Update: For the last ~3 months since I've been on this journey.
I've managed to build a few projects, and today seems like the right time to share my latest project.
A US Stocks Analysis Agent, check it out: https://t.co/DkmGEHyl1y
I’m about 2.5 years late to the party — but it’s high time I understand how AI actually works.
If I delay it any further, I’ll be irrelevant in a couple of years.
#Day0 starting my technical learning journey today.
@X, keep me accountable.
India is a weird market. With obesity rates shooting up, I'd have bet on the sales of generic GLP-1s exploding once their patents expired. They now cost about Rs 1,000–2,500 a month, and there's growing evidence pointing to benefits well beyond weight loss, including cardiovascular, metabolic, and liver health.
Yet, generic drugmakers are quietly cutting their sales targets by 25–30%. At Rs 1,000–2,500 a month, it's cheaper than a gym membership. The real problem seems to be retention. GLP-1s are injectables, and you have to keep taking them. If you stop, you gain back the lost weight. It seems like asking someone to stay on a weekly injection indefinitely is a much harder sell.
A few other friction points:
For a variety of reasons, Indians haven't taken to GLP-1s with the same enthusiasm as Western populations. Could it be because Indian physicians are conservative when it comes to prescribing newer drugs?
Self-injecting is a pain for most people, and that friction and inertia might be stopping them from starting in the first place.
Given that there are now GLP-1 pills, I'm wondering if the adoption curve will change.
PSA: when you wake up, reach for your phone immediately. Do NOT scroll Instagram reels. Send a good morning message. Not to your girlfriend, to Claude.
That way, you can start the clock for your 5 hour Claude Code usage limit while you freshen up and head to the office. At noon, the 5 hour window would have passed and the usage limit would reset. Then you can generate more shareholder value.
Advisory businesses have always been judged on activation: what % of users acted on the advice.
When execution is guaranteed, that metric becomes irrelevant.
The only thing left to measure is the quality of the advice itself. These companies have spent years optimising for engagement.
Now they'll have to optimise for being right.
P3P is a new payments framework where a user approves a UPI mandate once, and after that an AI agent can transact on their behalf, no further authentication needed.
Today, retail financial advice is a one-way street. You send alerts, nudges, and recommendations, and then hope the user acts on your advice.
P3P flips that. The moment someone subscribes and places a mandate, you're no longer suggesting trades you're executing them. And that changes the metric that matters.
I've been building products around financial advice for the last 6 years.
The #1 problem is activation: % of people actually acting on the advice.
People come on your platform and large number even converts, but most of them don't end up acting on it because they're too scared whether this will actually work.
@PineLabs seems to have just solve that problem 🧵
While money is money, Vaibhav should stay at RR
He can potentially create Virat (RCB) and Dhoni (CSK) level of legacy at RR. The type of legacy that outlives the playing career
A young D2C founder told me, with genuine pride, that her Instagram had crossed a million followers.
I asked what she sold.
She told me. Sales had been flat for four months.
She was about to raise more money to spend on more reels to grow an audience that was, by every indication, uninterested in paying her for anything.
This is one of the great unacknowledged tragedies of modern consumer business: attention and intent have been conflated into a single metric, and an entire generation of founders has been trained to optimise for the former while believing they're optimising for the latter.
They are different things.
Attention is cheap. It is generated by being funny, pretty, controversial, or adjacent to someone famous. Anyone with a ring light and a moderate tolerance for humiliation can acquire it at scale.
Intent is expensive. It requires that a person has identified a problem, decided that problem is worth spending money to solve, considered several options, and concluded that yours is the right one.
These acts have nothing to do with each other. The audience that watches you dance on reels is selecting for "entertaining content in the evening." The audience that buys your product is selecting for "solution to a specific, felt problem." The overlap between these two groups is not zero, but it is nowhere near what founders assume, and it is almost never enough to sustain a business.
The useful question is not "how do I grow my following?"
It is: "what do the people in my following actually need that I could sell them?"
Answering that well requires asking them. Which requires research. Which brings us, inconveniently, back to the original problem that reel-growth was invented to avoid.
The old meta for rapid UI development was:
> ask coding agents to build something
> iterate on the IA or design
> wait for it to keep rebuilding the app for each rev
The new meta:
> use Imagegen 2.0 in Codex to generate UI mocks
> iterate very quickly with Imagegen on concepts
> pick one and ask Codex to build it, one shot
It feels like a way better workflow and is probably way more token efficient - try it out if you haven't!
Recently my son asked me why he needs to do mental math when calculators exist. I told him if he doesn't, he will make irrational decisions throughout his life.
Let me explain. Say you see two packs of snacks. A 500g pack for ₹100, and a 200g pack for ₹45. Which one should you buy?
The math is not at all hard, but people who are scared of mental math will not do it. This is not such an important decision that you pull out a calculator for it. So you make the decision on vibes - say ₹100 "looks too high", or that the smaller pack costs "less than half of the biggest one" or some such.
The problem isn't that you made a poor decision on snacks. It is that if you do this repeatedly, you train your mind to make decisions on vibes. Over time your reasoning muscle atrophies - so you start relying even more on vibes.
Before you know it, you are taking even big decisions on vibes. Should I rent or buy a house? Let's decide based on "EMI affordability", not rental yield. Should I invest in this IPO? I have heard of the company's brand so I'm all in. It isn't only financial or quantitative decisions either - in my mind the math muscle and the logic muscle are closely correlated, so a decline in one certainly affects the other.
Like the Arab who let the camel's nose inside the tent, fear of math is the first step towards thoughtlessness, and needs to be nipped in the bud. Intellectual laziness starts with snack prices.
btw this is the app that has generated $5000 in just 3 days, organically. it uses your Mac’s accelerometer sensor to moan when you slap it. we’re in the peak era of software.
This is specifically interesting because when the platform that powers 43% of the web opens its doors to AI agents it definitely tells you what the next wave is going to be.
Full breakdown here: https://t.co/y8idFvWRgt
@wordpressdotcom, the company that powers 43% of the web, has built-in support for @claudeai , @GeminiApp, and @OpenAI as part of the platform itself.
Here's what they shipped 🧵
- If you're a marketer, you can publish content, update product pages, and pull analytics from a single conversation.
- For a developer, every WordPress site is now a surface your AI agents can plug into.
- And if you're a business owner running on WordPress, you just got a team member that works 24/7.
IMO this presents a few interesting opportunities:
1. There's a massive opportunity in just educating C-suites on how to use AI in their own workflows which helps them make faster & better decisions.
2. If 66% of companies haven't moved past pilots, that means most businesses are still waiting to be brought onto the AI stack. The opportunity to help companies go from experimenting to AI-native is enormous, and it's wide open right now.
Check out the full breakdown over here: https://t.co/ECpkG1vEQc
Here were some examples:
1. A bank got its executives to use AI dashboards in daily decisions. Result: $150M in incremental revenue.
2. A pharma company cut drug launch prep from 12 months to 3
3. A retailer retrained 8,500 call center staff on AI and generated $1.4B in revenue gains.
The pattern is the same every time. The companies that scaled were the ones where leadership changed their own habits first.