Hi👋
Aastha here, a technophile with multi-domain interests.
Can wander into conversations of software dev, finance,
engg, starting up,
shows, teds, life perspectives,
sapiens up-skilling endlessly...
fancy way of saying any skill relevant to humans :-P
Find my threads here🔗
I made a free guide to AI fellowships, for anyone early in AI who keeps hearing "apply to a fellowship" without ever being told which one, for what, or how.
Here's what's in it.
https://t.co/TyIuD33DdV
One piece of advice we got during YC was to explain our company using verbs instead of nouns.
Early on, I walked into a meeting and did the opposite:
“We’re building a cloud platform for AI”
No one knew that that meant, their eyes glazed over. Then I started saying this instead:
“We containerize your code and run it on GPUs in the cloud so you don’t have to manage the infra yourself”
That clicked way more. Our brains understand verbs because they’re more concrete. If you describe your company using nouns, you risk people not understanding you.
And no one buys or invests in things they don’t understand.
how to keep momentum after meeting someone cool:
number one tip is follow up QUICKLY
there's a few ways to do this well:
> timing is KEY. the faster you connect, the most likely the connection will stay
> so ask them for their number and follow up!! "hey! so great meeting you, want to do X next week?"
> notice this ask is SPECIFIC - not just "hey want to hang sometime?" (that probably won't go anywhere)
then there's 3 ways to invite them:
> do something 1:1 together: drinks, dinner, pickle ball, a walk, or some shared interest! keep it simple & low pressure.
> invite them to something you already do: yoga class, volleyball with friends, a weekly lunch. gives them a very natural 'in' since it's already in your schedule!
> bonus if you met them at a weekly event: just ask if they'll be there again next week. it saves you the hassle of logistics
most people will be honored that you asked
and happy to have the chance at a new friend too!!
don’t be disappointed if this process fails with someone. there’s a lot of factors that have to go RIGHT to make a friend: both in town, both available, both looking to expand their circle, etc. it's usually never personal & it's always worth putting yourself out there.
the right people will match your energy!!!
go make that new friend!!!
Woww, great feat!
Also relatable as building & witnessing similar end impact agentic platform & integrations here at Doordash;
Infact, we've a lot of these capabilities having specialized implementation sub-product tracks, interesting to see y'all having unified the experience.
We recently built an AI assistant inside @Razorpay called Slash.
It reads our entire codebase, debugs production incidents, reviews specs, writes code, reviews every single PR, answer tech queries and also raises PRs for small features.
It's easily accessible through Slack. We can tag it in any Slack thread, describe the problem in English, and it gets to work.
Six weeks ago, Slash handled 122 tasks in its first week. Last week it handled 14000+. Queries, analysis, bug fixes, PR reviews, test runs and work that earlier lived across scattered tools and teams can now be done with Slash right within Slack. 1000+ people used it in a single week because it got their work done faster. The whole adoption has been completely organic.
The numbers from last week have been very encouraging - 14,854 tasks completed. 2,150 PRs raised, 1,152 merged, 45% of those PRs shipped with zero human rework.
A payout gets stuck mid-retry during a live incident, an engineer tags Slash and within seconds, it cross-references logs with code and pinpoints a state machine bug blocking the retry-to-failed state transition. Tells the team exactly which logs to check and how to resolve the incident.
With its K8s analyzer skill, Slash scanned a single namespace, right-sized all 11 workers using 48-hour P95 pod metrics, and raised the PR. One run saved $560/month.
A marketing banner bug was fixed with few prompt iterations with a PR raised, merged to prod and deployed in minutes. No front-end developer touched the code.
Security teams ran static security testing and remediation through Slash at org scale. Thousands of findings were purged and many more got validated autonomously.
But Slash isn't just an engineering tool.
Account managers now trace stuck customer payments and integration failures through Slash instead of pinging engineers on Slack. L2 product support tickets get triaged by Slash before they reach engineering.
250+ non-engineers ran thousands of sessions last week. PMs used it for research on our payments infra, customer interviews and product features sometimes raising PRs of their own. Analytics teams built SQL pipelines. 11% of all sessions came from people outside tech and product.
On our company bakkar (watercooler) Slack thread, someone asked Slash jokingly to assign tasks to everyone and it responded in the same tone. It seamlessly started participating in inside jokes and conversations.
The quality compounds with use. Engineers who shipped 11+ Slash PRs averaged a 63% merge rate without rework. First-timers averaged 37%. Across the org, human review comments per PR have dropped more than 40% with Slash starting to do in-depth review of every single change.
We're still early. Large cross-repo refactors, fully agentic sdlc and plan mode are next. But Slash has already changed how people at Razorpay build, debug, and ship every day.
the opportunity cost of spending your 20s doing:
routine tasks
daily standups
eod updates
waiting for approvals
working on one tiny piece of the puzzle
is the highest right now.
especially when the internet lets you build, learn, distribute, experiment, fail, and restart faster than ever before.
just do your own thing.
and stay obsessed long enough for it to work.
Sahil Bloom reveals the easiest way to build a $100,000 a month business
“If you are a young person right now and you are technologically savvy, you could be making an enormous amount of money by consulting directly with companies that have no idea how to use AI or implement it into their workflows”
“Huge companies can go and afford McKinsey or Bain or whoever to come in and do this for them on these enormous projects, but small and medium-sized businesses are not getting hit up by those big consultancies”
“I think that a young person that understands AI and has a pretty decent understanding of some of the models that are out there and the capabilities can go build a $100,000 a month business doing that very quickly”
everyone assumed ai would flatten the talent distribution.. turns out it amplifies the hell out of it.
it used to be: can you build it.
now it’s: do you know what’s worth building, & can you feel when it’s wrong.
that’s ~unteachable & ~unautomatable right now. models can generate 100 variants of anything but they still can’t tell you which one matters.
amazing talent is roughly priceless in the ai era because with ai it’s leverage++++++.
Super intelligence is already here, and the bottleneck is our ability to harness it. By building efficient harnesses!
If you're a builder who have been burning the mid night oil, deep in the wonderland of Openclaw, Claude Code and agents, cycling between eureka and existential crisis, I've an offer you can't reject!
You will work with me very closely, to reimagine how humans work. Build systems that can make almost everyone 10x productive, and take away their grunt work.
You will have infinite token budget, an opportunity to work on problems that frontier research labs are solving, working with the researchers there, and work with some of the smartest folks in this space in the country.
Salary no barrier, your annual earning would be a function of what impact you can drive, education and age doesn't matter, show me what you've built.
DMs are open, and we're up for a big adventure! Lessgo!
Chia seeds make your stomach flat, but not for the reason you think.
Most people assume it’s the fiber. They’re half right.
Yes, chia seeds are loaded with fiber at about 10g per ounce. But fiber alone isn’t what’s flattening your stomach.
Chia seeds absorb up to 12x their weight in water and form a thick gel in your digestive tract. That gel slows the release of sugar into your bloodstream, which keeps insulin low.
Higher insulin levels can lead to increased fat gain especially visceral fat around your organs.
On top of that, the gel physically expands in your stomach and sends satiety signals to your brain before you’ve overeaten. You eat less without trying.
Gut inflammation is a hidden driver of bloating. Omega-3s in chia seeds reduce that.
So it’s not just fiber. It’s insulin, satiety, and anti-inflammation all working against together.
Add a tablespoon to water, a smoothie, or, my personal favorite, Greek Yogurt and your stomach will thank you.
Few months ago, I set up a small AI hacker team at @Razorpay
2 people. Today, they are 100x builders.
With AI, people aren’t the constraint.
Org structure is.
So now I’m scaling this.
If you’ve spent the last few months deep in
Claude Code / OpenClaw / agents
(or anything similar)
and feel like you’ve seen the future - this is for you.
What you’ll do:
Review workflows.
Rebuild them with AI.
Ship fast.
Perks:
• Unlimited tokens. Any model. Any tool.
• Real problems at massive scale
• No hierarchy. Direct access across the org
No compensation ceiling.
Pay scales with output, not title.
Outperform the org, out-earn it.
No resume.
Send me what you’ve built with AI. (Form below)
Bangalore | Full-time | Builders only.
4 factors to consider when making a career decision (none of which involve money):
1. Talent Density
You tend to rise or fall to the level of the people around you. When you work with exceptional people, you absorb their standards, pace, frameworks, and instincts almost through osmosis. High-talent environments compress learning cycles and force you to grow faster than you would on your own. If you care about compounding skills and judgment, there’s nothing more valuable than choosing the room with the highest talent per square foot.
2. Market Growth
A fast-growing market makes everything feel easier. It's a tailwind for skill accumulation, title trajectory, and opportunity set. Even average players can look like stars in a rapidly expanding industry; great players can compound outlier outcomes. Conversely, declining or stagnant markets create headwinds that even great performers struggle to overcome. It's very difficult to swim upstream, no matter how strong the swimmer.
3. Leadership Quality
Your manager is often the single greatest variable in your long-term development. Great leaders create environments where you're challenged, trusted, coached, and pushed into uncomfortable growth. Poor leaders create ceilings. They limit your exposure, suppress your risk-taking, and narrow your aperture of what’s possible. Choose leaders who invest in people, not just outputs.
4. Intellectual Stimulation
Intellectual stimulation is a leading indicator of future growth because curiosity compounds just like capital. You want to be in environments that make you feel alive intellectually. Where the problems are interesting, the challenges stretch you, and you're forced into deeper thinking. When your mind is engaged, you naturally develop new skills, pursue new ideas, and build momentum.
What would you add to the list (and why)?
Every country has an energy. And that energy rewires you whether you notice it or not. People move to Japan and become minimal. People move to Mexico and their entire relationship with time softens. People move to New York and suddenly they can't sit still. Your personality is far more malleable than you think. We treat it like something fixed, but new surroundings give you new defaults. New pace. New habits. New values absorbed through proximity instead of effort. You're not just the average of the 5 people closest to you. You're the average of the 5 places, the 5 routines, and the 5 inputs you're exposed to most. Your commute shapes you. The weather shapes you. Every space you occupy is voting on who you become. That's why I believe choosing where you live is one of the most important decisions you'll ever make. More important than your job title. Maybe more important than your five-year plan. Because the place shapes the plan. The place shapes your energy, your habits, your relationships, your default state. Get the place right and half of the other decisions start making themselves. Get it wrong and you'll fight yourself every day.
I've been using Claude Code heavily lately, and while doing so, I've been casually watching the OpenClaw codebase evolve. What I've witnessed mirrors a pattern I've seen play out with every agent framework before it — and it's worth talking about.
OpenClaw is a remarkable project. It went from zero to one of the most-starred repos on GitHub in under a week. And now, with AI agents actively contributing to its own development, the codebase is doing something extraordinary: it's expanding at a pace no human team could match — or meaningfully oversee.
A month ago, the repo sat around 400k lines of code. Now it's pushing 1 million. Daily commits are holding steady above 500. There's even a lean fork — nanobot — that replicates the core functionality in roughly 4,000 lines, advertising itself as "99% smaller." That contrast alone tells you something important about what's happening to the original.
From a software engineering standpoint, this is not a sign of health. Velocity without comprehensibility is just entropy with good PR.
What we're witnessing is a codebase that has crossed a threshold: it is no longer humanly maintainable. No engineer can meaningfully review these commits. No architect can hold the system model in their head. Technical debt isn't accumulating — it's compounding, at AI speed, every single day.
This raises a question I can't stop thinking about:
Does there exist any project in the world that can grow sustainably — maintaining architectural clarity while continuously expanding functionality — with zero meaningful human involvement? Not "AI assists humans," but genuine autonomous stewardship of a living codebase?
If that's possible, then what kinds of projects still can't be fully AI-maintained today? Is it complexity? Ambiguity in requirements? The need for taste and restraint?
And the deepest question: will we eventually reach a point where every software project can be fully maintained by AI — including the AI systems doing the maintaining?
My instinct is this: AI is extraordinarily good at local optimization. Write this function. Fix this bug. Add this feature. But "keeping a system simple" is not a local problem. It requires global aesthetic judgment — the ability to say "we could add this, but we shouldn't." That kind of restraint might be the last genuinely human contribution to software engineering.
Or maybe I'm wrong. Maybe future AI systems will develop something like taste. Maybe they'll learn that the most important code is often the code you don't write.
I genuinely don't know. But watching a codebase grow from 400k to 1M lines in a single month, driven almost entirely by agents, makes me feel like we're all about to find out — whether we're ready or not.