In Build Mode On with TST Technology this week, our guest is Drijesh Ppatel, cybersecurity and generative AI thought leader and Software Development Manager at IBM. Hailing from a small town outside of Shirpur, Maharashtra, he is a testament to the fact that where you are from doesn't dictate where you are going in life; your dreams, talent and motivation do.
Based on 14+ years of industry experience, Drijesh provides practical advice on scaling product-building, embracing AI, handling cybersecurity issues, and juggling career development with corporate facts.
Hailing him as a mentor, Mr. Parth Makwana (PM), Founder & COO, and Mr. Daxesh Italiya, Co-founder & CTO, of TST Technology, ask him questions about AI, cybersecurity and MNCs, among other topics. This episode is filled with useful tips for students, startup founders, and career professionals.
Watch the full episodes here:
What AI Skills Must Level 3 Workers Absolutely Adopt?
Drijesh pointed out that for Level 3 workers, the executives and managers in senior positions, AI is not just a choice- it's imperative. The skills go beyond mere awareness and delve into creating firm, flexible foundations and the ability to lead their teams.
1. Basics of a Platform
- Whether Windows or Linux, workers need to know how platforms work. This foundation provides the ability to set up environments, resolve issues proficiently, and construct on stable ground.
2. Programming Basics
- Having work experience with languages like Python, Java, or .NET is a must. They are not coding knowledge but rather languages that enable professionals to link business requirements with AI solutions.
3. Cloud Technology
- AI solutions also heavily rely on the cloud to be scalable and deployed. Knowledge of cloud services allows professionals to provide enterprise-level solutions.
4. Using AI Models
- The need is not for creating models from the ground up anymore but for knowing what models are available and how to use them efficiently. The ability to transform AI tools to fit business issues is the actual distinction.
5. Problem-Solving with AI
- The ultimate ability is using AI to solve actual problems. Rather than inquiring what AI can do, experts should inquire how AI can address their particular issues.
He also warns against overengineering, sharing his experience at one hackathon project where the team created an AI clock. It functioned, but it was not needed. The moral is that simplicity may take more thinking and self-control than complexity.
Drijesh said, "It is very simple to create something complex, but very complex to create something simple."
Why Traditional Businesses Should Embrace AI?
Sharing 3 real-life examples where he helped people use AI, Drijesh was quick to show that AI is already transforming the way even the most conventional professionals operate.
- A lawyer used AI to instantaneously locate acts and case precedents.
- An architect developed precise blueprints and house plans quickly.
- A doctor assembles research effectively and discovers connections that may take weeks otherwise.
These examples illustrate that AI has less to do with replacing knowledge and more to do with amplifying it.
Where Non-Tech Founders Should Start?
The adoption starts with USP clarity (Unique Selling Proposition):
- If there's no solution available in the market → opportunity to innovate.
- If solutions already exist → start with making a niche in USP first, then create a portfolio to back it up.
So, what do you do to make innovations with AI?
- Identify what's lacking in your sector.
- Look into AI tools that provide instant solutions.
- Establish your USP and build around it.
Using AI is not daunting if you just focus on the things that are truly useful and relevant to you.
Read our guides on using AI and tech to grow your business:
- The Complete Founder's Guide to Digital Transformation
- How to Build MVP with AI: The Complete Guide for Small Organisations
How Product Owners Should Respond to Data Breaches?
Drijesh stressed that cybersecurity isn't just an IT issue but a survival issue for businesses. When there are data breaches, product owners have both regulatory and reputational penalties.
For listed companies, the initial legal requirement is to notify the authorities of the breach. The Digital Personal Data Protection Act (DPDPA) does not have blanket penalties. They vary based on the sensitivity and value of the leaked data, from lakhs to crores.
He also reminded us that most breaches can be avoided with smarter ways of doing business:
- Reduce data collection. Collect only what is absolutely required.
- Encrypt by default. Presume all data is sensitive.
- Respect data boundaries. Data and servers should stay in approved geographies.
What happens, though, is that most companies build a product first and then work to secure it. Drijesh recommends starting to put in security measures from the design phase itself. Make security part of the product from day one.
Failing most times, Drijesh said, is due to human oversight: clicking on insecure extensions, neglecting app origin, or ignoring server locations. Product teams must be on their toes at each stage.
If there is a breach, panic does not help. The best reaction is organised:
- Breathe slowly and stay calm.
- Shut the infected sectors down to prevent the spread across the whole product.
- Notify the authorities in a timely manner.
For individuals, exposure checkers are available. Tools such as Have I Been Pwned enable users to know if their email address or credentials were involved in previous leaks.
The message was unmistakable: data responsibility is something a product owner has a responsibility for, not an afterthought. Carelessness not only pardons fines but also destroys the trust that products are made upon.
Digital Security, Fraud, and Prevention
Frauds are an everyday reality now, with lakhs and even crores being lost. Fraudsters do not necessarily hack into systems; they hack human psychology: exposing too much information on social media, entering lucky draws, or exposing data in public records. Using this information, they resort to trickery in the form of AI voice cloning and tactics of urgency to coerce victims into making hasty mistakes.
Prevention and awareness are the solutions:
- Double-verify money requests through known contacts prior to actioning.
- Don't respond to unfamiliar calls instantly since robots will store your voice to copy you.
- Block out unfamiliar emails. Spam responses validate that your email is active, too.
- Have dedicated contact information for public activities as opposed to private finances.
- Search for data breaches via online tools to know if your email has leaked.
Being alert and embracing simple practices can protect you from all but the most sophisticated scams. Constant awareness is your best protection.
Startup vs. MNC Mindset towards AI Adoption
Startups and multinationals have vastly different approaches to adopting AI, and each mindset has its own strengths and compromises. Drijesh noted that speed and stability frequently make the divide.
Aspect | Startups: Fast & Risk-Taking | MNCs: Stable & Structured |
| AI Adoption Speed | Quick experimentation and rapid pivots | Slower rollout due to compliance and approvals |
| Stability | Agile but often unstable processes | Highly stable with mature workflows |
| Scalability | Serves hundreds or thousands of users | Designed to handle millions of users |
| Growth | Faster growth, but volatile | Steady growth with accountability |
| Accountability | Limited, founders take big risks | Strong accountability, tied to governance |
| Culture | Innovation-driven, risk-tolerant | Process-driven, risk-averse |
Both methodologies are ultimately correct depending on the situation. Startups innovate with velocity, and MNCs impact with scale and stability. The healthiest ecosystems tend to form when the two thought patterns learn from one another, balancing agility with accountability.
How MNCs Tackle Product Research and GTM?
In big companies, product development is rarely linear. Drijesh pointed out how MNCs depend on methodical processes to balance creativity, compliance, and scalability so that products don't just get developed but thrive in highly regulated, competitive markets.
2 Common Methodologies For MNC Product Planning
Bottom-Up: Concepts are developed from ground-level teams: engineers, product managers, or innovators who identify opportunities. These concepts go through debate, in-depth study, and a proposal phase. It is only after the concept is defined that it flows through the next layers: compliance and legal verification, budget sanctioning, and ensuring alignment with current systems. This method fosters innovation internally while ensuring each step is overseen.
Top-Down: In this case, leadership begins with wide objectives, strategic priorities, or market requirements. Teams reverse-engineer the product from these specifications, creating solutions that are aligned with compliance, budget, and company-wide standards. Less exploratory, yet ensuring alignment with business strategy and minimizing risk.
The two approaches exist side by side in MNCs. The bottom-up approach is innovative, while the top-down approach guarantees that innovation aligns with long-term vision and compliance frameworks.
What is the Go-To-Market (GTM) Strategy For MNCs?
1. Compliance Checks: The products need to be compliant with industry rules and data protection norms prior to launch. Skipping this part is not feasible in an MNC context where penalties as well as reputational damage are significant.
2. Sales-Audience Fit: Instead of relying on one global playbook, MNCs tailor their sales and marketing approaches for every location, taking into consideration cultural differences, local laws, and customer expectations.
This structured blend of responsible product research and localised GTM execution allows MNCs to innovate at scale while safeguarding trust and ensuring adoption across diverse markets.
How Can You Become an Official Vendor for an MNC?
Breaking into the vendor ecosystem of a multinational corporation is no small feat. As Drijesh explained, the process is designed to filter for reliability, security, and scalability, ensuring that only partners who can deliver at enterprise standards are approved.
Step 1: Compliance Certification
✅ Get certified like ISO and other industry standards.
✅ Show compliance with international standards.
➡️ This step confirms credibility and is often the least that needs to be done to be looked at.
Step 2: Security & Legal Preparedness
✅ Demonstrate robust data protection and infrastructure security.
✅ Have contracts, intellectual property, and local and international legal compliance in place.
➡️ This creates trust and reduces regulatory and legal hazards.
Step 3: Technical Assessment
✅ Have your product or service demonstrate scalability and reliability.
✅ Be able to integrate with existing enterprise systems seamlessly.
✅ Offer sustainable support functions for long-term application.
➡️ MNCs don't only look at your product but also at your capacity to perform consistently at scale.
Step 4: Financial Negotiations
✅ Offer clear pricing and negotiable terms.
✅ Emphasize the harmony between price and long-term value.
➡️ Even as cost is a consideration, MNCs focus more on reliability, compliance, and technical prowess than on price.
The process is stringent, but it serves to guarantee that once approved as a vendor, they are entitled to long-term, high-value business within the MNC's global ecosystem.
Preventing Idea Theft: How Patents Shield Innovators
There is also a real concern that MNCs may steal ideas while being presented by innovators. For this, Drijesh advises that the process of patent filing should be started so there is legal proof of whose idea it was first, and no conflict or theft can occur. He also encourages people to file patents on their inventions regularly and urges companies to aid their employees in the process. Founders should see IP as an investment. Though returns may take 5–10 years, the payoff provides both revenue and legal security for the future.
Mentorship, Intrapreneurship, and the Next Generation
The expert's enthusiasm for mentoring comes from his own early days of working without networks or referrals. Now, he serves as a bridge for others, assisting individuals to hone ideas, establish connections, and even secure employment as his community gatherings have already brokered actual opportunities for some attendees.
Though entrepreneurial by nature, he hasn’t started a business of his own. Instead, he practices intrapreneurship, which means he’s running large-scale products inside IBM with significant autonomy and impact. With trust from leadership and the freedom to pick his teams, he enjoys the ownership of a startup while leveraging the resources of a large organization.
He also gives point-blank advice to students: excuses no longer apply. With access to free material such as YouTube, Udemy, Coursera, and documentation, anyone can pick up new skills in a short while. With dedication, one can learn Python within 15–20 days. The blueprint is straightforward: learn one platform, one language, and one cloud technology to create robust fundamentals.
But what about work-life balance?
It’s natural to wonder how Drijesh has time for all of these. Regarding work-life balance, he is of the opinion that no such thing exists; only life does. Stress often stems from greed: pursuing luxuries instead of focusing on essentials.
It is possible to work hard and live peacefully by setting boundaries, delegating, and occasionally disconnecting. For example, during vacations, he logs off at 6 PM while spending time in his hometown, spending time with his family, which feels really peaceful to him.
In India, the tech culture is also shifting from a Project Mindset (task completion) to a Product Mindset (outcome-driven results). The question is no longer “What did I finish?” but “What outcome did this create?”
Through his mentoring, intrapreneurship, and guidance, he demonstrates that success is not just about oneself but also about empowering the next generation to succeed.
Conclusion
AI, cybersecurity, and product strategy building are a must for professionals and companies looking to get ahead. As Drijesh Ppatel pointed out in this episode, becoming an AI master, learning about data responsibility, and tapping into the startup as well as MNC mindset can provide you with a winning advantage.
If you'd like to delve into how these lessons can be applied directly to your career or business, schedule a FREE Consultation Call with TST Technology here.
We'd also love to hear your input: leave a like, comment your thoughts, and recommend any guests or topics you'd like us to discuss in upcoming episodes. Your input helps make Build Mode On even more valuable to our community.
Until next time with a wonderful guest!
