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Most founders want to build SaaS products but struggle to find strong ideas. The secret? Stop guessing and start listening where real conversations happen. 🎯 I’ve curated a list of 50 highly active platforms where thousands of builders, founders, and users interact daily — from Indie Hackers, Product Hunt, and Hacker News to directories like BetaList, Uneed, SaaSHub, AlternativeTo, and a grouped Reddit hub (covering r/SaaS, r/SideProject, r/startups, r/Entrepreneur, and more). On each platform, you can discover validated product ideas directly from user pains, feedback threads, "what tool do you use" discussions, and launch comments. Different platforms surface different types of ideas — from micro-SaaS to enterprise tools. 🔗 FULL LIST OF 50 PLATFORMS WITH LINKS: 1. Indie Hackers - https://lnkd.in/e_hmm5aS 2. Product Hunt - https://lnkd.in/e5icp8VS 3. Reddit (SaaS communities) - https://www.reddit.com (r/SaaS, r/SideProject, r/startups, r/Entrepreneur, r/micro_saas, r/indiehackers, r/smallbusiness, r/GrowthHacking, r/Business_Ideas, r/Startup_Ideas, r/alphaandbetausers, r/roastmystartup, r/buildinpublic, r/thesidehustle) 4. Hacker News - https://lnkd.in/ewTwUanS 5. BetaList - https://betalist.com 6. Uneed - https://www.uneed.best 7. SaaSHub - https://saashub.com 8. AlternativeTo - https://alternativeto.net 9. There's An AI For That - https://lnkd.in/e6NYCtRM 10. Launching Next - https://launchingnext.com 11. Microlaunch - https://microlaunch.net 12. Peerlist - https://peerlist.io 13. Fazier - https://fazier.com 14. DevHunt - https://devhunt.org 15. TinyLaunch - https://tinylaunch.com 16. Startup Stash - https://startupstash.com 17. AppSumo - https://appsumo.com 18. G2 - https://www.g2.com 19. Capterra - https://www.capterra.com 20. SideProjectors - https://lnkd.in/ex2JFb6q 21. DEV Community - https://dev.to 22. WIP.co - https://wip.co 23. LaunchRocket - https://launchrocket.io 24. SaaStr Community - https://lnkd.in/eqyFSpza 25. StackShare - https://stackshare.io 26. Futurepedia - https://www.futurepedia.io 27. Toolify - https://www.toolify.ai 28. OpenAlternative - https://openalternative.co 29. PitchWall - https://pitchwall.co 30. StartupBase - https://startupbase.io 31. Acquire.com - https://acquire.com 32. Flippa - https://flippa.com 33. HackerNoon - https://hackernoon.com 34. Wellfound (AngelList) - https://wellfound.com 35. Crunchbase - https://www.crunchbase.com 36. SourceForge - https://sourceforge.net 37. Software Advice - https://lnkd.in/eWZQjAku 38. TrustRadius - https://lnkd.in/eNtNBXTJ 39. GetApp - https://www.getapp.com 40. Slant - https://www.slant.co 41. MakerPad - https://www.makerpad.co 42. NoCode Founders - Search "NoCode Founders community" 43. MicroConf Connect - Search "MicroConf Slack" 44. Ramen Club - Search "Ramen Club community" 45. Product-Led Alliance - Search community site 46. LaunchDir - https://www.launchdir.com 47. Tiny Startup - Search "Tiny Startup directory" 48. Open Launch - Search "Open Launch platform" 49. ListMySaaS - https://listmysaas.com 50. Awesome Directories - https://lnkd.in/eAudMrzb Which platform do you use most for SaaS ideas? Share below 👇 #SaaS #StartupIdeas #IndieHackers #ProductHunt #Entrepreneurship

Had the pleasure of attending SaaStr this year and, hearing from them, it's truly incredible everything they have created in such a short amount of time with a lean team. Check it out!

The line in the SaaStr piece that stuck with me: "just give the agents a Postgres database and let them rip." Jason's right to push back on it, and the reason isn't technical romance about CRM being irreplaceable. It's that a raw database has no opinion about your business. CRM and ERP aren't valuable because they store rows. They're valuable because thirty years of arguments got baked into the schema. Opportunity stages. Revenue recognition rules. The difference between a booking and billing and cash. SAP FICO is ugly precisely because it encodes tax logic across 40 countries that nobody on your team fully understands anymore. Hand an agent a blank Postgres and you haven't removed that complexity. You've asked the agent to reinvent it, live, with no guardrails and no audit trail. I've watched clean data models rot in 18 months when there was no system enforcing what "closed-won" actually means. Now imagine that with twenty agents writing, each with a slightly different definition. The agents don't need less structure. They need more. They need a system that says no. Where I'd love to be proven wrong: for teams already running lean on Salesforce or NetSuite, have you actually let agents write directly to the record — or only read? #CRM #EnterpriseAI #SaaS #ERP

Median private SaaS growth fell from 30% to 25% in a year, and SaaS Capital's newest survey shows bootstrapped scale-ups sliding further, 20% to 15%. Our projection bends toward an 18-20% floor because one revenue stream survives maturation: expansion from customers you already have. (KeyBanc's smaller panel shows re-acceleration; we weight the larger sample and say so on the slide.) Which is why the second chart is the whole strategy. McKinsey found top-quartile NRR companies trade at 24x revenue while bottom-quartile peers trade at 5x. One metric, a five-fold valuation gap. Yet most SaaS marketing budgets still point almost everything at strangers while the zero-CAC audience, existing customers, gets an onboarding email sequence and silence. The efficiency era makes it sharper: 83% of bootstrapped SaaS companies run at or near breakeven against 52% of VC-backed. Every marketing dollar now answers a payback question, which favors compounding channels (content, community, customer marketing) over auction clicks that reset to zero monthly. And the AI slide has a zero-length bar on it: not one company in KeyBanc's survey plans to cut AI spend. When adoption is unanimous, 'AI-powered' stops differentiating. Market the measured outcome; buyers are habituated to the word. Swipe for the charts. Data: SaaS Capital, KeyBanc Capital Markets, McKinsey & Company, Bessemer Venture Partners. Related benchmark publishers: ChartMogul, Maxio, Paddle, High Alpha, SaaStr Ai, Scale Venture Partners, Software Equity Group, Gartner. Projections: Emulent Digital Marketing analysis except where noted. #SaaS #SaaSMarketing #B2BSaaS #NetRevenueRetention #StartupGrowth #MarketingStrategy

Got a pretty good cold email this morning. That's not the headline; that's every day in the Age of AI. But.. Then they asked me if I already knew anybody at this company. I said, the CEO and the CMO. I literally just saw both of them at SaaStr. They said, 'Who?' 🤦‍♀️ Here's the thing: I think a human made this mistake. Ask any of our 4 AI sales agents we use, and they know their buyer (and their team) cold. The "human touch" only counts if the human does the homework. What's your guess 👇

New!! The 20 Minute Test in VP Hiring. Maybe All Hiring.: Investments rarely work out if you don't believe within the first 20 minutes I think I'm there on hiring, too now If you don't believe at least by minute 20 of the first Zoom that they're the VP for you … I'd pass — Jason ✨👾SaaStr.Ai✨ Lemkin (@jasonlk) April 3, 2024 So much has changed... Continue Reading

SaaStr just replaced 10 years of Marketo infrastructure for $14. They killed a $10K app in one hour. And they did it with AI agents working autonomously while their team slept. The setup: Replit's MCP beta integrated with Claude, creating an "AI VP of Product" where two models—Claude Opus and Replit Sonnet—debate features, share code, and ship updates without human intervention. The result: 20+ hours of concurrent development work per day. This isn't a demo. It's production software handling real business processes. **The Bottleneck Has Shifted** Most founders still think the question is "can we build this fast enough?" But SaaStr's experiment proves the real question is now "can we manage everything we're building?" Their team hit a wall—not in development capacity, but in operational oversight. They can ship faster than they can absorb what they've shipped. When AI can replace a $10K application in under an hour, the constraint isn't code generation anymore. It's governance, maintenance, and architectural coherence. **Why Multi-Model Orchestration Matters** Single-model workflows are obsolete. The unlock isn't one AI coding faster—it's multiple models working in tandem, checking each other's output, and managing goal-seeking behavior autonomously. SaaStr's two-model system debates technical decisions and reviews code before shipping. That peer review loop is why they're shipping production systems, not prototypes that break in week two. For founders: if you're not running multiple models that validate each other's work, you're leaving 90% of AI's potential on the table. **How TechAhir Builds Working, Sellable Products in Days** We've operationalized exactly what SaaStr discovered through experimentation: AI velocity must be paired with senior human oversight. Our process combines three disciplines: **Speed WITH Discipline, Not Vibe Coding** We use AI to amplify development speed, but every architectural decision is vetted by senior engineers. No autonomous agents shipping without guardrails. No technical debt accumulation disguised as velocity. **Senior Developers as Project Leaders and the Human Guardrail** AI generates code. Humans set standards, review architecture, and ensure what ships today won't break tomorrow. Our teams are led by engineers who've built production systems at scale—they know what good looks like. **Virtually Zero Defects via Customized-Model QA** We run multi-model validation loops before anything reaches production. One model builds, another reviews, a third tests edge cases. This peer-review architecture is why we ship working products, not prototypes that need six months of fixes. **The Real Takeaway** You can now ship working, sellable MVPs in days. But speed without discipline creates a maintenance nightmare. The teams… [Get your MVP built in 3 days](https://lnkd.in/eqU3wDDH) #AIAgents #MVPDevelopment #StartupSpeed #ProductDevelopment #TechLeadership

SaaStr just replaced 10 years of Marketo infrastructure for $14. They killed a $10K app in one hour. And they did it with AI agents working autonomously while their team slept. The setup: Replit's MCP beta integrated with Claude, creating an "AI VP of Product" where two models—Claude Opus and Replit Sonnet—debate features, share code, and ship updates without human intervention. The result: 20+ hours of concurrent development work per day. This isn't a demo. It's production software handling real business processes. **The Bottleneck Has Shifted** Most founders still think the question is "can we build this fast enough?" But SaaStr's experiment proves the real question is now "can we manage everything we're building?" Their team hit a wall—not in development capacity, but in operational oversight. They can ship faster than they can absorb what they've shipped. When AI can replace a $10K application in under an hour, the constraint isn't code generation anymore. It's governance, maintenance, and architectural coherence. **Why Multi-Model Orchestration Matters** Single-model workflows are obsolete. The unlock isn't one AI coding faster—it's multiple models working in tandem, checking each other's output, and managing goal-seeking behavior autonomously. SaaStr's two-model system debates technical decisions and reviews code before shipping. That peer review loop is why they're shipping production systems, not prototypes that break in week two. For founders: if you're not running multiple models that validate each other's work, you're leaving 90% of AI's potential on the table. **How TechAhir Builds Working, Sellable Products in Days** We've operationalized exactly what SaaStr discovered through experimentation: AI velocity must be paired with senior human oversight. Our process combines three disciplines: **Speed WITH Discipline, Not Vibe Coding** We use AI to amplify development speed, but every architectural decision is vetted by senior engineers. No autonomous agents shipping without guardrails. No technical debt accumulation disguised as velocity. **Senior Developers as Project Leaders and the Human Guardrail** AI generates code. Humans set standards, review architecture, and ensure what ships today won't break tomorrow. Our teams are led by engineers who've built production systems at scale—they know what good looks like. **Virtually Zero Defects via Customized-Model QA** We run multi-model validation loops before anything reaches production. One model builds, another reviews, a third tests edge cases. This peer-review architecture is why we ship working products, not prototypes that need six months of fixes. **The Real Takeaway** You can now ship working, sellable MVPs in days. But speed without discipline creates a maintenance nightmare. The teams… [Get your MVP built in 3 days](https://lnkd.in/eqU3wDDH) #AIAgents #MVPDevelopment #StartupSpeed #ProductDevelopment #TechLeadership

The obvious way to build a vertical SaaS company is to hire from inside the industry. Procore tried it and it didn't work. The pitch is intuitive. A sales rep who has stood on a jobsite will speak the customer's language, ask better questions, build trust faster than a generalist parachuted in from a horizontal SaaS company. Over 23 years, Procore learned the opposite. Sales motion is its own discipline. It doesn't transfer easily from operating inside the industry. Construction veterans who came in as sales reps tended to struggle. The model that worked: hire generalists into sales roles and teach them construction. Bring industry experts in as sales engineers and product specialists instead. Two different roles, two different hiring profiles, one pair carrying the translation gap between platform capability and jobsite reality. Tooey Courtemanche, Procore's founder, put the structural half on the operational record at the company's Q3 2024 earnings call: "On the technical roles, interestingly enough, a fair number of people that we're hiring for those technical roles come from industry." The complement half ran in a 2025 SaaStr Ai interview with Jason M. Lemkin: generalists into sales, industry experts into technical positions. Not the obvious arrangement, and not the one most vertical SaaS companies are running. Inside the Function takes apart how one elite company runs one operating discipline. New issue every Wednesday. This Wednesday's issue takes the pattern apart in full: how the pair actually operates, why the GTM evolution of late 2024 expanded the technical-role layer across every buyer persona, and the structural reasons the design is hard for smaller vertical SaaS companies to replicate.

Median private SaaS growth fell from 30% to 25% in a year, and SaaS Capital's newest survey shows bootstrapped scale-ups sliding further, 20% to 15%. Our projection bends toward an 18-20% floor because one revenue stream survives maturation: expansion from customers you already have. (KeyBanc's smaller panel shows re-acceleration; we weight the larger sample and say so on the slide.) Which is why the second chart is the whole strategy. McKinsey found top-quartile NRR companies trade at 24x revenue while bottom-quartile peers trade at 5x. One metric, a five-fold valuation gap. Yet most SaaS marketing budgets still point almost everything at strangers while the zero-CAC audience, existing customers, gets an onboarding email sequence and silence. The efficiency era makes it sharper: 83% of bootstrapped SaaS companies run at or near breakeven against 52% of VC-backed. Every marketing dollar now answers a payback question, which favors compounding channels (content, community, customer marketing) over auction clicks that reset to zero monthly. And the AI slide has a zero-length bar on it: not one company in KeyBanc's survey plans to cut AI spend. When adoption is unanimous, 'AI-powered' stops differentiating. Market the measured outcome; buyers are habituated to the word. Swipe for the charts. Data: SaaS Capital, KeyBanc Capital Markets, McKinsey & Company, Bessemer Venture Partners. Related benchmark publishers: ChartMogul, Maxio, Paddle, High Alpha, SaaStr Ai, Scale Venture Partners, Software Equity Group, Gartner. Projections: Emulent Digital Marketing analysis except where noted. #SaaS #SaaSMarketing #B2BSaaS #NetRevenueRetention #StartupGrowth #MarketingStrategy

New!! Dear SaaStr: Is it OK to Modify the Standard SAFE Form?: Dear SaaStr:  Is it OK to Modify the Standard SAFE Form? Ideally don’t.  If you do — at least be transparent and crystal clear on what changes you are making.  SAFEs require a high degree of trust to work.  Hiding changes undermines that trust. There’s an issue I see blow up several times now as... Continue Reading

This Week in SaaS July 14 – 20, 2026 You can read the full breakdown here: https://lnkd.in/dgV-5YjA Here's what stood out this week👇 💸 Big SaaS VC Rounds ↳ Fireworks AI raised $1.505B Series D at a $17.5B valuation. Daily token volume climbed from 15 trillion to over 40 trillion year over year and the platform passed a $1B annualized run rate ↳ Meshy raised $400M Series B at $1.38B for generative 3D modeling into games, film and spatial hardware ↳ Emergent raised $130M Series C at $1.5B. Over 12 million apps built on the platform in a year, many by non-technical solo operators ↳ Spectro Cloud raised $100M Series D led by Goldman Sachs Alternatives for AI infrastructure management ↳ Flex raised $70M at $1.2B for AI-native private banking. Annualized revenue tripled and payment volume passed $10B ↳ InstaLILY raised $60M Series B with Home Depot Ventures and United Rentals for AI forward-deployed engineers ↳ Sable raised $45M co-led by Sequoia and 8VC for autonomous AI customer-facing employees 🤝 SaaS M&A Deals ↳ SAP completed its acquisition of Prior Labs with a €1B+ committed investment. The bet: enterprise decisions run on tables and structured records, not large language models ↳ ZetaDisplay acquired retailmediatools, adding retail media planning to its digital signage platform 🧠 The takeaways Software isn't dead. Workflow automation is what's at risk. → Rory O'Driscoll argues roughly 10% of a large pre-GPT portfolio was effectively dead on arrival when ChatGPT shipped. → If your product only automates a workflow, move up the stack or expect to get rolled. Your agents should beat your best rep. Not match your average one. → An agent matching median human performance isn't a product. → Deployment standards should be set against top performers. When the model becomes a commodity, the moat moves → Operators across six verticals landed on the same conclusion. Everyone has frontier model access now. → Defensibility comes from the data surface and the workflow you own end to end, not from which model you call. Write the spec before you build the agent → SaaStr published the full 20-page spec behind their AI VP of Marketing after five months in production. → Output quality tracks input detail. Invest in the spec. The through line: the model isn't your advantage. The data you own, the workflow you control and the standard you hold your agents to...that's the whole game now. Today I run two private communities that might help you: ▪️ SaasRise: for SaaS CEOs and founders scaling from $1M to $100M in ARR ▪️ GrowthRise: for experienced B2B marketing leaders and founders under $1M leading their own GTM efforts Links to apply in the comments below 👇

Harry Stebbings' $600K Salesforce Story Sounded Familiar. We'd Already Done It For a Client. Harry Stebbings shared it on the 20VC x SaaStr episode this week, and it's been making the rounds since. A CEO told him their team replaced Salesforce with a CRM they vibe-coded themselves. Built for their own workflows, connected directly to their AI agents, and live in three weeks. The $600,000 annual Salesforce bill disappeared. We read that story and immediately thought of one of our own clients. They were paying a significant Salesforce subscription every year for a CRM that handled only a fraction of what they actually needed. We built them a custom CRM around the way their sales team worked instead of forcing them into a generic platform. Within weeks of going live, they dropped their Salesforce subscription. Stebbings also shared another example on X: the CEO of a $10 billion public company said their Chief of Staff replaced software costing $1.2 million annually with an internally built solution completed in just three weeks. Not everyone agrees this approach scales. Some SaaStr contributors argued that most companies still rely on Salesforce for its integrations, app ecosystem, and collaboration capabilities. That's a fair point. For large organizations with complex workflows and dozens of integrations, replacing an enterprise CRM overnight isn't realistic. But one thing is becoming clear: the cost of building custom software has dropped dramatically. A CRM, internal tool, operations dashboard, or workflow that once required months and massive budgets can now be built in weeks with the right team and AI-powered development. Where this approach actually works The businesses seeing real wins with this approach tend to share a pattern: ✓ The team is small enough that a custom system doesn't need to be a collaboration platform for hundreds of users ✓ They're only using a small slice of what the expensive platform actually offers ✓ Their workflows are specific enough that off-the-shelf software forces awkward workarounds ✓ They have engineers or a partner who can build it properly, not just fast Miss those conditions, and a quick build can become a maintenance problem. Get them right, and you eliminate a recurring software cost that may no longer make business sense. This is the work we do at iTechnolabs Our client's CRM wasn't built in three weeks. It was carefully planned, developed around their actual sales process, and integrated with the tools they already depended on. The outcome was the same: a Salesforce subscription they no longer needed and a system built specifically for their business. If a large part of your budget goes toward a CRM, support platform, or internal tool you've outgrown, it's worth exploring whether a custom solution makes more sense. Get in touch with iTechnolabs Inc. Tell us what you're paying for and what you actually use, and we'll honestly tell you whether a custom AI-powered solution is the right fit.

Most CS teams know which accounts need attention. The problem is proving it when the data lives across six systems that don’t talk to each other. Salesforce. Amplitude. Jira. Slack. Backstory. Public sources. Pulling it all into one defensible tiering model used to take weeks of cross-functional back-and-forth. Haya Kamal, Head of Customer Success at Backstory, did it herself in days. At the SaaStr Ai day tomorrow, she’ll show how she used Claude to reconcile signals across those tools, build a four-tier account model with revenue projections and reprioritize resources around the accounts with the most headroom. This is a working session, not a slide tour. Real backend. Real iterations. And the exact sequence: which tools, in what order, and where a human still has to make the call. Wednesday, July 22nd, 2026 | 09:00 - 09:30 AM PDT Come see it live! Register now: https://lnkd.in/e_Cz5Apd #SaaStrAI #AI #RevenueAI #Backstory

New!! 5.4M Impressions Driving 11,749 to Their Signup Form: What Advertising on SaaStr.AI Media Actually Delivers: Most B2B media buys are … a black box. You sign up, wire the money, the ad “runs,” and 60 days later you get a PDF with an impressions number and no way to check any of it. You have no idea if a single real buyer even saw it. We do it differently at... Continue Reading

New SaaStr Fund portfolio company CRO his first week on the job: Note: he also started before he started. We’ve talked a lot on SaaStr about how to make that critical hire: the VP Sales.  I&#…

In six months, Jobright.ai went from $5M ARR to approaching $10M. But the bigger milestone was not the revenue. It was completing the other half of the hiring market. We entered 2026 helping job seekers across the U.S. and Canada find fresher opportunities, understand their fit, navigate sponsorship constraints, and avoid wasting time on roles where they had little chance. Then the year started moving fast: → February: Crossed $5M ARR. → March: Reached 2M+ users. → April: Grew to 3M+ users with a team of fewer than 10. → May: Brought our employer platform to SaaStr with one message: Hire Top Talent at AI Speed. → June: Expanded Jobright TNT to 52,000+ vetted builders and 150+ hiring companies. → Early July: Approaching $10M ARR. The numbers matter, but the product evolution matters more. We saw the same problem from the other side.  Hiring teams were struggling with the same system from the opposite direction: AI made application pipelines exploded, and recruiters had to find real signal inside thousands of increasingly similar applications. That is why Jobright is evolving beyond a job-search platform. For candidates, we provide clarity, stronger matching, and better access.  For companies, we provide qualified, high-intent talent with less noise and more context. The future of hiring should not be more applications or more resumes. It should be a better connection between the right person and the right team. #Hiring #AI #Recruiting #FutureOfWork #JobSearch #Startups #Jobright

Q2’2026 @ Hyperline :) I shared an informal Q2 update with our partners last week. Feedback was so good that I decided to share the public version here too. TL;DR: - strongest quarter to date - 350+ customers now using Hyperline - real momentum in the US - much smarter product - partner ecosystem becoming a true GTM engine - but also… our annual offsite in the South of France, the World Cup in NYC, the Knicks parade, and heatwaves in Paris and NYC 🥵 We welcomed a new batch of ambitious companies, incl. AI companies backed by tier-1 global investors, fast-growing European businesses now scaling in the US, companies valued $1B+. (and many more we can't share there yet!!!) The companies joining Hyperline are getting bigger, their business models more complex, and the problems they expect us to solve now go far beyond simply generating invoices. (which is *exactly* where we want to be) Product-wise, our AI vision is turning into very real use cases: 👾 MCP server to explore data and automate workflows through AI tools 🚨 Sentinel to continuously monitor what needs attention 🤝🏻 Customer Intelligence to surface churn risks and upsell opportunities much earlier We also launched our Rillet integration, deepened relationships with some amazing advisory partners (incl. Polaris Ops, Onside Accounting, 2CFinance, 28 North Consulting, Ocobo, RevOpsAI, Novutech and more) - helping us across implementations, leading to great collaboration between teams and intros going both ways. Together with our partners, we hosted 4 events in Q2: - Finance & Monetization Dinner in SF during Stripe Sessions with Northlane - CFO Dinner in SF during SaaStr week with Anrok and Quanta - RevOps Breakfast in NYC with Qobra - Finance Leaders Lunch in Paris with Fincome for PE-backed companies Thank you to everyone who sent a lead, made an intro, joined an event, or recommended Hyperline when we weren’t in the room. Let’s go for Q3.

For b2b marketers or media nerds, this is a best-in-class content + social playbook worth following, studying, and emulating. Consider this little media microcosm: If someone was starting a company in 2015, you would tell them to read: TechCrunch, VentureBeat, and maybe Saastr as a deep cut. If someone is starting a company today, you tell them to follow Peter Walker at Carta, Matt Schulman at Pave, and maybe the Mercury blog for founder stories. i am continuously flabbergasted by the level of high-density information people like Peter give away for free as he essentially builds his own mini-media company on behalf of Carta. It has put the Carta brand front + center of any and all founders (Peter has 170k followers, and considering how deeply niche/technical his content is, you can bet they are Carta's ICP). This is a playbook worth following, even if you operate in a completely different industry.

Most of the alarming SaaS statistics going around are true. That is not the interesting part.   I spent a morning checking them against their sources, expecting to debunk a few. Nearly all of them held.   Bain found that about 60% of Google searches now end without a click to any website. Pew measured what happens when an AI summary appears above the results: clicks on ordinary links nearly halve, from 15% to 8%. The channel that built a generation of software companies is quietly closing.   Meanwhile the cost of growth keeps rising. To win $1 of new annual recurring revenue, the median SaaS company now spends $2 on sales and marketing. The least efficient quarter of companies spend almost $3. That is Benchmarkit's data. And Alexander Group found 3 out of 4 software companies reporting declining retention, part of a slide in gross retention now running three years deep.   Even the giants are telling us something. SaaStr's analysis estimates that most of Salesforce's recent growth came from price rises, not new customers.   So the numbers are real. Here is the interesting part.   Every one of them is also an M&A diligence question when it is time to sell your business. Buyers stopped paying for growth some time ago. They pay for efficient growth: payback, retention, distribution that does not rent its audience from an algorithm.   Which means this is not only a growth problem. It is a valuation event, arriving early.   The founders who treat it that way, now, while it is still theirs to fix, will be the ones with options later.