JaneethReddy Alle

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[Rahul Mathur @Rahul_J_Mathur]

This data suggests that the odds are stacked against you - there is a 2% probability of hitting the jackpot when you start a consumer brand in India.

If your goal is to build a long term business - the odds are much better - 8% probability of owning a meaningful slice of a cashflow asset.

My purpose of writing this post is to make people aware of base rates rather than outliers - the Consumer Brands category has seen a gold rush like phenomenon in India for the past 5 years.

The principles of building a brand remain unchanged - you have to stand the test of time, bring meaning to your customers life & provide a product of acceptable quality.

Good luck 🙏

[Madhav Immani @RtrMadhav]

@OnePlus_IN @OnePlus_Support

My experience with the OnePlus 12 has taken an unexpected turn, and I’m seeking a fair resolution.

Here is the timeline:

• Purchased in Feb 2024 for ₹63,000
• Underwent official battery replacement at an authorized service centre on Feb 9, 2026

[Jay Alto @theJayAlto]

you pity the moth confusing a lamp for the moon, yet here you are confusing a screen for the world

[Lena Hall @lenadroid]

May you have the audacity of OpenAI that wants a % cut of your AI assisted discoveries... after freely training on the sum of public human knowledge
with $0 royalties to anyone

[Sirisha Duddukunta @Sirisha__D]

Grateful for the recognition at RelevanceLab. Staying focused on continuous growth and driving technical rigor.
Committed to maintaining high standards and delivering impactful solutions.

[Deepinder Goyal @deepigoyal]

One more thing. Our 10 minute delivery promise is enabled by the density of stores around your homes. It’s not enabled by asking delivery partners to drive fast. Delivery partners don’t even have a timer on their app to indicate what was the original time promised to the customer.

After you place your order on Blinkit, it is picked and packed within 2.5 minutes. And then the rider drives an average of under 2kms in about 8 minutes. That's an average of 15kmph.

I understand why everybody thinks why 10 minutes must be risking lives, because it is indeed hard to imagine the sheer complexity of the system design which enables quick deliveries.

Also, if you've ever wanted to know why millions of Indians voluntarily take up platform work and sometimes even prefer it to regular jobs, JUST ASK any rider partner when you get your next food or grocery order.

You will be humbled by how rational and honest they will be with you.

Having said that, no system is perfect, and we are all for making it better than today. However, it is far from what it is being portrayed on social media by people who don't understand how our system works and why.

If I were outside the system, I would also believe that gig workers are being exploited, but that's not true.

[Bhaumik Gowande @bhaumikgowande]

India’s gig-delivery pricing models account only for horizontal distance (GPS) and ignore vertical labour.

In dense cities like Delhi, a significant share of deliveries involve multi-floor access, often without lifts. This unpaid effort distorts delivery time estimates and suppresses worker compensation.

Aggregator policy should mandate pricing adjustments based on floor count and lift availability, with incentives for ground-floor pickup.

Accounting for vertical distance is essential for fair wages, realistic ETAs, and humane urban logistics.

@LabourMinistry

[Camus @newstart_2024]

This is the most jaw-dropping 4 minutes and 21 seconds you will watch this year.

Nicole Shanahan — ex-wife of Google co-founder Sergey Brin, former running mate of RFK Jr., and someone who personally signed nine-figure philanthropy checks — just went full whistleblower on the entire Silicon Valley “tech wife mafia” and how they were used.

Her exact words (full clip attached):
“I don’t think many of the tech mafia wives realize… they were used to set the groundwork for what Klaus Schwab calls The Great Reset.
Their money especially was being conscripted through a network of NGO advisors, Hollywood, Davos, and their own companies.
A really small group of people… completely blind to how their groundwork is being used to enable these Great Reset policies.”

Then she turns the knife inward:
“These women find their meaning through philanthropic work. I really believed I was helping Black communities and indigenous communities rise up.
But now the problems have gotten worse. Crime worse. Mental health worse. The whole model is broken.
At the end of the day they always go: ‘But climate change.’
Social justice + climate change — it gets progressive women 100% of the time.”

She even says many now believe the biggest “climate change issues” are actually geoengineering issues.

This isn’t some random podcast bro.

This is a woman who lived in the mansions, sat on the boards, flew private to Davos parties… and is now saying:
“We were the useful idiots.”

Watch the full unedited 4:21 below. Sound on.

[Pankaj @the2ndfloorguy]

story behind "why netflix built https://t.co/YDCurkt2BM" is brilliant.

so, netflix had a massive fight with ISPs around 2014-2016. ISPs were slowing down netflix on purpose. they wanted more money from netflix

customers got bad streaming. but ISPs just blamed netflix.

netflix had to pay comcast, verizon, at&t and time warner for direct connections to their networks.

but in 2016, they launched fast dot com, clever part - It's not testing your general internet speed. It's testing your speed to netflix's servers specifically. so when someone complained about buffering, netflix could say "run fast dot com." If it's slow, the ISP is the bottleneck.

suddenly millions of people had a tool to prove their ISP was the problem
ISPs couldn't hide anymore.

netflix positioned themselves as the transparent good guys fighting for customers while ISPs looked like greedy monopolies

they solved a pr problem and a customer service problem with one simple website

I guess, that's how you win a corporate war

[Sridhar Vembu @svembu]

We understand the push for Zoho to go public. But let me state the reality: Arattai would very likely not have been built by a public company that faces quarter to quarter financial pressure. It was a "hopelessly foolish" project, and even our employees had expressed scepticism that Arattai would ever gain any traction.

We built it because we felt we need that kind of engineering capability in Bharat. We need a lot lot more of such capabilities in Bharat and we are on it.

We have some very ambitious, long range R&D projects going on in Zoho, including compilers, databases, OS, security, hardware, chip design, robotics (not to mention AI) and on and on. In addition, we have invested in many R&D intensive companies that we know won't make money soon.

Zoho is a kind of an industrial research lab that also makes money to fund itself. We essentially ignore short term profits, as long as we don't lose money. And we have a culture of founders and senior executives living frugally, like how good scientists and engineers in ISRO would live. To us that is the essence of Bharat. Japan operated that way when it was developing.

Imagine saying all that to Wall Street or Dalal Street!

[arnav @arnav_kumar]

There are a dozen reasons why UrbanCompany is a bad startup idea

Dozen reasons why it should not work.
Dozen reasons why there are no parallels to this idea.
Dozen reasons why a thousand 'Uber for X services' startups didn't make it in India and globally

- It is not an easy market
- Supply is unorganised, and services lack standardization
- It is a LOT of ops - finding, training, retraining thousands of people who might not be the most savvy

- Users demand a lot but don't want to pay a heavy premium
- Ticket size is low for many categories
- Many categories are low repeat categories
- There is platform leakage (bypassing)

- Maintaining high NPS and scaling across so many categories is like building 20 different businesses with their own economics, SOPs, demand-supply-seasonality dynamics

- A million things can go wrong while delivering the service - timing, behaviour, product used, expectation mismatch, safety issues..

- You are dealing with humans and atoms (vs code and bytes).
Dealing with humans is hard and draining..

- It is not the sexiest business to think of

- There is no mention of AI/web3/ latest buzzwords

And yet, UrbanCompany made it.
A resounding success story.

It reinforces a core belief I carry -

"All markets are bad markets till the right team shows up.

There are no easy startup ideas.
All startups are hard.

But some teams would win regardless of the variables - market, timing, headwinds, competition..."

Many congratulations to Abhiraj, Varun and team for this resounding success.

And for setting a great example for the ecosystem.

And for giving a life of dignity and pride and economic progress to thousands of unorganised sector professionals

❤️🚀

[ily⚡️ @0xIlyy]

Backend mfs instead of optimizing their code

[The Fauxy @the_fauxy]

🚨#𝗕𝗥𝗘𝗔𝗞𝗜𝗡𝗚: 𝗜𝘀𝗿𝗮𝗲�� 𝗣𝗹𝗮𝗻𝘀 𝘁𝗼 𝗦𝗲𝗰𝗿����𝘁𝗹𝘆 𝗗𝗲𝗽𝗹𝗼𝘆 𝗜𝗻𝗱𝗶𝗮𝗻 𝗚𝗼𝘃𝗲𝗿𝗻𝗺𝗲𝗻𝘁 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 𝗮𝗻𝗱 𝗖𝗼𝗻𝘁𝗿𝗮𝗰𝘁𝗼𝗿𝘀 𝘁𝗼 𝗜𝘁𝘀 𝗘𝗻𝗲𝗺𝘆 𝗡𝗮𝘁𝗶𝗼𝗻

[Markets by Zerodha @zerodhamarkets]

A €3.8 million Paris apartment belonging to India's Deputy Chief of Mission was seized by French courts in 2022.

The reason? A decade-old satellite deal gone spectacularly wrong. This is just the beginning of a global hunt for Indian assets.🧵👇

[Computer @AskPerplexity]

Conclusion:

An equal-weighted portfolio of these 20 stocks would have lost the vast majority of its value since July 2021.

The list is a stark illustration of the risks in chasing high-flying growth stocks during a market mania.

Most of these names have underperformed the broader market by a wide margin, with many suffering catastrophic losses or being delisted.

[Arindam Paul @arindam___paul]

Here’s a likely way of improving the efficiency of your Amazon ads by at least 10 pc

Say you’re spending ₹4–5 lakhs/month on Amazon ads

Your ACoS looks okay. Conversion rate seems fine. But your gut tells you—you’re wasting some money on irrelevant traffic

You’re not wrong

At Atomberg, we figured out that some of our Amazon spend was going toward search terms that had no business seeing our ads.

Stuff like:
•“cheap fan”
•“rechargeable fan”
•“usb fan under 1000”

None of them had anything to do with our category—premium BLDC ceiling fans. But we were still showing up. And paying for the clicks.

And not just Atomberg. I would have looked at Amazon accounts of at least 6-7 brands in the last few years at different scale. Every single one of them had the same issue

The fix? N-gram analysis

The good thing is you can do it in less than an hour—even if you're not a performance marketing expert

What’s N-gram analysis?

It’s just a fancy way of breaking down every search term that triggered your ads into smaller word patterns—called N-grams.

Say a customer searches for “cheap rechargeable fan for hostel room.” That one phrase can be broken down into:
•1-grams: cheap, rechargeable, fan, hostel, room
•2-grams: cheap rechargeable, rechargeable fan, fan for, hostel room
•3-grams: cheap rechargeable fan, fan for hostel, etc.

You do this across all your search terms.

And now, you have data not just at the phrase level—but across every pattern that keeps popping up.

That’s where the gold lies

Why you can’t rely on the search term report alone

I know what you're thinking—“Why do I need all this? Can’t I just look at my search term report and manually negate the bad ones?”

Sure, you can.

But that’s like killing mosquitoes one at a time instead of draining the dirty water.

Here’s why that approach doesn’t scale:

1. Search terms ≠ keywords

Amazon takes your broad or phrase match keywords and shows your ad on hundreds of long-tail search queries. One keyword = hundreds of possible triggers. Some convert. Most don’t. N-gram shows you the underlying common words across them all

2. Volume dilution hides the real waste

Maybe “rechargeable fan for hostel” spent ₹300 and didn’t convert. You ignore it. But what if 12 other search terms also had ‘rechargeable’ in them—and together they burned ₹6,000 with zero sales?

You only see the pattern when you zoom out with N-gram

3. Long-tail searches are infinite. N-grams are finite.

There will always be a new long-tail variation. But if you know “rechargeable”, “cheap”, or “usb” consistently perform poorly—you can negate them once and stop 100 future variations from wasting your budget

4. It’s not just about cleaning up

N-gram analysis also tells you what’s working—what combinations of words are converting better than average

Maybe “white ceiling fan”, “silent BLDC fan”, or “fan for living room” will have a ROAS of 5+. Those are your goldmine phrases. Double down on them

Here's what you should do

1. Download 3 months of search term data
2. Split into unigrams, bigrams, trigrams
3. Create a pivot table with frequency, spend, orders, ROAS per N-gram
4. Mark:
◦High-spend, low-conversion N-grams for negation: e.g., “cheap”, “rechargeable”, “usb”
◦High-ROAS, consistent N-grams for boosting: e.g., “bldc”, “ceiling fan white”, “silent fan”
5. Add negatives at a broad match level across all campaign
6. Create exact match campaigns for top-performing terms

Repeat every 3 months

Very high chance your efficiency will go up by at least 10 percent without doing anything else

[Trendulkar @Trendulkar]

India imposes tariff on India

[No Risk(a), No Reward @NoRiskaNoReward]

@randomrecruiter HMs are looking for the *best* qualified, not the *most,* which means they want someone whose experience best aligns with the role as it was cast. More is not always better.

You don’t use a nail gun just because it’s faster when what you really need is a finish hammer.

[The Random Recruiter @randomrecruiter]

Overqualified?

Some recruiters & hiring managers will think you’re a red flag.

• They think you’ll leave the moment a better offer comes.
• They assume you expect a salary they can’t afford.
• They worry you won’t fit into the team dynamic.

If you don’t address them upfront, they’ll make the decision for you.

[Sridhar Vembu @svembu]

A new chapter begins today.

In view of the various challenges and opportunities facing us, including recent major developments in AI, it has been decided that it is best that I should focus full time on R&D initiatives, along with pursuing my personal rural development mission.

I will step down as CEO of Zoho Corp and take a new role as Chief Scientist, responsible for deep R&D initiatives. Our co-founder Shailesh Kumar Davey will serve as our new group CEO. Our co-founder Tony Thomas will lead Zoho US. Rajesh Ganesan will lead our ManageEngine division and Mani Vembu will lead the https://t.co/ydhRPSqDRN division.

The future of our company entirely depends on how well we navigate the R&D challenge and I am looking forward to my new assignment with energy and vigor. I am also very happy to get back to hands on technical work. 🙏