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. 🙏

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!!!

Why Startups progress well with GenAI Solutions

My perspectives

•  It’s not about solving the problem instantly but gaining better clarity and progressively moving closer to the solution.
• The difference between a big company and a startup is that in a startup, you tackle such problems multiple times, discuss them repeatedly, and prototype extensively.
• In my view, it’s not just about finding the solution; it’s about engaging in discussions, gaining perspectives, prototyping, and solving iteratively. This process leads to innovative solutions rather than adopting a binary stance of zero or one.
• There’s no single way to solve these challenges. It’s about the approach: Are we gaining perspective? Are we taking a step forward? Is the problem solvable? How do we pivot and consider different angles?
• This iterative process is the essence of learning—not just limiting ourselves to Boolean states of zero and one.
• "Innovation comes from persistent iteration, not instant perfection."

Happy Learning!!!

Experimentation, Ownership, and Continuous Learning in Tech

Only certain things we learn through experimentation will provide a clear perspective. At least you have an intuition—it may work, or it may not.

Work in databases, machine learning, or deep learning requires conducting a certain number of experiments to be sure of what works and what doesn't. Of course, learning in these areas is ongoing and continuous.

Ownership is not just about having something without having done it. Ownership is more about having built a certain number of things and gathered the experience so you are able to own it because you know how to do it. When it's not a process that governs things, it's the people with experience and perspective who build better things.

Sometimes, I feel that the term "ownership" is very overloaded. Being a full-stack developer or a jack-of-all-trades requires only a certain amount of fixed time, and you cannot be good at everything. For example, knowing how to fine-tune an index or a model, understanding different types of prompts, context latency, and conducting various experiments.

I think we need to be very clear about learning. Don't just rely on certifications, working on one project, or having some perspective. It's more than just keywords, jargon, and perspectives. Undertaking a good number of experiments, embracing failures, and gaining diverse perspectives will give you the intuition to deal with ambiguity when facing the next set of problems.

#TechLeadership #ContinuousLearning #Experimentation #MachineLearning #DeepLearning #Ownership #FullStackDeveloper #DataScience #TechGrowth #ProblemSolving #Intuition #CareerDevelopment #SoftwareEngineering #SkillBuilding

Keep Going!!!

Future Robotic Farmer - Tesla Optimus

 

Optimus can now walk on highly variable ground using neural nets to control its electric limbs.

Join @Tesla if you want to work on interesting real-world AI systems. https://t.co/C8J90Age5Y

— Elon Musk (@elonmusk) December 9, 2024

Keep Exploring!!! 

Decisions vs Perspectives

 

Steve Jobs On How To Resolve Conflict:

(1) Don't try to get someone to 'buy into a decision' because you should hire people so phenomenal they tell YOU what to do. Thus, if you're trying to get them to buy into a decision, you've hired them to do what they think is right (likely… pic.twitter.com/8h26DaVr1u

— Big Brain Business (@BigBrainBizness) December 11, 2024

Keep Thinking!!!

Time-Based vs. Value-Based Pricing

• Ideas are born from experiments.
• Experiments are fueled by curiosity.
• Experiments rely on observations.
• Observations stem from a learning mindset.
• Learning is multifaceted.

Solving a problem in one hour often comes from countless hours of background work leading up to that moment.

Understand your pricing model and price wisely.

Keep Going!!!

Exploring the Tough Questions in GenAI Product Building

In all my GenAI product-building efforts, these questions consistently arise across various tasks: Data, ETL, Marketing, NER, Fashion, Design, and ESG.

• Choosing between vision models and text descriptions: When should you use vision models versus text descriptions? For the same task, OCR provides a certain level of accuracy, multimodal approaches yield different accuracy levels, and benchmarking takes time. Should a hybrid approach be considered?

• Improving model accuracy: How do you balance the use of low-cost models versus pursuing high accuracy? What are effective strategies for building products while minimizing costs?

• Catching critical hallucinations before production: How can you effectively address cases where a model misclassifies metrics in its interpretation?

• Maintaining transparent communication about AI limitations: How do you handle situations when founders ask, "Company X does this—why can't we?" especially when you lack insight into their models, architecture, or talent?

• Building trust through transparency: How can you reinforce that being open about AI limitations builds long-term trust? Developing production-grade applications requires considerable time and effort.

• Encouraging models to admit uncertainty: What are innovative ways to make models reason through their uncertainty, validate it, and improve reliability using multiple methods or ensemble approaches?

AI Advisory involves a combination of solution evaluation, in-depth research, continuous learning, hands-on coding, and assisting others in troubleshooting and resolving their issues.