AI & the agentic SaaS transition
AI-driven disruption of SaaS, including agent-native products, outcome-selling, changing cost structures, and vulnerable thin-feature tools.
34%
Best tweets about SaaS
50 Best Tweets About SaaS (2026)
A curated collection of the sharpest, most-shared X posts about SaaS—saved so you do not have to dig through the timeline yourself. Updated weekly.
Pricing, churn, positioning, and the metrics SaaS founders actually argue about in public.
- Creators
- 44
- Updated
Original Xholic analysis
What 50 top SaaS posts reveal
The supplied SaaS conversation is concentrated in AI and the agentic transition, metrics and unit economics, and churn and retention. Cited posts frame AI as both a route to outcome-based products and a threat to thin tools, seat-based pricing, and traditional valuation assumptions.
- Dominant tone
- Negative
- Median score
- 30.2
- Leading format
- Opinion
- Recent posts
- 36%
34% of posts
All-time engagement
42% of posts
Published in 90 days
Conversation map
The themes creators return to
Metrics & unit economics
ARR, MRR, growth rates, funnel metrics, unit economics, margins, and the limits of headline revenue as measures of traction.
32%
Churn, retention & customer quality
Churn, gross retention, customer quality, activation, support, and retention tactics as the core drivers of SaaS health.
30%
Valuation, funding & exits},{
SaaS valuation, revenue multiples, M&A, exit paths, public-market repricing, and venture-return expectations.
26%
Go-to-market & distribution
Customer acquisition through SEO, communities, outbound, content, affiliates, and demand-led distribution.
20%
Positioning, ICP & ROI
Positioning around a clear ICP, vertical niches, customer pain, ROI, outcomes, and differentiated messaging.
20%
Pricing & monetization
Pricing strategy, packaging, price transparency, premium positioning, and the move from seats to usage, credits, or outcome-based pricing.
20%
Moats & defensibility
Durable SaaS defensibility through proprietary data, integrations, workflow lock-in, compliance, operational complexity, and trust.
10%
Tone and stance
Sentiment Negative leads
Author posture Supportive leads
Performance benchmark
- Median likes
- 71
- Median reposts
- 5
- Median replies
- 14
- Median views
- 9.5K
Posts with media make up 40% of this collection. Their median all-time score is 39.8, compared with 21.9 for text-only posts.
Format mix
- Opinion 42% · score 11.2
- List 30% · score 42.7
- Announcement 20% · score 43.9
- Story 8% · score 24.3
Consensus and debate
Where creators agree, and where they do not
Shared view
Defensibility extends beyond the interface
These posts argue that thin features are vulnerable, while integrations, proprietary data, compliance, operational complexity, trust, and workflow lock-in can provide more durable defensibility.
Shared view
Metrics debate moves past ARR
Revenue alone is presented as an incomplete health signal. The posts emphasize activation, churn, retention, support, acquisition signals, and—by one proposed formula—gross profit adjusted for gross churn.
Shared view
ROI and customer pain anchor positioning
Posts emphasize measurable buyer value, urgent customer problems, and finding prospects where they already express demand rather than broadcasting product features alone.
Open debate
Agency versus SaaS remains contested
One post presents a productized agency as a capital-efficient route to agent SaaS, while others argue that consulting or agencies can be easier to monetize. Together, they contrast SaaS scalability aspirations with early execution and customer-acquisition challenges.
Open debate
Is SaaS collapsing or being repriced?
Posts range from collapse narratives tied to lower multiples and AI-enabled replication to arguments that SaaS remains viable when it has strong retention, production infrastructure, integrations, or compliance value.
Open debate
Outcome pricing meets cost pressure
These posts argue that AI can shift value from per-seat tools toward outputs or outcomes, while also flagging token and compute costs as a challenge to traditional SaaS-margin assumptions.
What performs
Patterns behind standout posts
Outliers favor actionable strategic narratives
The deterministic outliers include AI/agent playbooks, a resource-sharing post, an open-source service blueprint, and a venture-return argument. The five outliers span opinion, list, and announcement formats in the supplied analytics.
Lists package practical SaaS advice
Lists account for 30% of the supplied posts. Their cited examples package acquisition, distribution, acquisition-targeting, and operational tactics into practical playbooks.
Revenue quality drives the argument
Across churn-reduction, valuation, and traction-comparison posts, the argument is that headline ARR is insufficient without retention, churn, gross profit, and burn context.
Statistical standouts
- View standout post 1 Score 2461.0 · 81.52× median
- View standout post 2 Score 966.6 · 32.02× median
- View standout post 3 Score 903.0 · 29.91× median
- View standout post 4 Score 694.6 · 23.01× median
- View standout post 5 Score 241.3 · 7.99× median
Creator landscape
Who shapes this conversation
The five most represented creators account for 20% of the selected posts.
-
1. Hardik Gohil
@GohilHardy
2 posts
-
2. GREG ISENBERG
@gregisenberg
2 posts
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3. Jared Sleeper
@JaredSleeper
2 posts
-
4. Marc Lou
@marclou
2 posts
-
5. Nick Mehta
@nrmehta
2 posts
-
6. Rory O'Driscoll
@rodriscoll
2 posts
Isenberg links agents to validation
Greg Isenberg presents AI as both a product opportunity and a research mechanism: service delivery or acquired dormant products can reveal workflows, customer pain, and potential paths to an agent-native offering.
Lou emphasizes compounding and language
Marc Lou pairs a personal MRR-growth timeline with a positioning example where a move from web analytics to revenue attribution coincided with a reported conversion-rate increase.
Mehta focuses on incumbent transition
Nick Mehta describes incumbent SaaS leaders as managing churn, core-business growth, and an agentic pivot at once, and argues that the response must involve company-level value proposition and leadership.
Since the previous snapshot
What changed since Aug 7, 2026
- 70% of the selected posts remained.
- The creator count changed by +1.
- The leading sentiment remained stable.
How this analysis was made
Themes, sentiment, stance, and post format are classified per tweet. All counts, shares, medians, creator concentration, freshness, and performance comparisons are then calculated directly from the published snapshot.
Xholic's all-time score compares engagement while accounting for reach, post age, and creator consistency. It is used for relative comparisons within this collection.
This report analyzes the exact 50-post snapshot shown below. AI identifies editorial categories and drafts explanations; all statistics are calculated from the snapshot, and every narrative claim is checked against cited posts before publication.
Best SaaS tweets
Top SaaS tweets from 44 creators
Ranked 01–50
- 01
@gregisenberg ·
THE CLEAREST PATH TO A $10M+ SOFTWARE EXIT in 2 YEARS (with AI and agents) building an agency right now is one of the most interesting business moves the productized agency had its moment in 2022. it collapsed because scaling humans is a nightmare. inconsistent output, people quitting, margins getting crushed. most of the founders (and creators) who tried it got burned and moved on but the thesis was right. the labor problem is just solved now with AI, claude code, openclaw etc. here's the actual playbook i'd run today: pick one painful deliverable for one specific buyer. like SEO content for e-commerce brands doing $1M+ but not "marketing." or like ad creatives for DTC brands spending $50k/month on meta. one thing. one customer. that's it then you build the AI workflow behind it. you're selling an outcome on a monthly retainer. $3-5k/month. 80%+ margins because your cost is compute and a few hours of QA "BuT tHaT'S nOt a BiG bUsInnesS" okay but you're still swinging for the fences because the agency IS the research and development for your agent SaaS every client is paying you to figure out what to automate. you're learning what breaks, what scales, what customers actually want. by month 4 you know exactly what to productize. you build the software on top of the workflow you've already proven works and already have customers paying for agency funds the agent SaaS. SaaS scales without the agency overhead. the clients become your first software customers now let's talk about what this actually looks like financially year 1: 10 clients at $4k/month. $480k revenue. 2 people. maybe $80k in costs including compute, tools, one part time VA. you're taking home $400k between two people while building the software in the background year 2: you launch the software. your 10 agency clients are the first to convert. they already trust you. they've seen the output. you charge $800/month for the software version. now you have recurring software revenue AND the agency still running year 3: agency is winding down or running on autopilot. software has 200 customers at $800/month. that's $1.9M ARR. 2-3 person team. 85% margins. you are now a very attractive acquisition target the exit math is interesting. SaaS at $1.9M ARR with strong retention trades at 5-8x revenue. that's a $10-15M exit for something two people built in 3 years starting with zero VC CAVEAT: Startups are hard. A lot needs to go right. But from a framework perspective, I think this probably the lowest risk, highest reward option for lots of of folks and most of the businesses cost $0 to start basically this is the most capital efficient path to a software exit that exists right now happy building
- 02
@gregisenberg ·
I don't know why more people aren't buying dead SaaS companies and turning them into AI agent companies. 1. Use OpenClaw, Hermes, Perplexity Computer etc to build an automation that scans Product Hunt, Acquire, and app stores for dead SaaS products. Filter for ones that launched 2019-2024, had real customers, and went quiet. 2. Reach out to the founder on X. Most of them will respond within a day because they've been wanting to sell for a year and nobody asked. 3. Buy it. $5-30k. Sometimes less. 4. Export the database. Feed it to Claude or GPT. Map every workflow their customers were trying to do. 5. Read the support tickets. This is the goldmine. 200 strangers already told the last founder exactly what they needed and he couldn't deliver it. 6. Build an agent-native version that actually does those workflows instead of giving people a dashboard to do them manually. 7. Upload the old email list to Meta. Build a lookalike audience. Those old customers have moved on. You're not selling to them (realistically). You're using their data to find the next them. 8. Run $20/day ads targeting people who look exactly like the customers who already validated this market for you. 9. Build content around the exact pain points you found in the support tickets. Post on X. Post on YT. You already know what to say. 10. You now have the customer profile, the pain points, the pricing sensitivity, the churn reasons, and a lookalike audience. Your competitor who's starting from scratch has a landing page and a guess. The dead SaaS acquisition playbook is going to be one of the biggest quiet wealth builders of the next 5 years. Most SaaS products are a collection of workflows that can be rewritten as agent skills. Many will die. The top ones will pivot to agent companies. Build agent companies.
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@DeRonin_ ·
IDEA: reselling open-source repos to businesses. the play nobody talks about thousands of Github repos solve real business problems. free. open. production-ready and 99% of businesses will never find them here's how to turn ANY open-sourced solution into $2,000+/month per client: 1. find a tool that solves an expensive problem go to GitHub Trending. filter by stars, recent activity, and clear documentation. look for tools that replace something businesses currently pay $500-2,000/month for examples that exist right now: - CRM systems (Twenty, $0 vs Salesforce at $300/seat/mo) - helpdesk platforms (Chatwoot, $0 vs Intercom at $1,200/mo) - analytics dashboards (Plausible, $0 vs Mixpanel at $800/mo) - scheduling tools (https://t.co/gGrv3dpGMh, $0 vs Calendly Business at $480/mo) - email marketing (Listmonk, $0 vs Mailchimp at $600/mo) - form builders (Formbricks, $0 vs Typeform at $400/mo) - project management (Plane, $0 vs Jira at $700/mo for a team) these aren't toy projects. they have 10k-50k+ stars, active communities, and companies already running them in production 2. pick ONE niche don't be "we deploy open-source tools." be "we replace Salesforce for real estate brokerages" or "we set up private analytics for healthcare companies that need HIPAA compliance" the niche is where the margin lives. a generic deploy costs you $2k/client in support. a niche deploy costs you $200 because you've done it 15 times and everything is templated 3. deploy it on a $20-50/mo VPS Hetzner, Railway, Coolify, or a simple DigitalOcean droplet. Claude Code walks you through the entire setup. most of these tools have one-click Docker deploys your infrastructure cost per client: $20-50/month what you charge: $2,000-5,000/month (depends on the niche) everyone wins. they save money. you make money. the math is stupid simple 4. wrap it in their language not "self-hosted Chatwoot instance on Docker" say "your own private customer support platform with zero per-seat fees, full data ownership, and custom branding" businesses don't buy technology. they buy outcomes. "you'll never pay per-seat pricing again" closes deals faster than any feature list 5. build the moat with customization the open-source tool is the foundation. your value is: - custom integrations with their existing stack - branded interface matching their company - ongoing maintenance and updates - priority support with a human who knows their setup this is what separates a $2k/month retainer from a one-time $500 deploy. the tool is free. the orchestration is the product 6. find clients where they already complain search X and Reddit for "[tool name] too expensive" or "[tool name] alternative." these people are pre-qualified. they already know they have a problem and they're actively looking for a solution post case studies: "replaced $14k/year Intercom bill with a self-hosted solution for a 12-person team. same features. they own their data now" screenshots of real savings close deals. not pitch decks 7. scale by stacking tools per client client already paying you $3k/mo for their CRM? offer analytics for $1,500 more. then email marketing for $1,000. now you're their entire software infrastructure for $5,500/mo and they're still saving money vs their old SaaS stack one client. five tools. you deployed each one in an afternoon the part nobody talks about: these businesses will NEVER find these GitHub repos. they will never run a Docker container. they will never SSH into a server. they will google "affordable CRM for small team" and find you open source is the new wholesale. the code is free. the packaging is where the margin lives one person can run 5-10 clients. a two-person team scales to $30-50k/month. no funding needed. no office. no employees someone is going to do this in your niche. might as well be you study this
- 05
@deedydas ·
Founders should know the sobering reality for enterprise SaaS venture funding today. Here’s the math. Say you’re a $1M ARR company raising a Series A with a classic 33222 growth expectation. That gets you to $72M in 5yrs and say $250M in 8yrs. By then you’re usually growing <<50% and the public markets might give you a 7x or $1.75B, if you can even go public. If you get $10M at $100M post-money for the A, that’s a 17.5x and maybe 10x after dilution. That would be ~33% IRR and $10M invested becomes $100M. In the venture model, you have to outperform the SP500 which is 15% and a Google which is 25%. Here, with perfect execution, a lot of work, time and risk, you get 33% in a near optimal (95 percentile) case. And usually, you expect 7/10 things to not work out: execution risk, market size, competition. Plus, this math is for a Series A. You need investors to underwrite even more growth at the B / C / D. It’s really hard to see this sort of deal driving fund returns. Now, of course, there’s tons of caveats. You could pay less than $100M post, try to grow faster, do pro rata to avoid dilution, stay private longer etc, but the point remains. There might be exceptional growth stories like Databricks, Snowflake and Applied Intuition, but most deals look like what I described. In a previous time, SaaS multiples were higher in public (20x), entry valuations were lower ($30M) and the money you needed to hire talent was lower ($150k). You could get 100% IRR before. Now, it’s harder than ever to justify investing here, unless they are true outliers.
- 06
@RetentionAdam ·
I talk to delusional Series A founders every day. So now, I just tell them this. If your company does under $10M ARR, burns over $200k/mo, and has low Gross Retention…you are not worth $50-100M to anyone. Doesn't matter what your investors or your bankers tell you. Dirk Sahlmer from FE International has done nearly 6 years in SaaS M&A and hundreds of valuation conversations. He calls it Schrödinger's valuation, and he's right. Check it out and start recognizing what game you’re actually playing. Don’t waste the next 10 years chasing a fantasy.
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@starter_story ·
Getting your first 100 SaaS customers has almost nothing to do with going viral... Joseph has scaled two separate products past $3M in ARR. His current SaaS does over $250,000 a month. His approach? Capture the low-hanging fruit first. > That means things you can do in the next hour to start ranking on search engines. > It also means trolling subreddits where your future customers are already complaining out loud If you're building in SaaS right now, the first 100 wont come from luck they will come from showing up where the demand stays at.
Watch video
- 10
@javilopen ·
Software is collapsing. SaaS multiples went from 18x revenue in 2021 to 3.4x today. HOLY HELL. The thing is, before AI, the mere fact that you could build the product was a spectacular moat. You needed engineers, months, funding rounds, a CTO who knew Kubernetes (god, just https://t.co/MAQ0CWuRDl
- 11
@romanbuildsaas ·
At 28, I sold my first SaaS for 7 figures. I started it with just $500. Here's the exact playbook I'd follow if I had to do it again: ↓ 1. Don't reinvent the wheel Our biggest mistake : we spent 6 months trying to copy a YC startup that didn't even have product-market fit. Huge waste of time. Instead, find a SaaS that's already profitable. If customers are paying and the company is growing, the demand already exists. Your job isn't to invent a market. It's to build a better product for a specific audience. 2. Go vertical Horizontal SaaS is hard. We focused only on Shopify e-commerce stores. Instead of building 100 mediocre features, we built 10 features our niche couldn't live without. Your messaging becomes obvious. Your sales become easier. Your product gets better faster. 3. Get to $50k MRR This is where things become interesting. A SaaS doing ~$50k MRR can often sell for 2-3x ARR depending on growth, retention and profitability. If your product costs $100/month... You only need ~500 customers. Here's how we got them: • Cold email • LinkedIn outreach • B2B influencers • Organic content on X & LinkedIn • Affiliate program • Podcasts your buyers already listen to One rule: Don't create content about your product. Create content that solves your customers' problems. 4. Sell it Most founders go to Acquire (dot) com That's a great option. We didn't. I searched LinkedIn for people actively buying SaaS businesses. Messaged around 10 buyers. Got on calls. One acquired the company. The entire process took less than 2 months after due diligence started. Why did we sell? The team wanted to build something much bigger. That became GojiberryAI. Remember : building a SaaS isn't easy. You'll spend hundreds of hours solving problems no one else sees. But the formula is simple: • Build something people already want. • Focus on one niche. • Get customers. • Keep improving. Do that consistently... And selling your SaaS becomes an option, not a dream.
- 12
@arpit_bhayani ·
SaaS is not dead. The kind that is hard to justify buying is. Let me explain... companies pay for SaaS when it wins on at least two of four axes - time, money, capability (team's), and tokens. If a tool only saves you an afternoon of coding, that is not enough anymore. Anyone can build the core feature in a day. AI made that part cheap. Dirt cheap. What AI did not make cheap is the plumbing around the core feature - pipelines, integrations, compliance, uptime, audit trails, and edge cases collected over years of production use. That plumbing is the actual product. It takes time, energy, and effort to ensure correctness. The dashboard is just the part users see. The SaaS companies that die are the ones whose entire value is a thin wrapper around a feature a team can clone in a weekend. The ones that survive are the ones where switching costs, integrations, and compliance are the moat, not the UI. Building the demo was never the hard part. We did it overnight in hackathons, and now we do it in minutes with AI. Remember, the delta between a demo and production is 1,000 commits.
- 13
@namyakhann ·
Founders: 2026 SaaS Pricing Page Checklist: Tier Structure: - 3 plans maximum (Free/Starter, Growth, Enterprise) - Middle tier highlighted - Annual discount visible (20%+ saves) - Feature comparison table - No hidden fees Copy That Converts: - Plan names describe the buyer, not the size - Features listed as outcomes - "Most Popular" badge on recommended tier - Clear limits (users, usage, support) Transparency Wins: - Show all prices upfront - No "Contact Sales" until Enterprise - Monthly AND annual toggle - Trial terms crystal clear CTA Strategy: - Different CTA per tier - "Start Free Trial" beats "Get Started" - Enterprise gets "Book Demo" - Credit card optional for free tier FAQ Below Fold: - Can I change plans later? - What happens when I hit limits? - Do you offer refunds? - Is there a setup fee? - Annual vs monthly difference? Remember: Every hidden price = 40% fewer signups. Friction kills deals. Make buying brain-dead simple.
- 14
@thepatwalls ·
Just got off the phone with a $1M ARR saas founder. The secret? Selling REPORTING SOFTWARE to SERVICE BUSINESSES which they then use for their clients. On average, these agencies pay ~$10K per year for the tool. The value prop? It's no brainer purchase bc the software saves them hundreds of hours per week and also helps them retain clients for longer. It's an extremely niche reporting tool, and I think it can be replicated across 100s of other small niches. Episode coming soon.
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@coatuemgmt ·
AI labs are out scaling the most iconic SaaS businesses in history. The core driver: A fundamental shift from Selling Software (per-seat) to Selling Work (per-output). The Market Shift: Legacy: Tool-based subscriptions ($0.2T TAM). New Paradigm: Direct monetization of work ($5.5T TAM). By shifting the unit of value from the tool to the output, the addressable market potential expands by 25x. @LucasSwisher1 breaks down the data in our latest C:\Take
Watch video
- 19
@oliverbrocato ·
at 21, i was doing $1M/month in ecom. at 24, my SaaS just hit $410K MRR. if you offered me a $1M/month ecom brand or a $100K MRR SaaS today, i'd take the SaaS every single time. here's why: 1. predictable revenue vs praying for virality when i ran Tabs we were only as good as our latest TikTok. every month started back at zero. people impulse buy sex chocolate once and never come back lol. with Bustem, i can tell you with ~98% confidence what we'll do next month and the month after that. 2. you're actually solving a real problem most ecom is selling commoditized products where your only edge is creative. you don't run a business, you run an ad agency. that's not what i signed up for. at Bustem we help brands find and destroy copycats, counterfeits, and unauthorized resellers. that's a real mission and its fun to compete on more then just creative. 3. your team IS the product in ecom it's you, agencies, and VAs. in SaaS your people are the product. building a world class team has been 10x more rewarding than optimizing another ad. 4. it compounds ecom changes so fast you're building on quicksand. you have to reinvent yourself every other month. SaaS compounds. every customer, every process, every product improvement stacks on the last. and growth hacking B2B is so much easier because most of the competition is dinosaurs running companies from 2004. in ecom you're going toe to toe with the best marketers on the planet. Don’t get me wrong... I love ecom. It’s how I made my first real money. But after building both, I’d choose SaaS every time.
- 20
@Hartdrawss ·
This Reddit user cut SaaS churn from 15% to 4.5% in 60 days. Here's the exact playbook: 1/ the problem > B2B SaaS at $15K MRR with 15% monthly churn > basically refilling a leaky bucket every single month > 200+ services listed, quality inconsistent, customers confused > support overwhelmed, lowest loyalty, worst customers 2/ what actually fixed it > killed 80% of the product catalog. analyzed which services drove 80% of revenue and axed everything else. fewer options, way better experience. churn dropped 4-5% right there. > built an automated 365-day guarantee system. detects delivery issues and compensates automatically. no tickets, no manual review. support load dropped 40%. churn fell another 3%. highest ROI thing they ever built. > raised prices 40% and repositioned. lost price-sensitive users, gained way better ones. net churn improved even though volume dipped short term. > added real-time order tracking and proactive delay notifications. customers stopped churning just because they didnt know what was happening. small engineering effort, massive trust payoff. > started weekly 15-min calls with churned and active users. not surveys. actual conversations. drove 60% of product decisions in the year that followed. 3/ the result > churn went from 15% to 4.5% in 2 months > MRR went from $15K to $40K in the year after > mostly because they stoped losing people the leaky bucket was never an acquisition problem. it was always a retention problem.
- 21
@rodriscoll ·
A few more thoughts on the SaaSpocalypse. The SaaSpocalypse is really the story of a breakup. Wall St is getting ready to fall in love with AI, and to do that, it had to fall out of love with SaaS. Wall St is fickle, but it is serially monogamous. Love is blind; dead love is not. Wall St is suddenly shocked to discover SaaS has stock based comp that should be accounted for in free cash flow, finite TAMs, and companies that mature and grow stale. Meanwhile, Wall St is about to take AI companies public at 50x+ revenues, that dispense $10M stock-based comp packages to employees like lollipops, while having capex bills and negative free cash flow larger than any capex since we built the railways. Why? Because AI is growing like a weed. And growth, like beauty, is, as the poet Keats said, “all you know and all you need to know.” In the face of beauty or three years of 10x growth, all objections fade. We are all in the business of growth.
- 22
@tibo_maker ·
they said no to $2.5M in VC money for their 6 month old saas I would've done the same I can't say this enough: VC math and saas math are two different games. a fund needs you to swing for a billion or die trying a good saas business just needs happy customers paying every month most founders confuse the two and sign up for the wrong game this reddit story is a perfect example - tiny team, no full-time hires, and in 6 months they built one of the craziest organic growth stories I've seen 1200+ paying customers, 150k monthly visitors, MRR closing in on $50k. a VC saw it, loved it, offered $2.5m with a fast wire they rightly said no, and their logic was great too the term sheet had a liquidation preference. if things go wrong, investors get paid back first and founders keep the wreckage I get it, but the fund had nothing strategic to offer either no client intros, no distribution, no marketing muscle - just money and monthly check-ins and the biggest thing is their growth doesn't require capital they got here with almost no paid channels. LinkedIn and SEO did all the work you can't wire $2.5m into organic channels and make them compound faster money buys paid acquisition and headcount, and they needed neither see, to be fair, raising makes sense for things like hardware, long R&D cycles, markets where whoever scales first wins capital is the product there but a profitable saas growing 40-60% a month on organic channels is not that. raising there doesn't buy growth, it buys a boss if your customers are already funding you, you don't need a VC to do it
- 23
@GohilHardy ·
Things every SaaS founder should track weekly 👇🏻 • Unique visitors • Visitor → Sign-up conversion • Sign-up → Active user conversion • Weekly Active Users (WAU) • Churn rate • Customer retention • MRR • Top acquisition channels • Customer support requests • Most requested feature These metrics tell you what's coming next. What metric would you add to this list?
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@rodriscoll ·
There are growth investors and there are value investors, and there is a chasm in between. The SaaSpocalypse is really about the SaaS story shifting from the former to the latter. From 2004 to 2019, public SaaS companies grew at an average of 30% and were valued at an average of 6x revenues. It was the best, most predictable growth story in the market. Then two years of COVID gave us 40% growth at 20x revenues. Then came revenue deceleration. Not just back to 30%, but all the way down to 15%, while multiples went back just to 6x. On a revenue multiple graph, it all looked fine but it implied the growth rate would revert to 30% That's what the SaaSpocalypse is really about. Everyone is finally realizing that the growth story is all AI. SaaS companies without AI-driven growth will be valued like every other company in the market, on a growth adjusted multiple of free cash flow. Amazing companies with real value but no pixie dust premium. Turns out 30% revenue growth and 10% FCF is worth more than 10% revenue growth and 30% FCF. The Rule of 40 construct is (of course) wrong. The two are not interchangeable, and the transition from one to the other is hard.
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@kylegawley ·
It's 100x easier to get to $50k/mo with consulting than SaaS x5 clients paying $10k/mo is easier than 1000x customers paying $50 I think people grossly underestimate how hard it is to get 1000 customers - most SaaS will struggle to get 10 It's even harder to keep them, churn is brutal You can't exit which is true, but you already changed your life forever with that kind of money You can invest it and be financially free for the rest of your life in 2-3 years SaaS is brutally hard - years of uncertainty and a 95%+ chance of failure If you have skills and experience consulting is a much easier path with lower risk of failure Or do both, consulting is one of the best ways to find real business problems to solve with a SaaS
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@GohilHardy ·
Things every SaaS founder should track weekly 👇🏻 - website visitors - sign-up conversion rate - activation rate - churn rate - retention - top traffic sources - customer acquisition cost - monthly recurring revenue - support tickets - most requested feature Most founders track revenue only. The real signals happen before revenue.
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@nrmehta ·
I have lots of empathy for folks leading existing SaaS cos these days. They're fighting battles on 5 fronts: 1. Defending churn from larger platform consolidators 2. Defending churn from cheaper upstarts 3. Maintaining modest growth in the core business (x-sell, etc.) 4. Pivoting to a new agentic strategy 5. Keeping employees engaged while transforming the team and culture for #4 In an ideal world, they'd "burn the boats" and focus on #4 (as @eoghan @intercom impressively did) But some of these companies have significant debt to service while others have anxious public shareholders. Indeed, VC-backed companies have almost nothing to lose, since the equity value of their core businesses are sadly trending toward 0 in the eyes of future potential exits. Definitely not an easy time to run a SaaS co.
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@JaredSleeper ·
Comparing the growth curves of AI-native prosumer businesses with those of enterprise SaaS businesses is an egregious category error (and yes, I have done this too). Most of these businesses have gross retention far inferior to even SMB SaaS. And yes, that absolutely matters- both for growth duration and in maturity. Doesn't mean they aren't great businesses! But Grammarly/Canva/Wix are much more relevant comps than Salesforce, Workday, or ServiceNow.
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@MarketingMax ·
Met a guy a few years ago, building a SaaS business He was at $500 MRR “I’d never build an agency,” he told me. “It doesn’t scale!” Since then, several people we both know have built agencies to $100k+ a month with good margins. Meanwhile, he’s still working on his SaaS. The MRR? $1,200 I thought SaaS was supposed to scale better than an agency?
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@petergyang ·
People are saying SaaS is not dead. I think larger enterprise SaaS that can do multiple jobs are probably fine (e.g., Figma). But if you’re building a simple SaaS for a narrow use case, I think it's harder to monetize now because: 1. AI skills can often solve the same problem in a much more flexible, personalized way. 2. AI-native agents like Codex / Claude Code that have a user's personal context and memory have far more knowledge to solve the user's problem vs. a standalone SaaS website or chatbot. 3. People are willing to pay hundreds or thousands for services (human touch is what's rare these days) but charge $20 / month for a SaaS and people will compare it's value to their Claude / ChatGPT subscription. Curious if others feel the same way? I guess I'm in a bubble and most people have not set up their own AI skills yet.
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@nrmehta ·
Spoke to a CEO of a $140M ARR SaaS co yesterday. Profitable. Growing modestly. But churn is a big issue. The old playbook used to be to retain customers by: * Building a great product * Managing quality and uptime * Delivering rapid time to value * Ensuring strong adoption * Verify value and outcomes with your key stakeholders What's concerning now is many SaaS cos of all sizes (from AI native to mature) are experiencing churn even for customers that check all of those boxes. The work right now is to rethink your value proposition and reason for existence - not just shuffle deck chairs on the Titanic. This is not a Customer Success or CRO problem - it's a founder/CEO challenge. The captain needs to lead. Companies like Intercom show it's possible to not only avoid the glacier, but glide into open seas. But keep "sailing faster" at your own peril.
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@adrien_brbr ·
I took a job this week. 4 months ago I quit to go all-in on my SaaS. Build it, grow it, sell it by November, move to Australia. 237 EUR MRR. Growing. But not fast enough to pay rent. So I took a job. Not the plan. Felt like failing. But here's what didn't change: PostClaw still runs. Still makes money at 3 AM while I sleep. Still growing without me touching it. This is the part of building in public nobody posts about. The chapter between "I quit my job" and "I made it." The SaaS doesn't care where I sit from 9 to 5. It keeps running.
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@Soroosh_Tajdar ·
Honest taxonomy of SaaS ideas: 1. Solves a real problem people pay to fix today 2. Solves a real problem people tolerate instead of paying to fix 3. Solves a problem that only exists inside a specific workflow you happen to use 4. Solves a problem that doesn't exist but sounds like it should Most ideas in public SaaS communities are 3 or 4. The founders are convinced they're 1.
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@SimonHoiberg ·
Most early SaaS founders overpay for one thing they barely use: Convenience. "Just ship on whatever is fastest." "Who cares, it's only $99/month." "Managed everything, we'll optimize later." Later never comes. And suddenly your *infra bill* is a silent co‑founder that owns 30% of your margin. Here's how I think about stack decisions as a bootstrapped founder 👇 → Start boring. Postgres, simple queues, a single VPS. No exotic managed services unless they're mission‑critical. → Avoid invisible lock‑in. If you can't leave a provider in a focused weekend, you're not a customer - you're a hostage. APIs > proprietary SDKs. Exports > "just use our dashboard". → Separate "move fast" from "run forever". Use whatever helps you prototype. But before something becomes core: - Can I self‑host an equivalent? - Can I swap this out in under a week? → Price with costs in mind. Your pricing should assume: - Users grow. - AI usage grows. - Cloud prices rarely go down. If your unit economics only work at small scale, they don't work. You don't need a "hyperscale" architecture. You need a stack you *own* and can profit from at 100, 1,000, and 10,000 users.
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@rohanpaul_ai ·
Sequoia’s @carl_eschenbach calls the SaaSpocalypse narrative overblown. Argues SaaS incumbents remain dominant due to massive retention rates. However, AI-native firms have the speed to build agentic solutions by building on top of established SaaS
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@lucainweb3 ·
Seeing a lot of first time founders pitch to Animoca, I've noticed some of them don't fully understand what revenue KPIs they should be hitting to even consider raising at a certain stage. Trying to break it down simply (closest framework would be SaaS businesses): Pre-seed - $0 revenue. You have an idea, a founding team, and a hypothesis about who your customer is. Nothing is built yet. You're raising to prove the concept is worth pursuing. Seed - Still pre-revenue or very early revenue. You have a prototype, you've been talking to customers, getting feedback, and starting to understand how you get to product-market fit. The bet here is on the team and the thesis. Series A - $1-3M ARR. Your product is shipped and people are actively paying for it. You're doing $ 100K+ per month, iterating constantly, and showing real momentum. VCs want to see repeatable revenue here, not one-off spikes. Series B - $5-15M ARR. You understand your customer and your margins. Now the hard questions start - how healthy is your sales pipeline, what does churn look like, and how wide is that customer funnel really? Series C - $ 25M+ ARR. You have a great product, PMF, and strong customers. The question now is expansion - what else are your customers willing to pay for and how do you keep them inside your ecosystem? This is the path to unicorn territory.
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@nikita_builds ·
More SaaS companies are one AI project away from being replaced than they think. If your entire value proposition is software that a capable developer and a good model can replicate, you don't have a product moat. Maybe you have a head start, but that’s really it. Sure… you have distribution… but how long until people flock somewhere else? What actually holds up: physical infrastructure, operational complexity built over years, compliance and trust layers that take time to earn, proprietary data that can't be reconstructed. Admittedly, all of the above takes time. But that’s exactly the point. I spent most of my early years as a pure software person. The phone farm at Sendblue always felt like a liability: a weird operational burden we had because Apple wouldn't give us a real API. Looking back, it was the most defensible thing we built. Pure SaaS won't disappear. But the premium is shifting elsewhere.
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@frog_omo ·
In 2025, the average SaaS company changed its pricing 3.6 times. Kyle Poyar analysed 1,800 pricing changes and called it "the year everyone lost confidence in pricing." That's not a trend. That's an industry that doesn't know what its product is worth anymore. Here's the structural problem nobody's saying directly: Per-seat pricing was always a proxy metric. You weren't paying for seats; you were paying for the work those seats did. AI just made the proxy visible. One agent does what 10 reps did. You need 1 seat. The vendor just lost 90% of that contract at renewal. So credit-based models surged 126% year-over-year. Hybrid pricing jumped from 25% to 40% of companies in a single year. Salesforce built an entirely new license structure for Agentforce. Clay separated data credits from platform actions in March. Every one of those moves is the same admission: we don't know how to price the work yet. For ops leaders, this has a specific implication: the tool budget you approved in January is probably wrong by Q3.
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@villageglobal ·
"SaaS businesses have been built to sell a tool. In the AI era, they have to shift to selling outcomes. That is a fundamental DNA shift." @jakesaper, GP at Emergence Capital, on why most SaaS companies won't survive the AI transition: "If you've built your organization around selling a widget on a per-seat basis, and you have to shift to building something that does the job — it has huge implications on product, go-to-market, pricing." "Our firm was founded as software moved from on-prem to cloud. The vast majority of companies from that era did not survive. But even bigger companies got built on top of the ashes." "SaaS leaders thought about outcomes as 'did my customer renew?' In the future — 'did we create dollar value?'" "They were selling a tool to arm someone. That's a derivative. In this new world, they have to do the thing."
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@tiboel ·
The success of an AI company is now judged by the shape of its curve. People talk about “curves”. Not “Where will you end the year?” But “What did you make in the last 3 months?” Revenue is the new religion. But something fundamental changed: 👉 the nature of revenue. SaaS sold products. Tools. Shovels and picks. AI sells services. Resources. Every single scoop. With a product:you build once. Then margins expand. With a service:you pay every time. Compute. Infra. Models. Selling scoops is easier. Faster. More rewarding upfront. But less profitable. Revenue grows fast. But it’s not the same quality. The real opportunity? Product × AI The magic of service. With the margins of SaaS. Same curve. Very different economics.
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@TheGeorgePu ·
Cursor's ARR trajectory: January 2025: $100M. June 2025: $500M. November 2025: $1B. February 2026: $2B. Zero to $2B in roughly three years. Faster than Slack. Faster than Zoom. Faster than Snowflake. Fastest-scaling B2B software company on record. Now raising at $50B. I've been saying SaaS is dead. Numbers like these say otherwise. Or do they? Cursor passes nearly 100% of revenue to Anthropic and OpenAI for inference. The customer isn't buying software. They are buying broker access to other models. Is this SaaS? Or is it the death of SaaS dressed in SaaS clothing?
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