Abhinav Singi

Curious, open minded and stuff.
Engineering @LyearnHQ
Ex. Sr. Director of Product Engineering @Sprinklr
CS @iiit_hyderabad

[shadcn @shadcn]

Sometimes I leave out context and just sit and watch the agents struggle. Reminds them who's still in charge.

[Abhinav Singi @abhinavsingi]

Man from the future

[Aravind @aravind]

Nepal done. VZ done. Keir Starmer resignation took time, but also done.

Next: Sanchez of Spain and a coup in Cuba, hook or crook. Macron will also go by next year.

[Deedy @deedydas]

Most software engineers are facing an identity crisis bordering on depression.

As CTOs aggressively evangelize tokenmaxxing, a class divide ensues.

The lazy. The lazy push code. They don't write it. They don't manually test it. They don't even read it. They're on autopilot. See Jira ticket, prompt for task, submit code. Many of them are barely on their computer the whole day. A comment on the PR asking why they did this? The lazy ask AI. A Slack message? The lazy ask AI. Need to prepare for standup? The lazy ask AI. As long as it sounds enough like them and isn't detected. Some of the lazy are even overemployed, and work multiple jobs. The lazy smart ones get away with this, and even rewarded. After all, software engineering for the lazy is just a dance to convince your colleagues you're smart and hard working.

The craftsmen. The craftsmen are tired. Very tired. 15 PRs in queue. Slack blowing up. The entire burden of review falls on the craftsman. The burden of understanding. They try. They work their way through the code, thoughtfully commenting to improve what ships. The response? A lazy: "That's a clever idea! You're absolutely right." with an incorrect change. It's fine, the craftsman says. I can fix them. They write a doc urging his colleagues to be better. The next day? 20,000 line PR to review. Day after day, their workload grows. Bugs seep into production. No one seems to care. Another round of AI is thrown at it. Their animosity to their colleagues rises. Eventually, they give up. It's just not what it used to be. The craft they loved is dead. They eventually wake up, a lazy.

This isn't all companies. Many companies are genuinely more productive, adopt the right set of principles and practices around AI development and have highly talented teams that trust each other. It tends to happen in bigger companies that are 10+yrs old with a higher talent variance. But it happens. A lot.

[Abhinav Singi @abhinavsingi]

you learn new things everyday!

[Bull Theory @BullTheoryio]

BREAKING: Google is planning to release 32 million mosquitoes across Florida and California.

The company has asked the EPA for permission to proceed, with the public given until June 5 to respond.

The mosquitoes are infected with Wolbachia bacteria, which stops them from reproducing and slowly collapses the wild population from within.

Google's previous Debug Project trial in California's Central Valley nearly eliminated mosquitoes from three test sites entirely. A separate trial in Singapore cut dengue cases by 70% within 12 months.

Google has now released over 1 billion mosquitoes across four continents. This new proposal is the largest deployment in US history.

[I Am Devloper @iamdevloper]

Black Mirror S8E1: In 2027, developers are allocated a daily Claude token allowance by the government. A junior dev burns through his entire month's supply trying to centre a div. His family starve. He is forced to write the code himself. He can't. Society collapses.

[TBPN @tbpn]

"Go all the way until it hurts. If you're doing something and it's easy, it's not valuable." - @travisk

"If anyone says a strategic thing was easy, I'm like, 'You messed up. You could have gone way further. More competitive advantage. More differentiation. Get it together.'"

[Ray Dalio @RayDalio]

The greatest gift you can give someone is the power to be successful. Giving people the opportunity to struggle rather than giving them the things they are struggling for will make them stronger.

Compliments are easy to give but they don't help people stretch. Pointing out someone's mistakes and weaknesses (so they learn what they need to deal with) is harder and less appreciated, but much more valuable in the long run. Though new employees will come to appreciate what you are doing, it is typically difficult for them to understand it at first; to be effective, you must clearly and repeatedly explain the logic and the caring behind it. #principleoftheday

[Matt @matt503ea5sf9z5]

They're doing drone strikes with a KANBAN board and story points

[tmuxvim @tmuxvim]

the fuck do you know about haircuts

[Dan Robinson @danlovesproofs]

https://t.co/v7WnOzVhLq

[Abhinav Singi @abhinavsingi]

@netflix Do your magic

[Claude @claudeai]

Ads are coming to AI. But not to Claude. Keep thinking.

[Abhinav Singi @abhinavsingi]

wow!

[Lenny Rachitsky @lennysan]

Top takeaways from @stanine, COO/CPO at @Rippling:

1. Extraordinary results demand extraordinary efforts. “If you ever find yourself in the comfort zone at work, you’ve definitely made a mistake.”

2. Your job as a leader is to preserve intensity, not buffer it. Every layer of management can dilute the founder’s urgency by an order of magnitude. Don’t protect people from high standards. There’s an infinite supply of people who will advocate for relaxation; don’t be one of them.

3. Never be a “chill boss.” Chill doesn’t accomplish anything. Be intense, be respectful, be good, but don’t be chill. Nobody in a position of leadership actually wants to coast. The invigorating message isn’t “Take it easy”; it’s “Let’s go win.”

4. Understaff every project on purpose. When you have too many people, the lower-priority work gets done. It also creates politics and wasted effort. Deliberately keep teams lean. The wisdom is in knowing when you’ve gone too far.

4. Processes exist to reduce volatility—but they they will suppress creativity. Your payroll system should be boring and predictable (low volatility). Your new product experiments should tolerate chaos (high creativity).

5. The “bored and tired zone” is where great teams separate from good teams. Before you hit an inflection point, the work feels endless and unrewarding. You don’t want to write the documentation, you’re sick of the 19th bug. Push through anyway. That’s when competitors lose.

6. Treat escalations and complaints as gifts. Customers don’t want to bother you. Your reports don't want to bother you. That silence hurts you. The only way to improve is to know the problems. Chase them. Every escalation is data on how to make the system better.

7. You learn far more from success than failure. The “failure is the best teacher” line is comforting but misleading. Matt learned more in seven years at Rippling than nine years at his struggling startup. Join winning teams. Watch how it’s done right.

8. If you’re wondering whether you have product-market fit, you don’t. When it arrives, it’s unmistakable. Matt spent nine years at a startup thinking he “maybe” had it. At Rippling, it’s obvious. That’s what PMF feels like.

9. Quitting is sometimes the smartest move. 4-5 years in without clear traction? Maybe it's time to quit. “Never give up” serves VCs, not founders. Time is the one resource you can’t get back.

10. None of this matters—and that’s liberating. We’re on a blue marble drifting through space. Silicon Valley in 2025 is Florence in the Renaissance: a once-in-history moment. Play the sport with everything you’ve got, but never forget it’s just a sport. That perspective is the backstop that makes the intensity sustainable.

[Addy Osmani @addyosmani]

Every time we've made it easier to write software, we've ended up writing exponentially more of it.

When high-level languages replaced assembly, programmers didn't write less code - they wrote orders of magnitude more, tackling problems that would have been economically impossible before. When frameworks abstracted away the plumbing, we didn't reduce our output - we built more ambitious applications. When cloud platforms eliminated infrastructure management, we didn't scale back - we spun up services for use cases that never would have justified a server room.

@levie recently articulated why this pattern is about to repeat itself at a scale we haven't seen before, using Jevons Paradox as the frame. The argument resonates because it's playing out in real-time in our developer tools. The initial question everyone asks is "will this replace developers?" but just watch what actually happens. Teams that adopt these tools don't always shrink their engineering headcount - they expand their product surface area. The three-person startup that could only maintain one product now maintains four. The enterprise team that could only experiment with two approaches now tries seven.

The constraint being removed isn't competence but it's the activation energy required to start something new. Think about that internal tool you've been putting off because "it would take someone two weeks and we can't spare anyone"? Now it takes three hours. That refactoring you've been deferring because the risk/reward math didn't work? The math just changed.

This matters because software engineers are uniquely positioned to understand what's coming. We've seen this movie before, just in smaller domains. Every abstraction layer - from assembly to C to Python to frameworks to low-code - followed the same pattern. Each one was supposed to mean we'd need fewer developers. Each one instead enabled us to build more software.

Here's the part that deserves more attention imo: the barrier being lowered isn't just about writing code faster. It's about the types of problems that become economically viable to solve with software. Think about all the internal tools that don't exist at your company. Not because no one thought of them, but because the ROI calculation never cleared the bar. The custom dashboard that would make one team 10% more efficient but would take a week to build. The data pipeline that would unlock insights but requires specialized knowledge. The integration that would smooth a workflow but touches three different systems.

These aren't failing the cost-benefit analysis because the benefit is low - they're failing because the cost is high. Lower that cost by "10x", and suddenly you have an explosion of viable projects. This is exactly what's happening with AI-assisted development, and it's going to be more dramatic than previous transitions because we're making previously "impossible" work possible.

The second-order effects get really interesting when you consider that every new tool creates demand for more tools. When we made it easier to build web applications, we didn't just get more web applications - we got an entire ecosystem of monitoring tools, deployment platforms, debugging tools, and testing frameworks. Each of these spawned their own ecosystems. The compounding effect is nonlinear.

Now apply this logic to every domain where we're lowering the barrier to entry. Every new capability unlocked creates demand for supporting capabilities. Every workflow that becomes tractable creates demand for adjacent workflows. The surface area of what's economically viable expands in all directions.

For engineers specifically, this changes the calculus of what we choose to work on. Right now, we're trained to be incredibly selective about what we build because our time is the scarce resource. But when the cost of building drops dramatically, the limiting factor becomes imagination, "taste" and judgment, not implementation capacity. The skill shifts from "what can I build given my constraints?" to "what should we build given that constraints have in some ways been evaporated?"

The meta-point here is that we keep making the same prediction error. Every time we make something more efficient, we predict it will mean less of that thing. But efficiency improvements don't reduce demand - they reveal latent demand that was previously uneconomic to address. Coal. Computing. Cloud infrastructure. And now, knowledge work.

The pattern is so consistent that the burden of proof should shift. Instead of asking "will AI agents reduce the need for human knowledge workers?" we should be asking "what orders of magnitude increase in knowledge work output are we about to see?"

For software engineers it's the same transition we've navigated successfully several times already. The developers who thrived weren't the ones who resisted higher-level abstractions; they were the ones who used those abstractions to build more ambitious systems. The same logic applies now, just at a larger scale.

The real question is whether we're prepared for a world where the bottleneck shifts from "can we build this?" to "should we build this?" That's a fundamentally different problem space, and it requires fundamentally different skills.

We're about to find out what happens when the cost of knowledge work drops by an order of magnitude. History suggests we (perhaps) won't do less work - we'll discover we've been massively under-investing in knowledge work because it was too expensive to do all the things that were actually worth doing.

The paradox isn't that efficiency creates abundance. The paradox is that we keep being surprised by it.

[Abhinav Singi @abhinavsingi]

"You don’t flip a switch into excellence. You rehearse it daily."

[Zach Brandon @MVP_Mindset]

Tom Brady explains his mental edge and why practice (not gameday) creates separation.

"There was a part of me that was a psychopath out there. I was extremely hypercompetitive every day. I didn't feel like let's get to Sunday and now it's the time...Every day is the time to give your best, even in practice."

Every day your standards are either reinforced or lowered by how you treat practice.

You don’t flip a switch into excellence. You rehearse it daily.

📹: Impaulsive Podcast

[Abhinav Singi @abhinavsingi]

Now that's an outage.

[Starlink @Starlink]

On December 17, Starlink experienced an anomaly on satellite 35956, resulting in loss of communications with the vehicle at 418 km. The anomaly led to venting of the propulsion tank, a rapid decay in semi-major axis by about 4 km, and the release of a small number of trackable low relative velocity objects. SpaceX is coordinating with the @USSpaceForce and @NASA to monitor the objects.

The satellite is largely intact, tumbling, and will reenter the Earth’s atmosphere and fully demise within weeks. The satellite's current trajectory will place it below the @Space_Station, posing no risk to the orbiting lab or its crew.

As the world’s largest satellite constellation operator, we are deeply committed to space safety. We take these events seriously. Our engineers are rapidly working to root cause and mitigate the source of the anomaly and are already in the process of deploying software to our vehicles that increases protections against this type of event.

[Abhinav Singi @abhinavsingi]

Change your password!

[PeachProof @PeachProof23]

You Should Probably Change Your Password! 👨‍💻 🙄😂

[Abhinav Singi @abhinavsingi]

No wonder broadband's support team asks to check on speedtest dot net

[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

[Abhinav Singi @abhinavsingi]

"People by nature take the path of least resistance. If it's working, they'll keep going. Doing hard things means you're going on an untraveled path. It's risky."

[Amjad Masad @amasad]

How to Keep Winning

https://t.co/cfUFTlDctk