Leading Privado.ai as Founder and CTO, our mission is to embed privacy into the DNA of software engineering. Overseeing the development of Privado, our open-source tool, we enable engineers to manage sensitive data with unmatched precision. This endeavor reflects our core value of making privacy a fundamental aspect of technology.

Prashant Mahajan

Privacy teams should be worried. This is exactly how the same mistake happens twice.

Crunchyroll already paid $16M over privacy allegations tied to user viewing data.

Now it is being sued again. Different vendor, same underlying problem: a company allegedly let third-party tooling access what people were watching, tied to who they were.

That is not a policy failure first.
It is a systems failure.

From the outside, this looks like “data sharing.”
Inside the product, it usually looks routine.

An SDK gets added for engagement.
Events start flowing. User identifiers get attached.
Viewing activity becomes a usable signal for someone outside your system.

That is how legal risk gets created quietly.

This is the part many privacy programs still miss:
- The contract can look clean
- The policy can sound right
- The consent language can be reviewed

But if the system is still sending user-level viewing events to a third party, none of that matters much.

Legal teams need to ask harder questions:
1. What events are actually leaving the app?
2. What identifiers go with them?
3. Can a vendor tie content consumption back to a person?
4. Who verified the live data flow after the tool was implemented?

This is why privacy work cannot stop at notices, reviews, and vendor paperwork.

Policies describe intent.
Systems reveal reality.

If your privacy team cannot see what product telemetry is doing in production, you are relying on assumptions, not controls.

How many companies that settled privacy claims have actually fixed the underlying data flow?

#Privacy #DataPrivacy #Compliance #Legal #Law

Privacy Engineering Infrastructure Leader | Founder & CTO, Privado.ai | Built $100M+ Scale Systems | Defining AI-Driven Privacy Automation

This week California regulators fined a company most people wouldn’t expect in a privacy case.

A high school sports ticketing platform.

Students used it to buy tickets for football games, prom, and school events.

But behind the scenes, the platform was running tracking technologies for targeted advertising.

And here was the catch.

You couldn’t view your ticket without clicking “agree” to tracking.

No real opt-out or alternative path.

So attending a school event effectively meant agreeing to ad-tech tracking.

Regulators fined the company $1.1M and forced changes to its practices.

What stands out to me is the architecture behind this.

A ticketing system quietly became part of an advertising infrastructure.

The core product and the tracking stack were intertwined.

This happens more often than teams realize.

A simple product integrates analytics, marketing tools, or ad-tech.

Over time those integrations start shaping how the product works.

And suddenly core functionality depends on tracking.

That’s where privacy usually breaks... in the system design.

If someone can’t use your product without being tracked, it’s worth asking:
Was tracking ever meant to be part of the product experience?

#Privacy #Engineering #DataPrivacy #CCPA #Legal

Over the last few months, I kept walking out of customer conversations with the same feeling in my head.

Privacy teams are carrying way too much.

Not because they are not good at what they do. Not because they are not working hard. Actually the opposite. The people I speak with are thoughtful, sharp, and deeply serious about the work. But the day to day of privacy work still feels heavier than it should.

One customer told us their setup was still very manual and dependent on annual refreshes.

Another said something that really stayed with me: 
“I don’t need a person to fill out a spreadsheet anymore.”

Another put it even more plainly:
“We need the result. We need the answer.”

And another said what I think a lot of teams feel, even if they do not always say it out loud: “We don’t know what we don’t know.”

That is the part I kept coming back to.

None of these people were asking for something flashy. Nobody was asking for another dashboard, another workflow, or another pile of features to learn.

They were asking for something much simpler.

Clarity.

A better way to understand what is happening across their digital environment. What changed. What matters. What needs attention. What they can trust.

That is why we announced Wren today.

Wren did not begin as a vague idea about AI. It came from a much more practical place. We kept hearing the same pain, from different companies, in different words, and it became hard to ignore.

Privacy teams are working in environments that keep moving. Websites change. Apps change. Cookies change. Configurations drift. New tools show up. Old assumptions stop being true. But too much of the work still depends on manual effort, fragmented visibility, and tools that make you dig for the answer instead of helping you get there.

So even when teams have scans, inventories, workflows, and documentation, the real questions are still there:
- What changed?
- Why was this flagged?
- Is this actually a risk?
- Can I trust this result?
- What do I take to legal?
- What do I do next?

That gap is exactly what led us to build Wren.

We want it to take on the investigative work privacy teams should not have to do manually anymore. 

To spot when something new needs review. 
To help trigger the right assessment. 
To pull in the right docs, scans, contracts, and context. 
To help generate the assessment with evidence, not guesswork. 
And to help teams track the risks that actually need action.

For us, this announcement is not about launching something new just because we can. It is about taking a problem we kept hearing again and again and deciding to build for it properly.

We want privacy teams to investigate faster. 
We want them to get to the “so what” without all the chasing. 
We want them to feel more clear, more confident, and a little less buried in manual work.

A part of why we are building Wren is very simple: 
We want privacy pros to smile more

Check the announcement link in the comment.

When the Meta AI glasses lawsuit came out, I did not just see a product story.
I saw a privacy operations story.

Because this is what keeps happening. Legal teams document one version of data use. The system quietly evolves into another.

A feature gets shipped. A vendor gets added. A review workflow appears.

Data starts moving in ways no one properly mapped. And by the time anyone notices, the documentation is already out of date.

That is why manual privacy processes are struggling in 2026.

They depend on people explaining what they think the system does. But privacy risk does not live in what people think.

It lives in what the system is actually doing. That is the gap.

Spreadsheets, policy reviews, screenshots, and questionnaires still have a role.  

But they are not enough for environments where products change constantly and AI introduces new data flows faster than governance teams can keep up.

Automation matters because it gives privacy teams something manual processes cannot.

Actual visibility. Not more opinions or better wording.

Evidence.

For legal and compliance teams, that changes the conversation from:
what was approved
what was documented
what teams said

to:
what is running
where data is going
which vendors are involved
what changed since the last review

That is a much stronger foundation for privacy accountability.

In 2026, the problem is not that teams do not have privacy processes. The problem is that most of those processes still cannot keep up with the systems they are supposed to govern.

How are you handling that gap today between documented privacy controls and actual system behavior?

#privacy #data #AI #automation

40 million Americans are asking AI about their health.

Most assume HIPAA follows that conversation.

It doesn’t.

When a hospital uses an AI tool, there’s a Business Associate Agreement. That creates shared legal responsibility. Access is scoped. Logs exist. Controls are negotiated. OCR can enforce.

When a consumer opens ChatGPT Health or Claude and uploads lab results, that structure disappears.

There is no covered entity. No BAA. No HIPAA enforcement mechanism.

The protection comes from product design and terms of service. Not healthcare regulation.

From a systems perspective, this is a completely different environment.

Enterprise deployments sit inside defined trust boundaries. Identity controls. Access segmentation. Audit logs. Contractual limits.

Consumer tools are multi-tenant platforms. Even with encryption and isolation, governance is standardized. Not negotiated.

Legal assumption. Health data equals HIPAA.

System reality. Regulation attaches to relationships, not data types.

That gap is where risk lives.

If you lead privacy, consider this:
- Are employees pasting patient data into consumer AI tools?
- Do your policies clearly separate enterprise AI from personal experimentation?
- Can you technically detect where health data is flowing?

If regulators asked, could you evidence the difference?

None of this makes consumer AI unsafe.

But it does mean the regulatory posture is different. And most organisations are not modelling that difference clearly.

AI in healthcare now operates in two silos.

If your governance framework doesn’t reflect that, you’re relying on assumption.

Can you actually prove which environment your data is in?

#dataprivacy #HIPAA #law #AI

GDPR fines have now crossed €5.6B in publicly known enforcement.

Most people will read that as a regulator story. I think it is really an evidence story.

The hard part is no longer writing the policy. The hard part is proving what actually happened inside the system.

That is where most privacy programs break.

On paper, the company has a notice, a retention policy, a RoPA, DPAs, and internal controls.

In production, the reality is usually different.

Data fields get reused. Events change names. New SDKs get pushed live.
Vendors receive data nobody reviewed.

AI features get added on top of existing systems without anyone fully mapping the downstream flow.

Legal teams are still expected to stand behind disclosures and controls.

But those claims are often based on interviews, screenshots, and documentation created at a point in time.

Systems do not work that way. They change every week. Sometimes every day.

So when enforcement happens, the real question is not, “Do you have a policy?”

It is, “Can you show evidence of what your systems actually did with personal data?”

That changes a lot.

Documentation shows intent... system evidence shows reality... privacy reviews without engineering visibility create blind spots and accountability without technical proof is mostly trust

This is the gap legal and privacy teams need to pay attention to.

The risk is not just non-compliance. The risk is defending a position that was true when it was written, but false in the live system.

Privacy programs need to move closer to engineering reality.

Not because lawyers need to become engineers. Because legal accountability now depends on technical evidence.

How is your team validating what production systems are actually doing with personal data today, beyond documentation?

#privacy #GDPR

I’ve built systems at scale. That’s exactly why I don’t believe manual data mapping works.

I was talking recently with a data governance leader at a large media publisher.

Their process still depended on manual updates, annual check-ins with system owners, and lineage they didn’t really trust.

Honestly, that’s not surprising.

The problem is bigger than process.

Most privacy teams are still being asked to understand data flow through surveys, spreadsheets, and interviews.

But production systems do not wait for annual refreshes.

Tags change. Vendors change. Pipelines change. New use cases appear. Data starts moving in ways nobody captures fast enough.

So the map gets updated.

The system has already moved on.

That’s the gap privacy teams are dealing with now.

Not a policy gap. A visibility gap.

My view is simple:

Policies describe intent. Systems reveal reality.

If your data map depends on manual refreshes, it’s probably already outdated.

How are teams closing that gap today?

#privacy #legal #law #data

I am a Global Award Winning Tech-Design Leader 2025 with more than twenty years of experience building user-centric digital products and leading UI, UX, and web engineering for OTT, SaaS, AdTech, Media, and E-Commerce. I have worked with cross-functional teams across sixteen plus countries, helping organisations scale platforms, improve performance, and deliver experiences that users trust.

I currently contribute as a Strategic Technical Advisor at UIXPERTS LABS on an equity-based engagement. At the same time, I am open to a full-time leadership role where I can drive strategy, engineering excellence, and digital transformation with clear business outcomes.

A major strength I bring is my combination of Certified ISO 13485 Auditor capability with HFI-backed Usability, UX, and UI Engineering expertise. This blend is rare. It helps medical device and healthcare teams meet ISO 13485 requirements while creating safer, intuitive, and human-centred products. If you are in medical devices or supply chain, I can support you in aligning compliance with practical usability.

My focus areas include:
• ISO 13485 auditing with usability engineering perspective
• AI Consulting – pursuing the Certified Artificial Intelligence Consultant (CAIC™) track
• Digital experience, web strategy, and scalable architecture
• Leadership and mentoring for high-performing teams
• Product and technology alignment for faster delivery
• Community building through JavaScripters, IxDF India, and UXUI Summit

Some results I have delivered:
✔ Increased OTT engagement by twenty five percent using scalable design systems
✔ Improved delivery speed by thirty to forty percent with agile and cloud-first practices
✔ Enabled seamless OTT experiences across sixteen plus global markets

I am open to roles like Technical Director, Head of Web, Director of Digital Experience, VP Engineering, and CTO. I bring clarity, stability, and the ability to turn complex challenges into structured, high-quality outcomes.

If your organisation needs a leader who understands design, engineering, compliance, and people, I can create meaningful impact from day one.

Let us connect: https://linktr.ee/shaikhimran786

Imran Shaikh

🎊 Celebrating my new certification! 🎊 

I have successfully completed the Web Design for Usability course from the IxDF - Interaction Design Foundation.

This journey helped me sharpen and structure my thinking around usability at a deeper level. I strengthened my ability to:

• Design web experiences around clear user goals, making pages logical and easy to understand
• Apply user-centered design principles to reduce friction and enable smooth task completion
• Build intuitive navigation systems that help users stay oriented and find information quickly
• Integrate foundational accessibility practices to support users with diverse abilities
• Compare and evaluate design alternatives based on clarity, effectiveness, and ease of use
• Use evidence-based usability methods to identify issues and continuously refine digital experiences

Usability is not decoration. It is responsibility. When design becomes effortless for users, real impact begins.

Grateful for continuous learning and growth in the craft of meaningful digital experiences.

You can view the certificate here:
https://lnkd.in/dkHYfFUJ

#IxDF #IxDFINDIA #IXDFPune #UIUX #UXUI #Usability

🏆 Global Award-Winning Tech & UX Leader | Director – AI Technology @ Lemma | OTT, Media, CTV, AdTech & DOOH | Building Scalable Products, Teams & Communities

No alternative text description for this image

𝐆𝐫𝐚𝐭𝐞𝐟𝐮𝐥 𝐭𝐨 𝐑𝐞𝐜𝐞𝐢𝐯𝐞 𝐭𝐡𝐞 𝐈𝐱𝐃𝐅 “𝐎𝐮𝐭𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐋𝐞𝐚𝐫𝐧𝐞𝐫 𝐀𝐰𝐚𝐫𝐝” 🎓

I’m happy to share that I have received the “𝐎𝐮𝐭𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐋𝐞𝐚𝐫𝐧𝐞𝐫 𝐀𝐰𝐚𝐫𝐝” from the Interaction Design Foundation.

This recognition is awarded for successfully completing 15 courses on the IxDF platform. The journey has been deeply enriching, helping me strengthen my understanding of user experience, interaction design, usability, accessibility, and human-centred design practices.

Continuous learning has always been an important part of my professional journey. Platforms like IxDF - Interaction Design Foundation make it possible to stay updated with global design thinking and apply these insights to real-world product and technology challenges.

A sincere thank you to the IxDF - Interaction Design Foundation community and instructors for creating such valuable learning opportunities.

Learning never stops. Looking forward to continuing this journey and contributing back to the design community.

You can view the award here:
https://lnkd.in/dPMKbKz2

#IxDF #IxDFINDIA #𝐀𝐰𝐚𝐫𝐝 #Achievement #IndiaTalent #Job #Reward

𝐒𝐨𝐦𝐞𝐭𝐢𝐦𝐞𝐬 𝐭𝐡𝐞 𝐛𝐞𝐬𝐭 𝐢𝐝𝐞𝐚𝐬 𝐝𝐨𝐧’𝐭 𝐜𝐨𝐦𝐞 𝐟𝐫𝐨𝐦 𝐦𝐞𝐞𝐭𝐢𝐧𝐠𝐬, 𝐩𝐫𝐞𝐬𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧𝐬, 𝐨𝐫 𝐬𝐞𝐫𝐢𝐨𝐮𝐬 𝐝𝐢𝐬𝐜𝐮𝐬𝐬𝐢𝐨𝐧𝐬.

They appear when people play, experiment, and explore ideas together.

That’s exactly the spirit behind #play14 Mumbai, and I am excited to be one of the hosts for this gathering.

𝐅𝐨𝐫 2.5 𝐝𝐚𝐲𝐬, we will bring together curious minds to explore:

🎲 playful creativity
🎲 storytelling through games
🎲 new facilitation methods
🎲 collaborative learning experiences

Think of it as a chance to let your inner child come alive again while learning something meaningful.

You will meet an amazing mix of people including designers, tech leaders, facilitators, mentors, HR professionals, educators, game designers, founders, community builders, and creators.

If you are part of communities like IxDF - Interaction Design Foundation, JavaScripters Community, product, design, or tech ecosystems, this experience can open new ways of thinking and connecting.

More importantly, these 2.5 days often create friendships, collaborations, and knowledge exchange that continue long after the event ends.

📅 Event Dates
27 March (6 PM) – 29 March (7 PM)
Mumbai

Seats are intentionally limited to keep the experience interactive.

Register here:
https://lnkd.in/dDZ3iNZ4

If you have any practical questions about the event, feel free to reach out:
india@play14.org

Hope to see some familiar faces from the design and tech community there.

#play14 INDIA
#Play14 #Play14Mumbai  #LearningThroughPlay
#DesignCommunity #IxDF #JavaScripters #CreativeLearning
#UXDesign #ProductDesign #DesignThinking #TechCommunity #MumbaiEvents #CommunityLearning 🎲

𝐌𝐞𝐞𝐭 𝐭𝐡𝐞 𝐇𝐨𝐬𝐭𝐬 – Imran Shaikh

🎲 Meet the Hosts – #play14 Mumbai

Innovation does not always start in meeting rooms.

Sometimes it starts when people gather, experiment, and play with ideas.

Meet Imran Shaikh, a Global Award Winner Technology Leader and Community Builder who has spent 20+ years building tech teams, products ,tech & design communities.

He believes playful exploration often leads to unexpected insights and creative breakthroughs.

As Imran Shaikh says:
“𝐼𝑛𝑛𝑜𝑣𝑎𝑡𝑖𝑜𝑛 𝑏𝑒𝑔𝑖𝑛𝑠 𝑡𝘩𝑒 𝑚𝑜𝑚𝑒𝑛𝑡 𝑤𝑒 𝑠𝑡𝑜𝑝 𝑜𝑣𝑒𝑟𝑡𝘩𝑖𝑛𝑘𝑖𝑛𝑔 𝑎𝑛𝑑 𝑠𝑡𝑎𝑟𝑡 𝑡𝑜 𝑝𝑙𝑎𝑦.”

#play14 Mumbai is exactly about that.

📩 Exclusive host referral discounts available. DM to get your coupon code.

Join us at #play14 Mumbai
https://lnkd.in/d4Y2Eknw

#play14 INDIA
#Play14 #Play14Mumbai #Innovation #CommunityBuilding #CreativeThinking

🚀 Excited to Host #play14 Mumbai 1st Edition!

For the first time ever, the global #play14 unconference is coming to Mumbai, and I am happy to be part of the volunteer host team bringing this amazing experience to India’s creative and tech community.

#Play14 is not a typical conference.
It is a playful learning space where designers, technologists, educators, innovators, and curious minds come together to explore creativity through play.

💡 “𝑆𝑜𝑚𝑒 𝑜𝘧 𝑡𝘩𝑒 𝑏𝑒𝑠𝑡 𝑖𝑑𝑒𝑎𝑠 𝑒𝑚𝑒𝑟𝑔𝑒 𝑤𝘩𝑒𝑛 𝑤𝑒 𝑎𝑙𝑙𝑜𝑤 𝑜𝑢𝑟𝑠𝑒𝑙𝑣𝑒𝑠 𝑡𝑜 𝑝𝑙𝑎𝑦, 𝑒𝑥𝑝𝑒𝑟𝑖𝑚𝑒𝑛𝑡, 𝑎𝑛𝑑 𝑡𝘩𝑖𝑛𝑘 𝘧𝑟𝑒𝑒𝑙𝑦.”

This event is about:
• Creative thinking through play
• Human centred design conversations
• Meaningful networking with amazing people
• Learning in a fun and open environment

📍 Location: IndiQube Rockfort, Andheri East, Mumbai
📅 Dates: 27 – 29 March 2026

⚡ Seats are limited and registrations are filling fast.

If you are someone who believes in learning differently, collaborating openly, and exploring creativity, you should definitely join us.

✨ “𝐼𝑛𝑛𝑜𝑣𝑎𝑡𝑖𝑜𝑛 𝑏𝑒𝑔𝑖𝑛𝑠 𝑤𝘩𝑒𝑟𝑒 𝑐𝑢𝑟𝑖𝑜𝑠𝑖𝑡𝑦 𝑚𝑒𝑒𝑡𝑠 𝑝𝑙𝑎𝑦.”

I would love to see many friends and professionals from my LinkedIn network joining us for this special edition.

👉 Register here before seats are full:
https://lnkd.in/dDZ3iNZ4

Let’s come together and create an unforgettable #play14 INDIA Mumbai experience.

Host Team: Bharti Maru, Imran Shaikh, Ganesh Dalvi, CPF I M, Vaishali Naik, Pankkti Shhah, Laxman Murugappan, Wan Fadzil Adlan Wan Sidik


#Play14 #Play14Mumbai #DesignCommunity #CreativeLearning #Innovation #UX #ProductDesign #TechCommunity #Networking #LearningThroughPlay #ixdf #ixdfindia #javascripters #HR #HRNetwork #Facilitator #IAf

🚀 Announcing #play14 Mumbai – The Power of Play Comes to Mumbai!

For the first time ever, #play14 is coming to Mumbai, bringing together curious minds, designers, technologists, educators, facilitators, and playful thinkers for a truly unique experience.

📅 27–29 March 2026
📍 IndiQube Rockfort, Andheri East, Mumbai

#play14 is a global gathering of people who believe that play is not just fun, it is a powerful way to learn, collaborate, innovate, and unlock creativity. Across the world, #play14 events have created spaces where professionals step away from routine thinking and rediscover the joy of exploration and experimentation.

This Mumbai edition will be three days of playful learning, meaningful conversations, and hands-on activities designed to spark ideas and build new connections.

💡 What to expect
•⁠ ⁠Interactive play sessions and workshops
•⁠ ⁠Inspiring conversations with creative thinkers
•⁠ ⁠Networking with designers, innovators, and community builders
•⁠ ⁠A safe space to experiment, learn, and collaborate

✨ A simple thought we believe in:
“The opposite of play is not work. The opposite of play is boredom.”
When people play together, they learn faster, think better, and create stronger communities.

Seats are limited and registrations are filling quickly.

🎟 𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐧𝐨𝐰 𝐚𝐧𝐝 𝐛𝐞 𝐩𝐚𝐫𝐭 𝐨𝐟 𝐭𝐡𝐞 𝐟𝐢𝐫𝐬𝐭 𝐏𝐥𝐚𝐲14 𝐌𝐮𝐦𝐛𝐚𝐢 𝐞𝐝𝐢𝐭𝐢𝐨𝐧
👉 https://lnkd.in/d4Y2Eknw

𝐄𝐚𝐫𝐥𝐲 𝐛𝐢𝐫𝐝 𝐜𝐥𝐨𝐬𝐢𝐧𝐠 𝐭𝐨𝐦𝐨𝐫𝐫𝐨𝐰

If you believe in learning through curiosity, creativity, and collaboration, this event is for you.

Inviting all #play14 INDIA players to register and join us for this exciting gathering in Mumbai.

Let’s bring the spirit of play to Mumbai now 🎊 . 🎲


#Play14 #Play14Mumbai #PlayfulLearning #CreativeCommunities #DesignThinking #Innovation #LearningThroughPlay #CommunityBuilding #MumbaiEvents

𝐌𝐨𝐬𝐭 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐬 𝐀𝐫𝐞 𝐔𝐬𝐢𝐧𝐠 𝐀𝐈 𝐓𝐨𝐨𝐥𝐬 𝐭𝐡𝐞 𝐖𝐫𝐨𝐧𝐠 𝐖𝐚𝐲.

Not because they lack intelligence.

But because they use AI like a search engine instead of a thinking partner.

After months of experimenting with different AI tools and agents in engineering and design workflows, I realised that the real productivity jump comes from how you structure the interaction.

Here is a simple AI workflow that actually works.

𝐒𝐭𝐞𝐩 1: 𝐃𝐞𝐟𝐢𝐧𝐞 𝐭𝐡𝐞 𝐏𝐫𝐨𝐛𝐥𝐞𝐦 𝐂𝐥𝐞𝐚𝐫𝐥𝐲

Before prompting, write down:

• the problem
• the goal
• the constraints

If the problem is vague, the AI response will also be vague.

Clear thinking produces better prompts.

𝐒𝐭𝐞𝐩 2: 𝐀𝐬𝐤 𝐟𝐨𝐫 𝐌𝐮𝐥𝐭𝐢𝐩𝐥𝐞 𝐀𝐩𝐩𝐫𝐨𝐚𝐜𝐡𝐞𝐬

Instead of asking for a single answer, ask:

“Provide 3–5 different approaches and explain tradeoffs.”

This helps you explore possibilities quickly.

𝐒𝐭𝐞𝐩 3: 𝐁𝐫𝐞𝐚𝐤 𝐃𝐨𝐰𝐧 𝐭𝐡𝐞 𝐏𝐫𝐨𝐛𝐥𝐞𝐦

Large problems confuse AI.

Better approach:

Ask AI to break the problem into smaller components first.

This works extremely well for:

• system architecture
• UX workflows
• product strategy

𝐒𝐭𝐞𝐩 4: 𝐄𝐯𝐚𝐥𝐮𝐚𝐭𝐞 𝐭𝐡𝐞 𝐎𝐩𝐭𝐢𝐨𝐧𝐬

Ask AI to compare solutions.

Example:

“Compare these options based on scalability, cost, and implementation complexity.”

This helps in decision making.

𝐒𝐭𝐞𝐩 5: 𝐑𝐞𝐟𝐢𝐧𝐞 𝐭𝐡𝐞 𝐁𝐞𝐬𝐭 𝐎𝐩𝐭𝐢𝐨𝐧

Once you choose an approach, ask AI to refine it.

Example:

“Improve this architecture for better performance and reliability.”

Iteration produces far better results.

𝐒𝐭𝐞𝐩 6: 𝐀𝐬𝐤 𝐟𝐨𝐫 𝐑𝐢𝐬𝐤𝐬

A very useful trick:

“Identify weaknesses or risks in this solution.”

This helps uncover blind spots.

𝐒𝐭𝐞𝐩 7: 𝐂𝐨𝐧𝐯𝐞𝐫𝐭 𝐭𝐨 𝐀𝐜𝐭𝐢𝐨𝐧𝐚𝐛𝐥𝐞 𝐎𝐮𝐭𝐩𝐮𝐭

Finally ask for:

• implementation steps
• technical checklist
• decision summary

Now the output becomes practical.

My biggest learning

The difference between average AI usage and powerful AI usage is rarely the tool.

It is how clearly you structure the thinking process.

Professionals who learn to collaborate with AI effectively will move much faster in the coming years.

Curious to hear from engineers, designers, and product leaders here.

How are you integrating AI into your daily workflow? 

#ArtificialIntelligence #PromptEngineering #AIWorkflow #AIForEngineers #AIForDesigners #GenerativeAI #AIProductivity #FutureOfWork #EngineeringLeadership #DesignLeadership #TechLeadership #AIInnovation 🚀

Recently, one of my team member asked me, “Which AI tool should we use for our daily UI and UX work?”  

It sounded like a simple question, but it made me pause. Because today the real challenge is not access to AI. The challenge is choosing wisely.

Over the last few months, I have been personally testing multiple AI tools across design and development workflows. Not just from a curiosity point of view, but from a leadership responsibility. As Director of Technology, every decision we make impacts cost, productivity, and delivery speed.

What I realised is this. The smartest teams are not the ones using the most AI tools. They are the ones using the right tools for the right problems.

Some simple cost saving strategies that are working for us:  
First, start with real pain points. Automate repetitive tasks in research, wireframing, content, and frontend coding before experimenting with everything.  
Second, avoid overlapping subscriptions. Many tools do similar work. Standardising the stack saves both money and confusion.  
Third, measure output quality and time to final outcome. Speed without accuracy increases rework and hidden cost.  
Fourth, train teams on workflows and prompts. The real value comes from how you use AI, not from how many tools you buy.  
Finally, review and optimise regularly. If a tool is not improving productivity or user experience, it should not stay.

AI should simplify our work, reduce cost, and improve user experience. Otherwise, it is just another expense.

I am curious to know how leaders and teams are balancing cost, performance, and real impact while adopting AI in design and engineering.

#AI #UXDesign #UIDesign #DesignLeadership #TechnologyLeadership #ProductDesign #Innovation #CostOptimization #DigitalTransformation

𝐒𝐭𝐚𝐫𝐭 𝐘𝐨𝐮𝐫 𝐀𝐈 𝐏𝐨𝐰𝐞𝐫𝐞𝐝 𝐇𝐮𝐦𝐚𝐧-𝐂𝐞𝐧𝐭𝐞𝐫𝐞𝐝 𝐔𝐈 𝐃𝐞𝐬𝐢𝐠𝐧 𝐂𝐚𝐫𝐞𝐞𝐫 𝐓𝐨𝐝𝐚𝐲

View company: IxDF - The Interaction Design Foundation

You know that feeling when you see an app and instantly know what's wrong with the layout? 

When you can tell exactly why one interface feels effortless and another feels cluttered?

That's not just taste, it's visual perception.

And companies will pay $95K+ for it

The AI-Powered Human-Centered UI Design career program teaches you to use AI for generating options so you can focus on what you do best: Create visual hierarchy that guides attention, choose colors that build trust, and design interfaces that feel effortless and intuitive to people

What you'll do:
→ Master AI tools that speed up your design process 10x
→ Build 3-10 portfolio pieces
→ Develop visual design, typography, and accessibility at your own pace

No design experience needed. Just bring your eye for what looks right and curiosity about what makes interfaces work.

Your visual sense is valuable. Let's turn it into a career designing interfaces people love.

Ready to design a life you love?

https://lnkd.in/ekqpfBpQ

#UXCareer #IxDF #BreakIntoTech #LearnUX #LearnFromTheBest #DesignALifeYouLove

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The Battle

Prashant Mahajan

Imran Shaikh

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

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