Small AI Startups, Big Scaling Problems

“Small but mighty” AI startups are making waves—some even hitting $20M to $100M in ARR with lean teams. But as Jason Lemkin points out, this model has a hidden flaw: it often doesn't scale.

These startups thrive on early momentum, but when it comes time to expand, they face significant challenges. The very lean structures that propelled their initial success can become obstacles, making it difficult to build robust sales, marketing, and customer success teams.

The key takeaway? Early efficiency is impressive, but without a plan for scaling operations and teams, even the most promising AI startups can hit a growth ceiling.

Reference: Lemkin, J. (2025, April 8). The Problem with “Small But Mighty” AI Start-Ups. SaaStr.

Salesforce's Bold Bet on AI and Sales

In a surprising move, Salesforce announced that in 2025, it will hire zero new engineers, citing a 30% productivity boost from AI. Instead, the company plans to expand its sales team by 20% to capitalize on the growing demand for AI solutions.

CEO Marc Benioff emphasized the company's strategic shift:

“In 2025, they are hiring 0 new engineers. None. Because they think AI makes them 30% more productive; and In 2025, they’re expanding their sales team by up to 20%. Because they want to win in selling AI.”

This approach underscores Salesforce's commitment to leading the "Digital Labor Revolution" by focusing on deploying AI agents and enhancing enterprise sales efforts.

Reference: Lemkin, J. (2025, May 12). Salesforce: We Are Hiring 0 Engineers This Year. But We’re Growing The Sales Team +20%. Because AI. SaaStr.

AI Is Already Changing Sales

If you think AI is a future trend, think again. It's already transforming the sales landscape.

According to Jason Lemkin's article, "10 Ways AI Will Change Sales Forever. It’s Already Happening, In Fact," AI is poised to revolutionize B2B sales within the next 12–18 months. One of the most compelling insights from the article is:

“AI will join your sales calls – Within 12–18 months, your AI will be on every call, knowing your product cold and eliminating ‘I’ll get back to you’ moments.”

This means that AI won't just assist with administrative tasks; it will actively participate in sales calls, providing real-time, accurate information, and enhancing the overall customer experience.

Furthermore, AI is expected to handle up to 50% of routine sales, especially for transactional deals under $10K. This shift will allow sales professionals to focus more on complex, high-value interactions that require human intuition and relationship-building skills.

The integration of AI into sales processes is not a distant future—it's happening now. Sales professionals who embrace AI tools will be better equipped to meet increasing customer expectations and stay ahead in a rapidly evolving market.

Reference: Lemkin, J. (2025, April 28). 10 Ways AI Will Change Sales Forever. It’s Already Happening, In Fact. SaaStr.

AI Is Already Remaking SaaS

AI is no longer a futuristic concept in the SaaS world—it's the present reality. As Jason Lemkin notes, "AI isn’t a differentiator anymore per se — it’s the baseline." Customers now expect AI capabilities to be seamlessly integrated into products, enhancing workflows, onboarding, and predictive insights.(SaaStr)

This shift has led to skyrocketing customer expectations. Users demand faster, smarter, and more automated experiences. Onboarding should be seamless, communications should be automated, and insights should be readily available. To meet these expectations, products must be significantly better than they were even a year ago.(SaaStr)

AI is also revitalizing freemium and product-led growth (PLG) models. With AI enhancing onboarding and initial usage, customers can quickly realize value, making PLG strategies more effective than ever.(SaaStr)

However, AI is also disrupting pricing structures. Software categories that rely heavily on manual processes are being challenged by AI-driven alternatives that offer faster and cheaper solutions. Companies that fail to leverage AI to improve efficiency may find themselves under pricing pressure.(SaaStr)

On the upside, AI is improving gross margins for SaaS companies. By effectively integrating AI, companies can deliver more value at a lower cost, gaining a competitive advantage. As Lemkin observes, "Gross margins will improve for AI-driven SaaS. Don’t let costs be an excuse."(SaaStr)

In summary, AI is fundamentally transforming the SaaS landscape. Companies that embrace AI and integrate it effectively into their products and strategies will be well-positioned to thrive in this new era.

Reference: Lemkin, J. (2025, March 24). AI is Already Remaking SaaS. 10 Trends To Watch Right Now. And Not Fall Behind On. SaaStr.

AI Won’t Replace SDRs—It’ll Supercharge Them

AI isn’t coming for your Sales Development Reps—it’s coming to upgrade them.

At SaaStr Annual, Carta’s CRO Jeff Perry and LinkedIn’s first VP of Sales Brendon Cassidy made one thing clear: the smartest sales teams are using AI to make SDRs faster, sharper, and more effective—not redundant.

Here’s the takeaway that says it all:

“The real playbook: Use AI to make SDRs 2x more efficient, not replace them.”

Instead of wasting hours on manual prospecting or repetitive follow-ups, AI is doing the heavy lifting—surfacing the right leads, crafting personalised outreach, and streamlining workflows. That gives SDRs more time to do what humans do best: connect, influence, and convert.

The future isn’t about choosing between reps and robots. It’s about building teams that use both to win faster.

Reference: Lemkin, J. (2025, May 12). Not Using AI to Replace Your SDRs, But to Make Them 2x Better: A Deep Dive with Carta’s CRO and LinkedIn’s First VP Sales. SaaStr.

Average Reps Beware—AI’s Coming

If you're relying on autopilot in sales—AI may soon outpace you.

By 2026, AI won’t just assist with admin tasks like CRM updates and email follow-ups—it’s projected to replace the bottom 30–40% of sales reps entirely. These are the reps who lack product knowledge, fail to follow up, and struggle to build meaningful rapport.

One quote from the article makes it crystal clear:

“AI will replace the bottom 30%-40% of sales reps — those who don’t know their product well, who don’t follow up, who don’t build rapport.”

But here’s the opportunity: high-performing reps won’t be replaced—they’ll be amplified. AI can manage the repetitive, time-consuming tasks, freeing you to focus on what truly drives revenue—problem-solving, strategic conversations, and relationship-building.

The message is simple: don’t compete against AI—partner with it. The future belongs to sales professionals who combine human insight with AI-powered execution.

Reference: Lemkin, J. (2025, May 12). Where AI Will, and Won’t, Replace Sales Reps in 2026. SaaStr. https://www.saastr.com/where-ai-will-and-wont-replace-sales-reps-in-2026/

AI That Works: Calendly’s 10 Lessons

Calendly's journey into AI offers valuable insights for sales professionals aiming to integrate AI effectively into their workflows. Here are the key takeaways:

• Address Real Problems: AI should enhance productivity by solving specific, high-friction issues users face daily.(SaaStr)

• Avoid Parallel AI Products: Creating separate AI experiences can lead to low adoption. Instead, integrate AI seamlessly into existing workflows.(SaaStr)

• Evaluate AI Investments Carefully: Assess AI initiatives based on customer value, cost structure, data quality, and user experience impact.(SaaStr)

• Personalization at Scale: Use AI to personalize user experiences across all touchpoints, enhancing engagement and retention.(SaaStr)

• Measure Meaningful Metrics: Focus on metrics like user engagement with AI features, task completion rates, and impact on core product metrics.(SaaStr)

• Ensure Robust Data Architecture: A unified data infrastructure is crucial for consistent and effective AI experiences.(SaaStr)

• Maintain Consistency Across Channels: AI should provide a consistent voice and experience across support, marketing, and product interfaces.(SaaStr)

• Manage AI Costs Strategically: Be mindful of the costs associated with AI, especially at scale, and consider hybrid approaches for cost-intensive features.(SaaStr)

• Implement 'Invisible AI': AI should operate seamlessly in the background, enhancing user experience without being obtrusive.

• Prioritize Continuous Education: Offer AI-powered, contextual learning experiences to keep users engaged and loyal.

These lessons underscore the importance of integrating AI thoughtfully to enhance user experience and drive business growth.

Reference: Lemkin, J. (2025, April 17). Building AI That Actually Works: 10 Key Lessons from Calendly’s CPO and Head of UX. SaaStr.

Scaling AI the Monday.com Way

Monday.com’s rise from $10M to over $1B in ARR in just eight years wasn’t just about product-market fit—it was about embedding AI as a strategic growth lever.

Co-founder and Co-CEO Eran Zinman shares a perspective that every sales and product leader should note:

“AI is not just a feature; it's a core part of our product strategy.”

That mindset shaped how Monday.com approached everything—from customer workflows to product innovation. Instead of treating AI as a bolt-on or gimmick, they made it integral to the user experience. The result? More intuitive automation, smarter insights, and a platform that adapts to the way teams really work.

Here are three key lessons from their journey:

1. AI is Infrastructure, Not Add-on They invested in making AI foundational. This allowed their features to scale across multiple verticals and use cases without having to rebuild core logic for every department.

2. User Empowerment at Scale AI wasn’t used to replace human decisions—it was designed to amplify them. Features like AI-powered task suggestions and workflow automation helped users move faster with less friction.

3. Speed Fuels Product Velocity By deploying AI across teams internally (not just in the product), Monday.com improved their development cycles and operational efficiency. That internal AI adoption was just as critical as customer-facing innovation.

For sales professionals and startup founders, the takeaway is clear: the companies that win with AI aren’t just using it—they’re designing around it. That means aligning teams, building with scale in mind, and constantly asking: how can AI make this better for the user?

Reference: Lemkin, J. (2025, February 28). AI at Scale: 8 Learnings from Monday.com Co-Founder and Co-CEO Eran Zinman. SaaStr.

AI Tools for Marketing Scorecard (May 2025)

Every B2B sales leader wants to know: where is AI delivering real value in marketing—and where is it still a science experiment?

A new 2025 scorecard based on insights from 50+ top CMOs gives us the clearest picture yet.

Here’s the TL;DR for sales pros:

🚀 What’s Working

• Analytics & Insights (⭐⭐⭐): AI is great at finding patterns humans miss. Think of it as your secret pre-call briefing—now smarter and faster.

• Ad Creation/Optimisation (⭐⭐⭐): Creative variations and smarter targeting are saving time and boosting campaign ROI.

• Budget Optimisation (⭐⭐): Tools are improving—soon you’ll see AI helping marketers put their money where the results are.

🤖 What’s Still Maturing

• Customer Journey Mapping (⭐): AI’s not yet reading buyer minds, but it’s starting to track the breadcrumbs.

• Event Marketing (⭐): In-person events? Still mostly human. Virtual ones are starting to feel the AI touch, but we’re early days.

🔎 What It Means for Sales

If marketing isn’t leveraging AI in analytics or ad targeting, they’re leaving conversions on the table—and you’re losing sales momentum.

This isn’t just a martech issue—it’s a pipeline issue.

🧠 Sales Insight

The smartest sales teams aren’t just asking for MQLs anymore. They’re partnering with marketing to guide AI investments toward high-impact outcomes—like better qualified leads and real-time account intelligence.

Source: Based on insights from Carilu Dietrich’s 2025 State of AI in B2B Marketing Scorecard, reflecting conversations with 50+ tech CMOs.

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A Practical Guide to AI Agents

Agents are the next evolution of automation—and they’re a big step up from chatbots or basic workflows.

This guide unpacks how to design, deploy, and scale AI agents that can think through complex decisions, take action across systems, and actually complete real-world tasks for your users. It’s written for product, engineering, and AI teams, but any forward-thinking business leader should pay attention.

What’s an Agent (and Why Should You Care)?

Agents don’t just respond—they act. They use AI to make decisions, choose tools, and run multi-step workflows. Think customer support, fraud analysis, or triage—jobs that used to need human judgement.

When Should You Build One?

If your rules-based automations are breaking down—or your team is drowning in edge cases—it might be time. Agents shine when there’s ambiguity, messy data, or high-context decisions.

How to Design a Great Agent

Three key ingredients:

• Model: The brain (usually a large language model)

• Tools: APIs or functions to take action

• Instructions: Clear prompts and guardrails to keep it on track

Start with one strong agent and expand from there. Multi-agent systems come later—only when things get complex.

Guardrails Matter

Agents need boundaries. You can use filters, classifiers, and human overrides to prevent chaos. Safety isn’t optional—it’s built in from day one.

Start Simple. Build Fast. Scale Smart.

Don’t over-engineer. Launch a single use case, test with real users, and expand as you learn. Done right, agents can transform how your business handles everything from support to operations.

📘 Read the full guide here: A Practical Guide to Building Agents – OpenAI