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Lovable might be dying. Web traffic has declined ~50% from 35.4M in June to 19.1M in September. This trend can be seen across other big vibe coding tools such as Replit and Bolt. Here’s why I think this is happening: 1) The viral wave has passed: Spring/summer hype (esp. Lovable’s June peak) pulled in lots of non-devs on monthly plans. They experimented and never returned. Cultural convo has also shifted from “AI can build an entire app” back to a more realistic view of AI’s limitations. 2) Power users eating up compute: A small group of power users burned through compute budgets. To protect margins, platforms throttled usage and raised prices. That scared away casual users. 3) Lovable’s need to monetize: After raising $200M, Lovable raced to monetize, tightening free credit limits and ending generous 50% discounts. The friction dulled its appeal for casual builders. 4) v0's pricing change: In May, v0 lost 500k (10%) of web traffic after moving from $20/month to usage-based credits. Casual users found their balance disappearing in hours, leading to outrage. 5) Replit’s missteps: Replit once thrived on its free tier and always-on Repls. But over the years, free education plans discontinued, always-on removed from basic plans. A high-profile AI agent failure occurred in July (accidentally deleting a live database) and user trust took a hit. 6) AI coding losing its novelty: AI coding is being absorbed into mainstream tools. GitHub Copilot, Cursor, and VS Code integrations keep developers in their IDEs, instead of web-first “vibe coding” sites. Google’s Firebase Studio also launched AI-powered app building with Gemini, eating into the traffic of these sites. However, new entrants like Emergent have managed to keep growing despite bigger players losing traffic. It might be still in its hype phase - YC acceptance, fresh funding has helped it scale. The real test will be whether it avoids the same hype to drop-off curve. Vercel’s v0 has also seen an increase in traffic likely due to its new Marketplace and deeper Vercel integrations. They also raised funding at the end of September, which could have resulted in an increase in web traffic. I wonder how players like Lovable, valued at a billion dollars, will maintain growth and valuation.

We just hit $4M ARR. This was the hardest $1M marker we've reached so far. 5 key lessons learned from this journey: 1) Prioritize recruiting - Our team is spread thin now due to hiring slowly. So, spending more time on recruiting great engineers and GTM talent. 2) Be proactive with current customers - We are just over a year into launch and now have to deal with churn. So we need to ensure customer happiness and awareness of new products. 3) Build faster - We know what customers want, focusing on that will reduce churn and increase satisfaction. 4) Keep focus on top of funnel - We have 5-6 sources of leads. The goal now is to get better leads rather than more leads. 5) Never slow down when you have momentum - It seemed like there was less urgency due to July/August malaise. This cannot happen again. Momentum is very important for a startup.

hiring recruiters at the early stage is like outsourcing top of funnel for sales. would you do it? No. but we're fine doing that for something we consider the most important function, recruiting. There's probably a lot of alpha to be achieved if founders treated early - mid stage recruiting like they do sales - and lead it directly/very involved. we're trying that now

Zuck’s actually losing the AI talent war, despite the $100M offers. Meta’s lost 140 AI engineers and researchers to OpenAI while only hiring 20 from them. Meta’s lost almost 300 AI engineers/researchers to other AI companies like OpenAI, Deepmind etc. This is 60% of all outflows in this space. So is Zuck really poaching employees are just getting back the talent he lost?

Best AI company names: 1) Decagon 2) Cognition 3) Anthropic 4) Applied Intuition 5) Perplexity

A great salesperson will have 3/4 of the below. A special one, all 4: -follow up discipline -supreme people / EQ skills -unassailable product and market knowledge -killer closing instinct

Palantir's ACV is $4 Million. 4x larger than any other public enterprise SaaS company. Their consulting style service with FDEs is clearly paying off. With just ~850 customers, their revenue is 2.8B. ACV’s of other public SaaS listed below: 1. Palantir: $4,078,064 2. ServiceNow: $1,222,619 3. Workday: $800,000 4. Snowflake: $322,610 5. Salesforce: $252,667 6. Microsoft Azure: $214,000 7. Cisco: $189,000 8. Oracle: $117,778 9. SAP: $85,425 10. Figma: $45,977 (only customers paying $10k+)

making sure customers see new products/features is a completely underrated skill and isn't prioritized enough. sending an email and checking the box isn't enough. we were able to give ourselves a shot at reviving 2 customers that were likely to churn. just because they discovered a new product offering that fit their needs. but we had to work hard on multiple channels to get their attention. tell your customers what you build. do whatever it takes to make sure they see it.

once you've closed enough contracts doing founder led sales (up to $1m - $3m ARR), that winning feeling/dopamine starts to taper and comes from building rapport with potential killer hires. wonder when that'll shift again.

We received 780 inbound demo requests in the last 60 days as a seed stage startup. Here are 4 things we did to make this happen: 1. Discipline - We have certain metrics to hit on channels and we make sure we hit them no matter what. This discipline ensures we have great weeks and good weeks of pipeline, but never bad weeks. The two weeks we let these slide, we saw the hit. 2. Long Game - We bet on inbound from the very beginning. We are active on channels our competitors haven’t tapped into, ensuring visibility everywhere our prospects might be spending their time. 3. Personal Brand - I started taking founder-led marketing seriously by writing content on LinkedIn consistently this year and I’ve gone from 1.5k to 13k followers in 8 months. 4. Power law posts - You can and should post consistently, but the reality is that a few posts will bring in 10x more attention and demos than standard posts. We went viral for our take on Lovable using Crustdata’s web traffic data and had good coverage due to our seed announcement. Opportunity: we’re hiring for 2 more account executives in our NYC office. There will be plenty of inbound leads to work off of, but also an opportunity to build out our outbound playbook with some already existing successful use cases.

The most popular YC X25 companies: 1. YouLearn - 1.8M visitors 2. Better Auth - 334k 3. Odapt - 78k 4. Zero - 60k 5. SixtyFour - 34k 6. Willow - 33k 7. PgDog - 22k 8. Text AI - 21k 9. Den - 19k 10. Sim Studio - 15k

grandmasters in chess don't see pieces and moves, they see a language great founders don't follow steps, they navigate thousands of small issues while maintaining big vision great sales people don't see prospects and follow ups, they orchestrate a process that flows great product people don't think in sprints, they think of harmonious interactions between users and product

Downstream effect of new H1b ruling = more work trials Candidates = have to make sure companies have runway an resourcefulness to shoulder extra costs (who knows if this will effect H1B renewals). Companies = is this person worth an effective extra $100k in salary? Both sides will want to make sure their investments are sound as the stakes are raised. There will likely be a lot more work trials with a shorter interview process.

Conferences are underrated growth levers for startups. I'm at my first major conference in 12 years and it's been eye-opening. In the world of AI slop, conferences are one of the best ways to form connections. My biggest takeaway: in-person is still huge, but you need a long thought-out gameplan to be successful.

We just hit $4M ARR. This was the hardest $1M marker we've reached so far. 5 key lessons learned from this journey: 1) Prioritize recruiting - Our team is spread thin now due to hiring slowly. So, spending more time on recruiting great engineers and GTM talent. 2) Be proactive with current customers - We are just over a year into launch and now have to deal with churn. So we need to ensure customer happiness and awareness of new products. 3) Build faster - We know what customers want, focusing on that will reduce churn and increase satisfaction. 4) Keep focus on top of funnel - We have 5-6 sources of leads. The goal now is to get better leads rather than more leads. 5) Never slow down when you have momentum - It seemed like there was less urgency due to July/August malaise. This cannot happen again. Momentum is very important for a startup.

Lovable might be dying. Web traffic has declined ~50% from 35.4M in June to 19.1M in September. This trend can be seen across other big vibe coding tools such as Replit and Bolt. Here’s why I think this is happening: 1) The viral wave has passed: Spring/summer hype (esp. Lovable’s June peak) pulled in lots of non-devs on monthly plans. They experimented and never returned. Cultural convo has also shifted from “AI can build an entire app” back to a more realistic view of AI’s limitations. 2) Power users eating up compute: A small group of power users burned through compute budgets. To protect margins, platforms throttled usage and raised prices. That scared away casual users. 3) Lovable’s need to monetize: After raising $200M, Lovable raced to monetize, tightening free credit limits and ending generous 50% discounts. The friction dulled its appeal for casual builders. 4) v0's pricing change: In May, v0 lost 500k (10%) of web traffic after moving from $20/month to usage-based credits. Casual users found their balance disappearing in hours, leading to outrage. 5) Replit’s missteps: Replit once thrived on its free tier and always-on Repls. But over the years, free education plans discontinued, always-on removed from basic plans. A high-profile AI agent failure occurred in July (accidentally deleting a live database) and user trust took a hit. 6) AI coding losing its novelty: AI coding is being absorbed into mainstream tools. GitHub Copilot, Cursor, and VS Code integrations keep developers in their IDEs, instead of web-first “vibe coding” sites. Google’s Firebase Studio also launched AI-powered app building with Gemini, eating into the traffic of these sites. However, new entrants like Emergent have managed to keep growing despite bigger players losing traffic. It might be still in its hype phase - YC acceptance, fresh funding has helped it scale. The real test will be whether it avoids the same hype to drop-off curve. Vercel’s v0 has also seen an increase in traffic likely due to its new Marketplace and deeper Vercel integrations. They also raised funding at the end of September, which could have resulted in an increase in web traffic. I wonder how players like Lovable, valued at a billion dollars, will maintain growth and valuation.

hiring recruiters at the early stage is like outsourcing top of funnel for sales. would you do it? No. but we're fine doing that for something we consider the most important function, recruiting. There's probably a lot of alpha to be achieved if founders treated early - mid stage recruiting like they do sales - and lead it directly/very involved. we're trying that now

Downstream effect of new H1b ruling = more work trials Candidates = have to make sure companies have runway an resourcefulness to shoulder extra costs (who knows if this will effect H1B renewals). Companies = is this person worth an effective extra $100k in salary? Both sides will want to make sure their investments are sound as the stakes are raised. There will likely be a lot more work trials with a shorter interview process.

making sure customers see new products/features is a completely underrated skill and isn't prioritized enough. sending an email and checking the box isn't enough. we were able to give ourselves a shot at reviving 2 customers that were likely to churn. just because they discovered a new product offering that fit their needs. but we had to work hard on multiple channels to get their attention. tell your customers what you build. do whatever it takes to make sure they see it.

The most popular YC X25 companies: 1. YouLearn - 1.8M visitors 2. Better Auth - 334k 3. Odapt - 78k 4. Zero - 60k 5. SixtyFour - 34k 6. Willow - 33k 7. PgDog - 22k 8. Text AI - 21k 9. Den - 19k 10. Sim Studio - 15k

grandmasters in chess don't see pieces and moves, they see a language great founders don't follow steps, they navigate thousands of small issues while maintaining big vision great sales people don't see prospects and follow ups, they orchestrate a process that flows great product people don't think in sprints, they think of harmonious interactions between users and product

Best AI company names: 1) Decagon 2) Cognition 3) Anthropic 4) Applied Intuition 5) Perplexity

A great salesperson will have 3/4 of the below. A special one, all 4: -follow up discipline -supreme people / EQ skills -unassailable product and market knowledge -killer closing instinct

Palantir's ACV is $4 Million. 4x larger than any other public enterprise SaaS company. Their consulting style service with FDEs is clearly paying off. With just ~850 customers, their revenue is 2.8B. ACV’s of other public SaaS listed below: 1. Palantir: $4,078,064 2. ServiceNow: $1,222,619 3. Workday: $800,000 4. Snowflake: $322,610 5. Salesforce: $252,667 6. Microsoft Azure: $214,000 7. Cisco: $189,000 8. Oracle: $117,778 9. SAP: $85,425 10. Figma: $45,977 (only customers paying $10k+)

Zuckerberg’s great Apple heist. With Apple falling behind on AI, Meta has raided Apple’s AI labs and walked away with 58 of its researchers and engineers Apple’s iPhone 17 launch was a flop. It wiped out $112B in their market value overnight. The reason is clear: Apple has fallen dangerously behind on AI. The consequence: In the last 3 years alone, 370+ researchers, engineers, and executives in AI/ML have left the company. Using Crustdata, we broke down Apple’s AI brain drain: 107 AI researchers, engineers, and execs went directly to other tech companies focusing on AI: Meta: 58 Google: 41 OpenAI: 12 Anthropic: 4 Inflows: From Meta: 24 From Google: 34 From OpenAI + Anthropic: 0 Apple is losing 2-3x more AI talent to other tech companies than it’s gaining.

Conferences are underrated growth levers for startups. I'm at my first major conference in 12 years and it's been eye-opening. In the world of AI slop, conferences are one of the best ways to form connections. My biggest takeaway: in-person is still huge, but you need a long thought-out gameplan to be successful.

Lovable reached $100M ARR with 0 sales people. But 20% of their team is made of Growth/GTM folks. There's a similar pattern across other popular vibe coding tools. There's a lot more importance given for growth and the importance of sales might be changing for scaling new companies: Sales becomes a tiny, highly-specialized function focused on closing only big enterprise contracts with a swarm of AI agents closing smaller deals and doing manual tasks.