manveerc

Your comment hits on a broader tension I see a lot, not just here but in business strategy in general. It's the divide between compelling, experience-based narratives and empirical evidence. I think both are essential.

The author has presented a fantastic and intuitive narrative with the "BUYER-PULL" model. Your analogy is spot-on: you can't sell 16 meals a day to someone who only needs three. The qualitative insight is powerful.

My request for data comes from the next step. How do we know this narrative is not just a "just-so story"? How much does this effect matter on the margin? In the complex world of B2B sales, where needs aren't always as clear as hunger, can "push" tactics sometimes be effective at helping a buyer crystallize a latent need?

Asking for metrics like close rates isn't meant to demand an impossible standard of scientific proof. Instead, it's an attempt to test the boundaries of this framework and understand its real-world impact. Great insights often come from quantifying the effects of a powerful story.

This is super cool. It is great except for two things

1. Don’t want the notebooklm branding 2. Data processing. Some data I will be sharing will be private, so want to make sure it will not be used for training models.

Many SPVs were available for recent funding rounds, but my biggest gripe was the excessive fees layered on top of them.

More importantly, we should ask who will be left holding the bag when this bubble bursts. For now, investors are getting their money back through acquisitions. Founders with desirable, traditional credentials are doing well, as are early employees at large AI startups who are cashing out on the secondary market. It appears the late-stage employees will be the ones who lose the most.

Link is not publicly accessible

Is there any data that you can share beyond anecdotal claims? For starters would love to see following

- Close-rate differences between push vs. pull strategies.

- Win rates for deals where urgency was “created” vs. “aligned with existing urgency.”

Thanks, I will check it out. Does it allow you to create longer(5+ mins) videos?

Is PE your target user? And is deal sourcing the primary usecase?

If yes, I am guessing they would be looking for understanding the fundamentals of the company, so start by looking at the SEC filings (assuming public company). Essentially helping them narrow down the entire universe into the set of companies that are interesting.

Very nice! Is It intended to be an alternative to MotherDuck?

Yay! Now I can message my friends while driving my car. I needed this so much.

Congratulations! As a bike noob, this was very informative.

PS: I see a bunch of feedback along the lines of,”Why did you build this?” Please ignore. It's a passion project. Do whatever gives you energy.

That is orthogonal to the point I am making. I also don’t like the business but that doesn’t mean he is not a great leader

I don’t think it would have gotten this big if it was not for Zuckerberg. I was at Facebook, 2012-13, and had a few interactions with him. Since then I have worked at Dropbox and Confluent. Met CEOs of few other big companies of this era. None of them are in the same league as him. His clarity and dedication are unparalleled.

I wasn't aware that Bihar, Mizoram and Nagaland were dry states too. Growing up I lived in Madhya Pradesh and Maharashtra (border states to Gujarat), so was mostly aware of them. My friends who lived and worked in Ahmedabad would frequently leverage the 30 day loophole or go to neighboring states. It was never a big deal, like the way it is portrayed in the article.

Yeah that’s what my understanding is too about NotDiamomd. There are a bunch of similar products out there.

The article ignores the crucial context: Gujarat is the only dry state in the entire country. This is why this story looks like another piece of Western media propaganda.

I have tried it, maybe I am bad at using it but my experience has been pretty bad with it

No this is for customer facing dashboards. We are operating in an agency model, sheets is great because of the flexibility. But for all those traditional time series graphs it is a bit cumbersome when data is across multiple sheets and tabs

Yes that’s the immediate plan

Congratulations on the launch, looks great. Do you also support Google Sheets? We are building our dashboards in Sheets right now and that’s a big pain. Looking for alternatives.

In the context of coding agents, they do simulate “reasoning” when you feed them the output and it is able to correct itself.

No, but I need to look that up now!

Very nice! We had a use case where we needed to convert some images into SVGs. Since AI performed poorly at that task, we had to spend time reading and understanding the SVG code. This makes things much easier.

“Inverting inertia” is a great framing, but it mostly applies to one type of startup. Sequoia’s Arc framework shows there are three paths: Hair on Fire (urgent pain, momentum matters), Hard Fact (people live with the pain, you have to change habits), and Future Vision (people don’t even believe it’s possible, you need to build credibility). Doing unscalable things is vital in Hair on Fire, but in the other two paths the playbook is more about reframing reality or creating belief before momentum even starts.

Awesome, will look forward to it!

Congratulations! Is there a mobile version as well, especially for Android?

For most people, this is a tool we use daily. What’s the reasoning behind choosing a weekly usage limit instead of a daily one? Is it because the top 5 percent of users tend to have spiky usage on certain days, such as weekends? If that’s the case, has there been any consideration of offering different usage tiers for weekdays and weekends?

I’m just curious how this decision came about. In most cases, I’ve seen either daily or monthly limits, so the weekly model stood out.

I believe it’s the same study where developers were new to the coding tools, the one developer who had some experience actually saw a significant boost in productivity.

> On the other hand, we now were missing a Core Engineering team, and there’s no better group of AI engineers than the lineup Cognition has assembled.

This is harsh on rest of the eng team at Windsurf. Agreed the founders who went to Google were good, but this is saying rest of the team is not good

> They seem to be more focused on workflows and pulling together context (also a very important problem in the space), we we've put more of a focus on root causing infra issues specifically.

So just to clarify, are you saying that Parity is focused on infrastructure issues, while something like Onegrep addresses the broader problem by providing context?

> I haven't heard of Beeps and can't find it, could you share the URL?

https://www.beeps.co/

Congratulations on the launch! I'm curious—how is what you're building different from other AI SRE solutions out there, like Cleric, Onegrep, Resolve, Beeps, and others?