are masters of 50 tools, but lack focused depth.

Slide 10: “This Is Just the Beginning”
What it means: It definitely is, and depending on who we hire first, it’ll either scale fast or stall early.
✅ Hard truth: We will provide another narrative when the time changes.

hashtag#perspectives hashtag#observations

Ref - Link

Keep Thinking!!!

From Idea To Prototype With GenAI | Insights by Sivaram A, AI Advisory at Stealth AI

 

Happy Learning!!!

2024 GenAI Tech Talks

Happy Learning!!!

The Great AI Disconnect: What Leaders See vs What Engineers Face

It's a Cycle of Hype - Hope - Repeat

• 🧠 The CEO was sold a “miracle platform” — “It’ll boost your existing models by 90%!”
• 📊 The VP hears, “It integrates 90+ data sources seamlessly!”
• 🧩 The Senior Manager is told, “Plug-and-play pipelines. Just flip a switch!”
• 🧑‍💻 The Engineers? They discover broken schemas, data gaps, and a model that works on benchmarked datasets only

When results don’t match the pitch:

• The CEO is promised: “50% discount next cycle!”
• The VP gets: “Let’s collaborate and fix it.”
• The manager burns out.
• The engineers build workarounds.

And the narrative? Reboots.

🎢 Rinse. Hype. Repeat.

Ref - Link

Keep Thinking!!!

The Real Hallucination: Believing AI Can Replace Human Experience

 🧠 When we don't prioritize human intelligence, we allow flawed narratives to take root. I wish we acknowledged this reality. This Ad itself reflects Human Hallucination of AI.

🤖 AI processes data, but it does not experience the world. It can simulate emotions, but it does not truly feel them. 

❤️‍🔥 The difference between AI and human experience isn’t just knowledge, it's the depth of feeling, the weight of emotions, the richness of perspectives, and the reality of lived moments.

📉 “Good use cases are invisible until bad examples make headlines.”

#HumanIntelligence #AIEthics #ResponsibleAI #EmotionalIntelligence #HumanCenteredDesign #AIvsHuman #TechnologyWithPurpose #AugmentedIntelligence #FutureOfWork #HumanFirst #AIReflection #ResponsibleAI #DigitalHumanism #AIAndEmpathy #LeadershipInAI #Hallucination
#MindfulTech

Ref - Link

Keep Thinking!!!

🔍 Sometimes it's not the outcome, but the overlooked patterns that matter most.

 This flowchart captures a silent reality, how small decisions and invisible habits compound into undesired career paths. From academic stress to burnout, and from neglected skills to financial crisis—this is a system of causes, not isolated events.

🎓 If you're a student navigating this AI-driven, hyper-competitive era:

• Your resume may look perfect,

• Your marks may shine, 👉 But if your habits, mindset, and industry readiness aren't aligned, you’ll face a different outcome than you expect.

This flow was haunting my thoughts. It shows how things often don’t end up the way they’re supposed to—not because of one big mistake, but due to overlooked choices made daily.

⚠️ Be intentional about how you study, network, build skills, and face failure.
Bad outcomes aren’t built in a day. Neither are great careers.

Keep thinking. Stay aware. Own your path.

Prompt + AI Code + Human Thinking > Prompt + AI Code

 

Ref - Link

✅ Encourage juniors to use AI tools. It’s how the industry is evolving. Let them explore, but don’t stop at the surface.

🔍 Observe what bugs they can identify in AI-generated code and how they fix them. That tells you a lot about their problem-solving ability.

⚙️ Audit how they think about design and scalability. Can they spot limitations in AI output? Are they making informed architectural decisions?

🧠 The difference between a learning mindset and a copy-paste mindset becomes obvious over time. AI can accelerate growth, but only if developers take time to understand why things work.

🎯 Also, interview patterns must evolve to reflect this new ecosystem. We shouldn’t penalize devs for using modern tools—we should assess how they use them critically and creatively.

Let AI be a catalyst, not a crutch.

Keep Thinking!!!

Always plan for High Availability and backup models.

 

• 100% Reliability - Very much impossible
• Every system will have failures and lessons to fix
• AI intelligence can also fail more than human intelligence

Keep Thinking!!!

Human confidence + AI guidance > AI confidence alone

 

Ref - Link

Keep Questioning!!!

This reddit comment has been picked up by Google's AI

"Google lists mixing 1/8 cup of non-toxic glue with your pizza sauce to help the cheese stick and add extra tackiness." - Ref - Link

Comment
by from discussion
inPizza

This reflects the state of Ethical AI Adoption

Keep Questioning!!!

AI Calories Scam

• Near Pose - X Calories
• Far Pose - X/2 Calories
• Side Pose - 3X Calories

Ref - Link

Keep Thinking!!!

Underappreciated Things in Life

To all IT professionals working within rigid pyramid structures, where growth is linear and competition is often the currency of progress

Forgive the competition. Celebrate your life. There are countless underappreciated silent heroes in this sector.

• Saying yes to align with the team, even when your views differ

• Doing your work diligently without seeking recognition or visibility

• Choosing forgiveness when you could easily call out someone's mistakes

• Solving problems quietly, even when there's no direct reward or acknowledgment

• Staying away from visibility politics, yet remaining silent and dignified

• Taking time to learn deeply, rather than rushing to compete

• Balancing your own views while adapting to collective patterns

• Being patient enough to accommodate, even when others are agenda-driven rather than value-based

• Sensing narratives and intent clearly, yet stepping away gracefully once you’ve connected the dots

Keep Going. Your quiet strength matters. 🙏

What is AI :)

Many times truth can be expressed in simple words :)

 Keep Thinking!!!

AI products in Healthcare, Hard fitment

 

Ref - Link

Keep Questioning!!!

Prompt Engineering - AI Vibes - Song with Lyrics and Music :)

[Verse]

Learning AI every day
Words and lines but in a new way
Teaching prompts to obey
Let's do this come what may

[Verse 2]

Lines and codes like a game
Every prompt should have a name
Crafting questions to be tame
Jumping into this no shame

[Chorus]

Prompt engineering
Creating everything
Generation accelerating
AI minds syncing

[Verse 3]

From models to output bright
Leading bots to give insight
Words aligned just right
Artificial lights ignite

[Verse 4]

Tune your prompts to sing
Every thought can bring a spring
Questions with a new zing
AI’s potential we'll bring

[Bridge]

Every prompt a spark
Lighting up the dark
Generation's mark
Begin that creative arc

Keep Going!!!

How AI will eat jobs, things which I have noticed so far.

Case #1 - Large Investment Banking Company

• Created there own LLM to help developers to speed up with coding which increased productivity
• Because of new LLM, they don't want to hire new people and existing people absorbed the new work 

Case #2 - Product Based

• Reduced the offshore strength from 15 to 08, soon they are abt to reduce it to 05
• Paid AI tool for all documentation purpose.

Case #3 - Cloud team

• Cloud team able to manage the same work with only 30-40% of previous employee count 

Key notes from post -  How AI will eat jobs, things which I have noticed so far.

Keep Thinking!!!

❌ Increased Bugs and Defects

Some CTOs observed that aggressive GenAI adoption led to higher defect rates and an increased support burden post-release.

Here's a simplified view:

• ✅ GenAI-First CTO + Trained Team + Established Best Practices = Productivity
• ✅ GenAI-Ready CTO + Trained Team + Piloted Projects = Stability
• ❌ GenAI-Aware CTO + Aggressive GenAI Adoption + AI-Aware Team = Chaos

Ref - Link

Keep Going!!!

My Experience and Ways of Working with Gen Z Peers

After a long time, "Dude" and "Bro" have made their way back into calls.

My Approach

When it comes to working, I tend to rely on the basics — focusing on a more collaborative approach. Instead of pushing hard on deadlines, I think about how I would solve a problem myself and use that mindset to guide others.

Managing Challenges

Every day brings a new set of challenges. We are constantly racing against time versus quality. There are always different solutions, but on a personal level, how do I ensure I don't burn out?

For me, it comes down to knowing my work, staying open to learning, and balancing outcomes.

Working with Others

When collaborating with a co-worker or junior, I make it a point not to simply hand out instructions like "do XYZ" or "complete ABC."
Many times in my own experience, I’ve only been given instructions — "do this, do this."
But my style of execution is more like: "If I were to do this, how would I approach it?"

Balancing Time and Quality

Rather than passing along time pressure, I try to share ideas about what we can realistically accomplish within a given timeframe. This helps us make trade-offs between time and quality.

Time is important.
But quality always speaks above everything else.

It's tricky to strike the right balance, ensuring the output meets the bar without putting too much pressure on yourself or the team.

Building Trust

Within the team, cultivating a culture of trust is key.
It's not about rolling up your sleeves for everything, every moment, every hour.

It’s about doing the best you can, without blocking others or creating unnecessary pressure.
Be clear on what you want to do and how you plan to achieve it.

Unless you have clarity on how something can be done in limited time, just assigning it as a task adds more pressure.

Collaboration becomes even more important under intense pressure.
It should never be reduced to one-way communication like, "do this, do this."

"Collaboration under pressure is not about commands — it's about clarity, trust, and shared perspectives"

Keep Thinking!!!

75 mph Tesla crash occurred while Autopilot

 

Keep Thinking!!!

AI Pricing - Microsoft cuts data centre plans and hikes prices in push to make users carry AI costs

 Pricing by Value and Services

• For Model Providers: - Pricing is driven by token count, model usage, and infrastructure costs. As AI workloads scale, operational expenses push providers to adjust usage-based pricing.

• For Enterprise Solutions: AI-powered features are now premium add-ons, with rising prices for AI services like Microsoft Copilot. These are strategically packaged to monetize AI as a high-value layer on top of existing products.

• For Customers: They experience improved productivity but face significantly higher costs, especially in enterprise subscriptions where AI is bundled as an extra.

• Key USP: The core value proposition is positioning AI as a high-value productivity tool that enhances workflows, automates tasks, and unlocks efficiency gains.

• What’s coming next:
  Expect tiered AI feature offerings across products to maximize adoption while segmenting the market:

• 🟢 Basic: Entry-level, limited AI capabilities (possibly free or low-cost).
• 🟡 Premium: Advanced features focused on team productivity.
• 🔵 Professional: Full-featured AI, enterprise-grade tools, customization, and priority performance.

Microsoft cuts data centre plans and hikes prices in push to make users carry AI costs

Keep Thinking!!!

By 2026, AI Code > AI Code + Human Input / Iterations

 

2025 will be the last year where people will be superior to ai. From 2026 onwards it’s getting crazy. Wild times ahead.

„AI coding capabilities will reach a "very serious" level by the end of 2025 — and may match the best human coders by late 2026“

pic.twitter.com/4LwQRWfn4o

— Chubby♨️ (@kimmonismus) March 2, 2025

Keep Learning!!! 

Knowledge is Cheap, but Focus is Expensive!

 Want to be productive today? It’s not about working long hours or collecting shiny accolades. True innovation doesn’t come from:

❌ More hours worked
❌ Star ratings on a project
❌ Endless hackathons
❌ Tech talks

With so much knowledge and code readily available, real impact comes from:

✅ Working with a great team
✅ Collaborating effectively
✅ Iterating and improving
✅ Failing fast and learning
✅ Solving smaller, meaningful problems

Instead of chasing a grand vision, start building—step by step.

Keep thinking. Keep solving. Keep moving forward.!! 

AI-Friendly Before AI-First: GCC Perspectives

In a recent conversation with my ex-boss, we explored some of the unique dynamics of Global Capability Centers (GCCs). One key takeaway: a company must be AI-friendly before it can become AI-first.

Alignment Starts with Initiatives, Not Just ROI

Organizations often begin their AI journey through initiatives rather than immediate ROI-driven motives. There might be AI talent within the team, but project priorities shape what gets implemented. As a consultant, I’ve seen that internal teams possess strong capabilities but are often bandwidth-constrained. They will evaluate, challenge, and probe external perspectives, yet their ability to execute depends on time and focus.

The Role of GCCs: Delivery vs. Innovation

GCCs can function in multiple ways—either as pure delivery centers catering to regional project needs or as innovation hubs driving transformational change. The distinction is crucial because execution models differ significantly.

Innovation vs. Execution: The Long Game of AI

Project success, project innovation, and project vision are all distinct. A project doesn’t end when it goes live; it evolves. AI and data-driven products thrive on iteration—data quality improvements, model refinements, customer feedback loops, and continuous enhancement. The real differentiator isn’t just building and shipping—it’s about creating lasting impact.

Keep Going!!!

Growing Better in Your Perspective, Not in Comparison

Career is Not:

The competition challenges individuals to prove their relevance, contributions, and visibility. It can become a cycle of constantly demonstrating skills, communication, and expertise to outshine others in a highly competitive landscape. The relentless pursuit of visibility creates a dynamic where comparisons become inevitable, even when the differences are as distinct as apples and oranges. We find ourselves not only competing with direct peers but also with colleagues across various divisions, all striving to be recognized and make a meaningful impact.

Career Is:

Take time to build your perspectives and focus on what you can do during your peak years of good health and availability. A career is more about experience and shaping what truly makes you happy. It’s a marathon, not a sprint - plan your journey in phases and balance your priorities.

"Growth is not measured by how far ahead you are of others, but by how deeply you understand yourself and how intentionally you shape your journey."

The Experimenter’s Mindset: Focus, Iterate, Persist!

• Productivity = Focused Time
• Ideation = Aha! Moment + Iteration
• Right Idea + Confidence = Realization
• Don’t stop experimenting just because you haven’t learned everything.
• Some fundamentals and assumptions will evolve as you learn from mistakes.
• Persistence > Time / Data / Needs / Tech Perspectives
• Success = Sticking to your idea despite constraints!

Keep Going!!!

How My Days Go These Days – AI Advisory / Consulting / Strategy

• Code for a few hours, and develop a solution in mind.
• Attend meetings to align with the vision.
• Build a structured solution approach.
• Revisit and map your domain experiences.
• Balance Build fast vs. Fail fast identify red flags.
• Add a layer of insights.
• Test your solution, and integrate different perspectives.
• Some tasks run in parallel, others are sequential.
• Even when offline, the solution keeps running in your mind.
• Every paper, resource, or discussion sparks new ideas.
• Manage time between meetings, deep thinking, reading, and coding.
• Everything adds up incrementally—failures translate into new perspectives.
• Be selective - pick and choose the right opportunities.
• 10 hours or 15 hours - doesn’t matter. Quality over hours.
• Happy to Work Remotely/Freelance - No Time for Pollution, Traffic, or Office Gossip
• Learning thrives on diverse perspectives - what you learn, experiment with, research, and intuitively connect.

Keep Learning!!!

🚀 The Experimenter’s Mindset: Focus, Iterate, Persist! 🔑

• 🚀 Productivity = 🎯 Focus Time
• 💡 Ideation = 🤯 Aha! Moment + 🔄 Iteration
• ✅ Right Idea + Confidence = 🎉 Realization
• ❌ Don’t stop experimenting just because you haven’t learned everything
• 🔄 Some fundamentals & assumptions will keep evolving as you learn from mistakes
• 🌍 Tag along with the ecosystem + 📚 Courses = 🔥 Motivation
• 💪 Persistence > ⏳ Time / 📊 Data / 🎯 Needs / 🛠️ Tech Perspectives
• 🏆 Success = Sticking to your idea despite constraints! 🔑✨

 Keep Experimenting!!!

With GenAI, does Deepwork become Quick Work?

With GenAI tools, iterations, and idea generation happen naturally at a faster pace. Design, solutioning, and iterations become much quicker.

However, there are potential long-term impacts with surface-level learning:
1️⃣  The natural trial-and-error learning process gets shortened
2️⃣   The ability to evaluate information objectively is compromised due to shorter attention spans
3️⃣   The depth of historical understanding suffers when complex topics are reduced to simplified summaries
4️⃣  Shortcuts often come with trade-offs—what we learn quickly, we may forget just as fast if depth is lacking

👉 Are we trading deep understanding and human reasoning for speed?
👉 Should we slow down and give complex problems the time and focus they deserve?

Keep Thinking!!!

Policymakers - Start Working on the GenAI Anti-Venom

Keep Thinking!!!

DeepSeek's Culture is Secret to Success

Good Read from Post

DeepSeek's Culture is Secret to Success

Key Lessons from post

• Research groups are formed based on specific goals, with no fixed hierarchies or rigid roles
• Everyone has unique experiences and comes with their own ideas
• There are no weekly reports, no internal competitions that pit employees against each other
• We need people who are extremely passionate about technology, not people who are used to using experience to find answers. Real innovation often comes from people who don't have baggage

Pick what you can connect with and Keep Going!!!

Beginning of AI Soldiers / Machines

Keep Thinking!!!

Interviews vs Perspectives

Happy to see the discussion encouraged the candidate to explore new perspectives.

The interview is not about pass or fail; it's an opportunity for meaningful discussion and the exchange of ideas.

Happy Learning

GenAI Quality: Beyond the Demo Effect

1. Demo ≠ Production Quality

• Real-world performance matters more than showcases
• Focus on consistent, reliable results

2. Benchmark-Driven Validation

• Standardized performance metrics
• Comprehensive testing scenarios
• Regular evaluation cycles

3. Strategic Speed

• Quality over frequency
• Data foundation first
• Systematic experimentation

4. Data Quality -First Architecture

• Quality data infrastructure
• Robust validation pipelines
• Continuous data improvement

5. Evidence-Based Development

• Model comparison frameworks
• Data-driven decisions
• Measurable improvements

Keep Learning!!!