28% of SaaS deals die in the qualification stage. Budget gaps, missing executives, poor fit, bad timing, and weak ROI cases sink opportunities. Learn how early-stage CEOs can fix qualification discipline.
Builder.ai’s Rise and Collapse: Lessons for Seed-Stage SaaS CEOs
Builder.ai, once a $1.5 billion AI unicorn backed by Microsoft and Qatar’s sovereign fund, has collapsed under the weight of fraud and hype. Marketed as a no-code, AI-powered app builder, the company relied heavily on human developers and inflated its revenue through round-tripping deals. This 3,000-word deep-dive traces Builder.ai’s rise, the discovery of its fraudulent practices, and comparisons to similar scandals like Theranos, Zymergen, Frank, and WeWork. Most importantly, it outlines the lessons seed-stage SaaS CEOs must learn: transparency in technology claims, strong financial governance, resisting hype-driven valuations, and building customer trust over vanity fundraising. For SaaS founders navigating today’s AI-saturated market, Builder.ai is a cautionary tale: hype might win headlines, but integrity is the only true differentiator.
“Why the Dawn of Autonomous Procurement Is Still a Mirage”
The narrative that “software buys software” oversimplifies enterprise reality. While Jeff Morris Jr. argues that procurement is shifting to AI agents making algorithmic, impersonal buying decisions, the evidence says otherwise. AI agents today are experimental, risky, and far from handling the complexity of multimillion-dollar enterprise deals. Trust, relationships, compliance, and governance remain central to software procurement. Instead of replacing sales teams, AI is emerging as a co-pilot—augmenting research, recommendations, and workflows. Authoritative sources like Reuters, Goldman Sachs, and Gartner emphasize that full autonomy in procurement remains speculative. Enterprises still rely on human judgment, negotiation, and accountability. This blog explores why algorithmic procurement is a mirage, not a present reality, and why hybrid, human-in-the-loop models are the real future. For SaaS founders and executives, the takeaway is clear: invest in AI augmentation, but don’t abandon the sales craft that still drives trust and deals.
Why 35% of B2B SaaS Deals Are Lost in the Discovery Stage
Why do 35% of B2B SaaS deals die in discovery? Most losses stem from poor discovery, missed decision-makers, weak differentiation, and lack of trust. Learn how early-stage CEOs can fix this.
Participant Recruitment: The Achilles Heel of Qualitative B2B Research
B2B SaaS research, participant recruitment, Win/Loss interviews, willingness-to-pay studies, ICP validation, qualitative research challenges, SaaS pricing research
2024 B2B Sales Benchmark Report: Why Top Performers Win Deals and Average Reps Lose in the U.S., U.K., and Global Markets
The 2024 B2B Sales Benchmark Report reveals why top performers consistently win deals while average reps struggle. Analyzing $54B in revenue and 4.2M opportunities, this article explores how pipeline generation, qualification, objections, relationships, and deal management drive success—or failure—in U.S., U.K., and global markets.
Why I Don’t Help Pre-Seed or Seed Stage SaaS Firms Raise Venture Capital
Many consultants promise to help pre-seed and seed-stage SaaS startups raise capital—but without a Series 7 license, those services can expose founders to serious legal and financial risks. In this article, I explain why I avoid fundraising engagements, the SEC’s crackdown on unlicensed brokers, and what it really costs to work with a licensed broker-dealer.
How Local Businesses Can Adapt to Economic Shifts for the Betterment of Their Communities
Economic shifts can arrive without warning, pressing down on small businesses with both subtle tremors and sudden jolts. Local entrepreneurs often feel the squeeze first, balancing cash flow while watching […]
Why Enterprise SaaS Companies Win or Lose Deals: A Deep Dive into 2024–2025 Win/Loss Statistics
Enterprise SaaS win/loss statistics from 2024–2025 reveal that average win rates sit at 19%, but deals with prior champions close at nearly 50%. This blog explores the key drivers of SaaS wins and losses, including brand awareness, buyer indecision, deal sizes, pricing models, and the rising importance of trust and relationships.
How 95% of Generative AI Projects Are Failing — A Global Reality Check
A new MIT study reveals that 95% of generative AI projects fail to deliver measurable results. Despite billions invested and immense hype, most pilots collapse due to flawed integration, misaligned priorities, and lack of organizational readiness. Only 5% succeed, often by focusing on targeted use cases, leveraging specialized vendor partnerships, and aligning AI with practical workflows. The findings have rattled markets, raising fears of an AI bubble similar to the dot-com crash. Yet, lessons emerge for businesses worldwide: start with purpose-driven pilots, invest in ROI-rich areas like back-office automation, and scale responsibly. This article explores the MIT study, examines investor jitters, uncovers broader risks like algorithmic bias and job displacement, and offers a roadmap for sustainable AI adoption. For global businesses, the message is clear: avoid the hype cycle and focus on strategy, not speculation.