Chandu G

News buff, Techie

[Kunal Shah @kunalb11]

It’s been a minute.

2015–2018
- Exited FreeCharge. Spent time learning and investing.
- Pondered about: Why can't trust be rewarded? Started with $1M of personal capital.
- Launched CRED to reward people for paying credit card bills on time.

2019–2025
- Built a system run by a team that values ownership, judgment, and craft.
- Grew from 0 to 17M members by aligning incentives with behaviour.
- Built several products during COVID lockdowns.
- Raised $900M+ from global investors. Did 4 ESOP buybacks.
- Made Indiranagar and IPL ads slightly more interesting.
- Received a full stack of regulatory licences.
- Lost 35 kilos.
- Scaled from 0 to ~$325M ( ~₹3,200 crore) in annual revenue across payments, lending, insurance, commerce, wealth, and credit cards.
2026
- First profitable quarter (yet occasionally asked what our business model is)
- Raised another $900M from Meta in primary and secondary capital.
- Announcing our 5th ESOP buyback.

Today

CRED is ready for its next phase. I am stepping back and @miten steps in as interim CEO, partnered with an incredibly talented team. He has been heading strategy and finance and suffering me since 2020. I’m stepping away from the operating role and will continue as a shareholder. My commitment doesn’t change. Just the role.

Extremely grateful to our members, partners, regulators, and investors who made this possible. And to our board, Shailendra, Micky, Saurabh for their extraordinary conviction.

Team CRED, I’ll still expect you to be a 10x version of yourselves.

As for me, I’ll be joining Meta to lead WhatsApp globally.

Meta comes in as a minority investor in CRED. No access to member data.

While it’s come very far, the delta between WhatsApp today and its full potential is massive. I look forward to working with Mark, Chris, and the leadership across Meta for the next step in WhatsApp’s journey. Will, thank you for scaling something the world relies on quietly, and for making this transition smooth.

Onwards.

[Chandu G @ChanduG]

Solid argument. If re-organization is necessary, this seems to be the best way possible for southern states.

[Lokesh Nara @naralokesh]

Dear Dr. Tharoor, a few points here.

First, Article 81 envisages that seats in the Lok Sabha be allocated on the basis of population. The constitutional freeze linked to the 1971 Census was always temporary and was due to expire in 2026. In the absence of any intervention, a fresh delimitation based on 2026 Census will see several southern states facing a sizable reduction in their share. Due to your opposition to the bill, the Congress party is squarely responsible for this.

Second, India in 2026 is not India in 1971. Our population has grown from about 55 crore to nearly 146 crore. While Lok Sabha membership has remained virtually unchanged, the average MP today represents nearly 2.5 times as many citizens as an MP did when the freeze was imposed. Expanding the House is therefore a democratic necessity, not a political choice.

Third, if seats are increased to better reflect today’s population realities, retaining each state’s proportional share is a reasonable and balanced approach. It protects states that successfully implemented population stabilisation while simultaneously improving representation for all Indians.

More fundamentally, it is worth remembering that no state has a constitutional right to greater representation per voter than another. The Constitution’s objective is precisely the opposite: that every citizen’s vote should carry, as nearly as practicable, equal weight. The continuation of the present proportional balance is not a constitutional entitlement; it is NDA’s way of ensuring that states that acted responsibly are not disadvantaged.

As for your thought experiment, parliamentary influence ultimately flows from votes on the floor of the House. Whether a simple majority or a two-thirds majority is required, a proportionate increase for all states leaves those equations unchanged. If everyone receives the same proportional increase, nobody gains an advantage over anyone else!
@ShashiTharoor

[Chandu G @ChanduG]

@AnthropicAI Management succeeds more than anybody. May be engineers push back less on PRs coming from Managers ?

[Sidhant Sibal @sidhant]

"European sells weapons which are used to attack India, for many many years. We Indians have never done anything to endanger Europe", EAM Jaishankar says when asked about India's stance on Russia Ukraine conflict

[Chandu G @ChanduG]

@Tenali_RK JEE mains has two attempts with gap of more than a month. They will assign best rank.

[Chandu G @ChanduG]

Great story telling.

[Matt Garman @mattsgarman]

Most people thought flat data center networks would never work at hyperscale.

The @awscloud team figured it out.

Resilient Network Graphs are a completely new network architecture, now live.

33% better throughput, 40% less network power.

https://t.co/LEaIItVqe9

[Chandu G @ChanduG]

So looks like RR or PBKS can make it to playoffs. I would like to see RR make it to playoffs and we will get to see more of Suryavanshi.

[Chandu G @ChanduG]

This innings by Shreyas Iyer may be one of the insights why he is not considered for T20 team. Main reason is they can't replace anyone from World Cup winning team.

[Chandu G @ChanduG]

I think PBKS will struggle to get to Playoffs unless they get to chase and couple of batsman having a good day.

[Chandu G @ChanduG]

This is it. Frame it!

[Mitchell Hashimoto @mitchellh]

I strongly believe there are entire companies right now under heavy AI psychosis and its impossible to have rational conversations about it with them. I can't name any specific people because they include personal friends I deeply respect, but I worry about how this plays out.

I lived through the great MTBF vs MTTR (mean-time-between-failure vs. mean-time-to-recovery) reckoning of infrastructure during the transition to cloud and cloud automation. All those arguments are rearing their ugly heads again but now its... the whole software development industry (maybe the whole world, really).

It's frightening, because the psychosis folks operate under an almost absolute "MTTR is all you need" mentality: "its fine to ship bugs because the agents will fix them so quickly and at a scale humans can't do!" We learned in infrastructure that MTTR is great but you can't yeet resilient systems entirely.

The main issue is I don't even know how to bring this up to people I know personally, because bringing this topic up leads to immediately dismissals like "no no, it has full test coverage" or "bug reports are going down" or something, which just don't paint the whole picture.

We already learned this lesson once in infrastructure: you can automate yourself into a very resilient catastrophe machine. Systems can appear healthy by local metrics while globally becoming incomprehensible. Bug reports can go down while latent risk explodes. Test coverage can rise while semantic understanding falls. Changes happens so fast that nobody notices the underlying architecture decaying.

I worry.

[Chandu G @ChanduG]

Is this a Kerala thing ? Most of the politicians seems to live like middle class and in small houses instead of bungalows

[V D Satheesan @vdsatheesan]

Visited #AKAntony Sir and sought his blessings. His unwavering support, guidance, and wisdom continue to be a great source of strength as we move forward with renewed commitment and responsibility.
#TeamUDF

[Chandu G @ChanduG]

@copyconstruct It just may be more marketing just like inviting Jensen to their conference and claiming they are closely working with Nvidia.

[Chandu G @ChanduG]

@cricket_broken @GovindIstOdraza If PBKS,RR,CSK lose all their games and DC wins next 2 games, they get to playoffs without needing RR.

[Chandu G @ChanduG]

Musk trying to limit OpenAI's compute advantage.

[Claude @claudeai]

We’ve agreed to a partnership with @SpaceX that will substantially increase our compute capacity.

This, along with our other recent compute deals, means that we’ve been able to increase our usage limits for Claude Code and the Claude API.

[Claude @claudeai]

We’ve agreed to a partnership with @SpaceX that will substantially increase our compute capacity.

This, along with our other recent compute deals, means that we’ve been able to increase our usage limits for Claude Code and the Claude API.

[Andrew Ng @AndrewYNg]

Coding agents are accelerating different types of software work to different degrees. When we architect teams, understanding these distinctions helps us to have realistic expectations. Listing functions from most accelerated to least, my order is: frontend development, backend, infrastructure, and research.

Frontend development — say, building a web page to serve descriptions of products for an ecommerce site — is dramatically sped up because coding agents are fluent in popular frontend languages like TypeScript and JavaScript and frameworks like React and Angular. Additionally, by examining what they have built by operating a web browser, coding agents are now very good at closing the loop and iterating on their own implementations. Granted, LLMs today are still weak at visual design, but given a design (or if a polished design isn’t important), the implementation is fast!

Backend development — say, building APIs to respond to queries requesting product data — is harder. It takes more work by human developers to steer modern models to think through corner cases that might lead to subtle bugs or security flaws. Further, a backend bug can lead to non-intuitive downstream effects like a corrupted database that occasionally returns incorrect results, which can be harder to debug than a typical frontend bug. Finally, although database migrations can be easier with coding agents, they’re still hard and need to be handled carefully to prevent data loss. While backend development is much faster with coding agents, they accelerate it less, and skilled developers still design and implement far better backends than inexperienced ones who use coding agents.

Infrastructure. Agents are even less effective in tasks like scaling an ecommerce site to 10K active uses while maintaining 99.99% reliability. LLMs' knowledge is still relatively limited with respect to infrastructure and the complex tradeoffs good engineers must make, so I rarely trust them for critical infra decisions. Building good infrastructure often requires a period of testing and experimentation, and coding agents can help with that, but ultimately that’s a significant bottleneck where fast AI coding does not help much. Lastly, finding infrastructure bugs — say, a subtle network misconfiguration — can be incredibly difficult and requires deep engineering expertise. Thus, I’ve found that coding agents accelerate critical infrastructure even less than backend development.

Research. Coding agents accelerate research work even less. Research involves thinking through new ideas, formulating hypotheses, running experiments, interpreting them to potentially modify the hypotheses, and iterating until we reach conclusions. Coding agents can speed up the pace at which we can write research code. (I also use coding agents to help me orchestrate and keep track of experiments, which makes it easier for a single researcher to manage more experiments.) But there is a lot of work in research other than coding, and today’s agents help with research only marginally.

Categorizing software work into frontend, backend, infra, and research is an extreme simplification, but having a simple mental model for how much different tasks have sped up has been useful for how I organize software teams. For example, I now ask front-end teams to implement products dramatically faster than a year ago, but my expectations for research teams have not shifted nearly as much.

I am fascinated by how to organize software teams to use coding agents to achieve speed, and will keep sharing my findings in future posts.

[Original text: https://t.co/rnnVWqebVe ]