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Jason Lemkin's breakdown of Artisan's Ava 2.0 is one of the most honest takes on AI SDRs I've seen. But PainSignal data on cold outbound and AI voice quality reveals two critical gaps: data quality remains a hidden pain, and SMBs are largely underserved. Here's what founders and indie hackers need to consider.
A SaaStr founder shares how a rogue PR firm trashed a relationship without the client knowing. Our data reveals this isn't rare—it's a systemic risk as teams deploy more AI and human agents without oversight.
Your most loyal customers are secretly building workarounds with AI agents. Our data shows 47 reported problems with support degradation for long-tenured accounts — and the root cause isn't just neglect, it's incentive structures that reward new logos over retention.
Jason Lemkin's SaaStr piece on Reevo's AI agents nails the most important decision rule in automation: target high-effort, low-judgment work. PainSignal data backs up the admin burden but casts doubt on 'zero leakage.' Here's what builders should steal and what they should question.
Jason Lemkin's SaaStr AI 2026 lead leaderboard reveals where B2B budget is flowing: building, selling, and running companies. But our data suggests the real pain is deeper in back-office operations like payroll and HR.
Three out of every four companies we track are scrambling to rein in AI costs—and it's not just engineering feeling the squeeze. Marketing teams, sales, and support are blowing their budgets too. For builders, this pain creates a massive opportunity.
AI is the new dial-tone. Every company has it. But our data reveals two hidden pitfalls—integration debt and procurement paralysis—that are silently killing vertical AI startups. Here's what the SaaStr AI 2026 panelists missed.
SaaStr AI 2026 celebrated CS rebirth at AI-native companies. But PainSignal's 19,860 problems show most B2B is stuck in legacy systems and compliance hell. The real story isn't CS's death—it's a bifurcation that most builders and investors are ignoring.
Nue's CPQ demo at SaaStr showed AI that doesn't guess. Our data confirms that pricing errors and discount abuse are rampant. The real insight: deterministic AI built on a pricing engine that enforces guardrails is the only kind worth shipping in revenue workflows.
Jason Lemkin's SaaStr piece nails the financial cost of GTM tool sprawl—$3M in fees, 22 tools, 11 ops people. But our data reveals a deeper toll: employee burnout from constant context switching, and a hidden integration tax that hits SMBs hardest. Here's the full picture.
Jason Lemkin built 10K, an AI VP of Marketing that orchestrates SaaStr's entire go-to-market. It's impressive. But our data on thousands of marketing teams shows that most aren't ready to replicate this. The real bottleneck isn't AI — it's data hygiene, integration depth, and trust. Here's what you need before you build.
SaaStr's latest says the fastest AI companies are ditching the old CS playbook—renaming CSMs, killing NPS, and replacing rigid platforms with in-house builds. But PainSignal data reveals a deeper disconnect between technical and business buyers that even the hottest companies haven't solved. The real opportunity is hybrid CS models for a divided buyer base.