The Wire

Real-time updates from ANZ tech sales

2 months ago
News

Vercel AI agents handle 93% of support, replaced entire SDR team

## The numbers Vercel is running hundreds of AI agents internally and posting specific metrics, per CPO Tom Occhino at SaaStr AI Deploy: - **96% of marketing content** now starts as AI-generated drafts from Slack threads - **93% of customer support inquiries** handled with no human intervention - **SDR team reabsorbed** after a lead qualification agent took over repetitive work Those are operating claims from a conference talk, not verified company disclosures. But they match what Vercel sells: AI infrastructure for developers building agents. ## What this means for sales teams Vercel's model is product-led, not sales-led. The company has historically run on self-serve developer adoption with enterprise layered on top. So when Occhino says they replaced SDRs with an agent, context matters: this is a developer tools company with a different motion than traditional enterprise software. The agent that replaced SDRs handles qualification, the mechanical part. The people who did that work moved to higher-impact roles, per Occhino. No word on whether "higher-impact" means sales, customer success, or something else entirely. ## The GTM agent: DealOne Vercel's go-to-market agent, DealOne, ingests sales calls, generates notes with action items, and posts coaching suggestions. It is built on Vercel's own AI SDK and runs in production. Occhino's thesis: every company will build custom agents, not buy off-the-shelf "agents as a service." You cannot buy a one-size-fits-all agent any more than you can buy a one-size-fits-all website. What you buy is the tooling to build and run agents cheaply. ## The reframe Occhino and CTO Malte Ubl (ex-Google, created Core Web Vitals) frame agents as a shift from UI-first software to autonomous software that acts on your behalf. The UI becomes a leaf node for human decisions. The trunk is headless automation. Their conclusion after two years: humans stop doing work an agent can do and move to work that compounds. The support team only touches hard or valuable tickets. Everything else is signal: product gaps or misconfigurations. ## What we do not know Vercel is a late-stage private company. Revenue is not disclosed. ANZ headcount or local operating scale is unclear from public materials. The SDR reabsorption and support/marketing percentages come from Occhino's talk, not a company earnings report or verified HR data. Treat this as a case study in how one well-funded developer platform is restructuring around agents, not a benchmark for sales org design across B2B. ## The broader pattern Multiple AI SDR and agent vendors (Artisan, 11x, AiSDR, others) are pitching automation for outbound and inbound qualification. Salary surveys show SDR comp holding steady in 2024, but role elimination concerns are real. Vercel is not eliminating the function, they are redeploying it. That distinction matters when you are deciding whether to take an SDR role in 2025.

SaaStr
2 months ago
News

Anthropic hits $183B valuation in 4 years, $9.4M revenue per head

## The numbers Anthropic, founded in 2021 by former OpenAI researchers, raised a $13 billion Series F in 2025 at a $183 billion post-money valuation. That is four years from founding to one of the highest private company valuations ever recorded. The company is doing roughly $5 billion in annualised revenue with about 5,000 employees. That works out to $9.4 million in revenue per person. For context: when Salesforce crossed $30 billion in revenue, it had roughly 79,000 people. When Google hit that mark, it had around 32,000. Anthropic got there with 5,000. Apple generates about $2.5 million per employee. Alphabet does $2.1 million. Anthropic is at nearly four times that rate. ## What this means for sales The old model assumed revenue and headcount scaled together. Every dollar of new ARR required more AEs, more SDRs, more managers to manage the managers. Revenue per employee crept up slowly as businesses matured. That link is breaking. When your product is intelligence delivered through an API, you are not adding humans to serve each new customer. The marginal cost of the next million in revenue is compute, not a bigger org chart. Anthropic's growth has been driven by enterprise API usage and strategic partnerships with Amazon and Google, not a traditional long-cycle B2B sales motion. The company does have a sales organisation, but its structure and comp are not publicly disclosed. For ANZ, Anthropic's footprint appears limited and mostly indirect. No large ANZ office or disclosed headcount, which suggests the region is served through global enterprise sales and cloud channels rather than a local team. ## The compression continues Cursor, the coding tool built by Anysphere, went from founding in 2022 to a $60 billion deal with SpaceX in 2026. Four years. The fastest path to an exit of this scale on record, and the largest tech acquisition ever. Wiz, the cloud security company, went from founding in 2020 to a $32 billion all-cash acquisition by Google in 2026. Six years, 30x ARR multiple. These are not outliers anymore. This is the new ceiling for AI-native companies that sell intelligence, not software. The old benchmarks do not apply.

SaaStr
2 months ago
News

SaaStr built AI VP of Marketing, runs it alongside human CMO

# SaaStr built AI VP of Marketing, runs it alongside human CMO Jason Lemkin's SaaStr spent over $500,000 building what it calls an AI VP of Marketing. The agent, named 10K, does not write content. It orchestrates: plans campaigns, manages pipeline in Salesforce, connects to Zapier and vendor APIs, and assigns daily tasks to the two humans running marketing. The build happened because existing AI marketing tools only generate content. SaaStr already has 5,000+ pieces of content across 13 years. The bottleneck was not more blog posts. It was knowing what to do, when, and executing a coherent plan across channels. 10K pulls from 5+ years of SaaStr data, feeds it into Claude Opus, and outputs a Replit app that plans every marketing action through mid-2026. It updates daily. When a campaign underperforms, it flags it on day two, not day sixty. No ego, no sunk cost fallacy, no defending pet projects. The operating model: run the AI VP and the human VP in parallel. Compare outputs. Debate recommendations. SaaStr says the AI's honesty and lack of agenda beats most human analysis, even if it is not better than a great human marketer. What it cannot do yet: manage third-party AI agents directly. 10K can analyse outputs from tools like Artisan or Qualified, but it cannot train them or change their behavior. Each agent has different guardrails, input processes, and training requirements. Lemkin says that orchestration layer, a single pane of glass that manages all AI agents, is a massive opportunity for someone to build. The broader shift: SaaStr had 20+ full-time employees in 2020. Today it runs 3 full-time humans and 20+ AI agents at the same revenue scale. The AI layer connects to 10+ years of data and automates workflows for a media/events business with multiple revenue streams: content, conferences, sponsorships. For sales teams watching this: the AI VP is not hypothetical. The comp is real, the workflow is live, and the early signal is that orchestration matters more than content generation. If your go-to-market stack includes multiple AI tools, the next question is who (or what) coordinates them.

SaaStr
2 months ago
News

SaaStr runs on 3 humans and 21 AI agents, books 614 meetings

# SaaStr runs on 3 humans and 21 AI agents, books 614 meetings SaaStr, the B2B media company and $200M VC fund, operates with 3 humans, 1 dog, and 21 AI agents in production. Their Amelia agent handled 2.2M website sessions, 442,000 chats, and booked 614 qualified meetings. Average sponsor ASP: $85k. The stack matters because it shows what GTM efficiency actually looks like when you cannot afford traditional headcount. No BDR team. No army of CSMs. Just agents that started as dashboards and evolved through 600 to 1,000 commits each. **The agents doing sales work:** - **Amelia AI:** Qualified inbound. Replaces 3 BDRs SaaStr could not afford. 614 booked meetings, $85k ASP. - **Agent Force:** Dead lead revival inside Salesforce. Highest open rate because it has the most context. - **Ava/Artisan:** Warm outbound to past attendees and lapsed sponsors. Recovered ~$500K this year. - **Monaco:** Cold ICP look-alikes. Fills its own funnel, books meetings autonomously. - **QBee:** Sponsor success. Manages 150+ accounts with personalized outreach and real-time risk flagging. No full Salesforce integration yet, already outperforms 85% of human CSMs at force-ranking health. **Why this matters for sales teams:** Owner.com provides the other half of the story. The restaurant SaaS company hit $100M ARR with 83% of new customers starting via Gradr, their free AI website generator. The product costs $1 in compute per restaurant and converts into $1/month subscriptions. Owner's CRO Kyle Norton took ARR from $3M to $21M in 22 months using AI-first GTM. Klaviyo, the public marketing automation company, is rebuilding product and engineering processes around agents. Not customer-facing features. Core internal workflows. **The connective tissue:** Headless Salesforce. None of these agents work if they have to use the UI. They use the API directly, in real time. **What this means for ANZ sales teams:** If a sub-10-person media company can book 614 qualified meetings and manage 150+ enterprise sponsors with agents, the traditional SDR-to-AE ratio is under pressure. Not next year. Now. The question is not whether to deploy AI agents. The question is whether your comp plan assumes headcount that will not exist in 18 months. Owner showed the blueprint: build the free AI product, convert to paid, bundle from there. 83% of pipeline starts with the agent. The AE closes the expansion. SaaStr showed the ops model: agents own qualification, revival, warm outbound, and sponsor health. Humans own high-touch enterprise closes and strategy. The gap between these models and traditional sales org charts is widening fast.

SaaStr
2 months ago
News

Lovable hits $400M ARR with 197 people: PLG at $2M per head

## The Numbers Lovable, the AI app-building platform, hit $400M ARR with 197 people. That is $2M+ in ARR per employee. For context: most B2B SaaS sits at $150k to $250k per head. They doubled from $100M to $200M in four months, then doubled again. Elena Verna, Head of Growth, spoke at SaaStr AI about what is actually working when AI writes 80% of your code and competitors can clone your features in a weekend. ## Feature Differentiation Is Dead Verna's thesis: when AI collapses the cost of building, feature leads last weeks, not years. You ship something new, competitors replicate it by next sprint. The 15-year B2B playbook of "better product, better engineers" does not hold. What still works as a moat: - Hardware (genuinely hard) - Network effects (hard to create, compound over time) - Proprietary data - Security and compliance (slow and expensive, which is the point) - Brand ("Brand is back, baby") Notably missing: SEO, SEM. When everyone can build the product, the relationship with the customer is what is left. ## The GTM Implication Lovable runs product-led growth, not enterprise field sales. Self-serve, rapid adoption, AI positioning. The scale came from distribution and workflow integration, not a 50-person sales org. Verna's take on org structure: everyone ships code, no traditional PM-to-engineer ratios. A `#shipped` channel with multiple production releases daily. A `#feedback` channel where ideas go live in 24 hours if one other person agrees. She also went from leading a 200-person growth team at Dropbox to firing herself out of marketing at Lovable and going back to IC. Her read: the next decade's career flex is the high-powered IC with AI agents, not the VP title. Worth noting for sales leaders watching quota-carrying AEs debate management tracks. ## What This Means for ANZ B2B If feature parity is a weekend sprint, sales teams cannot lean on product superiority. The pitch shifts to: distribution, integration, trust, compliance. Enterprise AEs selling against AI-native competitors need to know what moats their company actually has, because "better roadmap" is not one of them anymore. Verna says Lovable is still "on the product-market fit treadmill" at $400M ARR. The category moves so fast they recapture PMF every month. Scale did not let them slow down. It raised the stakes on velocity. No public data on Lovable's ANZ presence or sales team size. The growth engine appears to be product-led, not field-sales-led. That $2M per head number? That is the new benchmark when AI does the building.

SaaStr
2 months ago
News

Seven ANZ startups raised $17 million this week, quantum tech leads

Seven ANZ startups raised $17 million combined this week. That is split across early-stage deals, not the $50 million Series B rounds that come with 20-AE hiring plans. QuantX Labs led the pack with $7 million USD ($7 million AUD) in seed funding from Serendipity Capital. The South Australian quantum sensing startup builds optical atomic clocks for defence, satellite networks, and critical infrastructure. The tech is 10 to 100 times more stable than existing microwave-based systems, smaller, and portable. Applications include GPS resilience, radar networks, and telecommunications timing. Founded in 2016, QuantX Labs is commercial now, selling into defence and infrastructure. Quantum sensing is a crowded global market, but the defence angle and Australian sovereign capability positioning give them an edge for government contracts. The other six startups in the funding tally include Nardo (sports tech, backed by former Socceroo Tim Cahill), Alloovium and Gutgutgoose (both Y Combinator-bound), and four others not detailed in the source material. Combined, they raised $10 million. What this means for sales teams: These are seed and pre-Series A deals. Hiring plans will be measured, not explosive. QuantX Labs might add 1-2 commercial or partnerships roles given the defence sales cycle. The Y Combinator startups will focus on product-market fit, not go-to-market scaling yet. For context, ANZ startup funding is down 60% from 2021 peaks. Seed rounds are steady, but growth-stage capital is tight. The companies closing deals now are capital-efficient and commercial-ready. If you are tracking ANZ startup hiring, focus on startups 12-18 months post-seed: that is when the first AE hire happens. QuantX Labs is Adelaide-based. Quantum tech is a federal priority, which helps fundraising but does not guarantee fast deal cycles. Defence procurement moves slowly. Expect long sales cycles, high ACVs, and a small, specialised sales team structure.

SmartCompany
2 months ago
News

Harvey hiring enterprise CSMs at $190M ARR, Assembly AI ditches CS title

## The Old CS Playbook Does Not Work for AI Products Three fast-scaling AI companies shared what they are doing differently in customer success, and it cuts against a decade of SaaS conventional wisdom. The details matter because these are the companies setting the pace: Harvey at $190M ARR serving 100,000+ attorneys across 60+ countries, Assembly AI selling API infrastructure to technical buyers, and Lovable scaling product at speed. ## Harvey: Enterprise CS Is Still High-Touch Tom Ronen, VP Customer Success at Harvey, runs an on-site, executive business review motion that looks like 2001. That is deliberate. Harvey is selling AI into 200-person law firms where partners have practiced the same way for 30 years. No automated health score gets you there. The company is hiring Enterprise Customer Success Managers with explicit focus on value realization, adoption, ROI, and C-suite legal stakeholders across the US, Canada, and Latin America. Harvey is backed by Sequoia and OpenAI's startup fund, positioning against legal workflow and document automation platforms. **Takeaway for sales:** If your product requires deep behavior change inside a skeptical enterprise org, high-touch CS is a competitive moat, not a relic. ## Assembly AI: The CSM Title Is Broken Ryan Seams, Head of Customer Success and Solutions at Assembly AI, watched technical buyers change body language the second he said "customer success." They got defensive. The title now signals QBRs and renewal pressure, not technical partnership. Assembly AI tried renaming roles to Technical Account Manager. Recruiting died: two candidates in two and a half months. They switched to Forward Deployed Engineer. Pipeline filled immediately. The actual job barely changed. The brand did. **Takeaway for sales:** Audit what your titles signal to technical buyers. The words on your Slack profile change whether a customer leans in or shuts down. ## Lovable: Stop Saying AI Monica Perez, Global Head of Customer Success at Lovable, stopped leading with AI in customer conversations. Her argument: saying "AI-powered" signals you are behind, not ahead. AI is becoming baseline infrastructure. Lovable's onboarding opens with what the customer will unlock, not what the technology can do. The moment you stop saying AI in every conversation is the moment you become AI-native. ## What Actually Drives Retention Bobby Cooper, founder of Retention Intelligence, shared platform data showing over 50% of CSM activities have no correlation with retention. CSMs accrete work over time, become jacks of all trades, and teams bloat. The fix: map every activity to whether it changes the product outcome for the customer inside the intended timeline. If it does not, it has no place in the playbook. **Takeaway for go-to-market:** Run a time-and-motion study on your post-sales team before you add headcount. You are likely funding work that does nothing for retention. ## Adoption Is Not Enough Anymore For traditional SaaS, decent seat utilization plus the same buyers at renewal meant CS did its job. That breaks with AI products. A law firm can log into Harvey constantly without changing how it operates. Logins are not transformation. Harvey tracks five ROI pillars and asks CSMs to tag value stories against them, because the goal is reducing non-billable work and speeding up matters, not racking up active users. **Worth noting:** These are AI-native companies redesigning CS around product speed and technical buyer expectations, not legacy process. The competitive set matters. Harvey competes with legal-tech enterprise vendors. Assembly AI competes with speech-to-text and voice AI infrastructure providers. Lovable is growing extremely fast in a category where users build software in plain English. The CS model follows the product motion, not the other way around.

SaaStr
2 months ago
News

Token budgets hit SaaS: AI spend forcing sales and CS headcount cuts

## Token Budgets Are the New Headcount Fight Engineering leaders are getting a new budget question: keep your 400-person team, or cut to 300 and spend the other 100 salaries on AI tokens. The numbers coming out of early adopters: Uber caps engineers at $1,500/month in token spend, roughly $18k/year or 10% on top of a $200k engineer. Brandon at McCor says they now spend more on tokens than engineering salaries with 80 engineers. The EDA software market, historically the most tool-heavy segment, runs about 13% of engineering spend on tooling. Jason Lemkin's read: the best shops push past 10%, maybe a third or more. Rory O'Driscoll thinks that math is aggressive. Nobody has run a full org at that ratio yet. ## What This Means for Sales and CS Roles The first cuts in 2024 were about survival. The second wave is about choosing tokens over marginal headcount. Bottom of the QA list, CS roles that can be automated, inbound SDRs closing $3k deals. The roles that survived the first layoff wave are now being measured against AI cost. SaaStr already made the call: cut B players, spend on tokens instead. The bet only works if your VP of Engineering can ship product with fewer people. Fast-growing companies say yes. Slow-growing companies say it cannot be done. ## Why Comp Matters Here If corporate America settles at 10% token spend relative to engineering cost, you get to the Anthropic and OpenAI growth curves without mass layoffs. At 33%, you are looking at one in three or one in four roles across product and engineering getting replaced. Sales and CS roles that touch product or require technical context are in the blast radius. The other data point: Anthropic raised $65b and filed to go public in the same week. ARR up 28% since the last quarter. When the best company of the decade goes zero to trillion in five years, it warps the bar for everyone else. VCs are now screening for billion-dollar positions, not billion-dollar outcomes. That means faster growth, bigger TAMs, and less tolerance for blockers like small teams or capped markets. ## The Takeaway for Sales Professionals If you are in a technical sales role, ask your leadership what the token-to-salary ratio is for your engineering team. That number is your leading indicator for where headcount lands in 2027. If your company is slow-growing and the ratio is climbing, start looking. If you are fast-growing and leadership is betting on tokens, make sure your role is tied to revenue, not process. Comp transparency matters more now. Real OTE, realistic attainment, ramp periods. The market is resetting fast, and the roles that survive are the ones that prove they drive pipeline, not the ones that just touch it.

SaaStr
2 months ago
News

Adelaide AI email startup Nitrosend raises $700k seed

## Adelaide AI email startup Nitrosend raises $700k seed Nitrosend, an Adelaide-based AI email marketing platform, closed a $700,000 seed round led by Eastend Ventures, with participation from Archangel Ventures and Aussie Angels. The company was founded by brothers Edward and George Hartley, who previously built SmartrMail, an email automation tool that scaled to 6 billion emails sent before being acquired by Relay Commerce in 2022. They brought back their former CTO, Kam Low, as a founding team member for the new venture. ### What they are building Nitrosend positions itself as an AI-native email platform. Instead of drag-and-drop template editors, users describe campaign goals in natural language (via Claude, ChatGPT, or the Nitrosend platform), and the system handles writing, design, sending, and performance reporting. The platform also automates workflows like welcome sequences, cart abandonment, and customer segmentation. Target market: SMBs that lack dedicated marketing resources or agency budgets. ### Early traction The company signed 190 users since April 2026, including early-stage startups Elita Genetics and Fast Lane. No public customer count, revenue, or sales headcount disclosed. ### Market context Nitrosend sits in the crowded AI email marketing segment alongside Mailchimp, Klaviyo, ActiveCampaign, HubSpot, and newer AI-native tools. Their differentiation: 10 years of email infrastructure experience combined with AI workflow automation. For sales teams evaluating martech stacks, the platform could reduce reliance on marketing ops resources for campaign execution, though enterprise buyers will want to see more proof of scale. Eastend Ventures founding partner Josh Garratt: "Experienced founders going after a market they already understand better than anyone, at exactly the moment that market is being reshaped by AI." Worth noting: the company appears to be operating with a founder-led commercial motion rather than a dedicated sales org at this stage. No sales hiring announced.

Startup Daily
2 months ago
News

SaaStr updates VP of Sales interview guide: AI fluency now mandatory

# SaaStr updates VP of Sales interview guide: AI fluency now mandatory Jason Lemkin has updated his widely-shared VP of Sales interview framework for 2026, and the changes reflect what is happening on sales floors right now: AI agents are handling meaningful pipeline volume, title inflation is worse than ever, and the VPs who do not know their Clay from their Artisan are getting left behind. The original advice still holds. Do not hire a VP of Sales until you have proven the motion yourself, either by making 1 to 2 reps successful first, or by hitting $1M to $2M ARR with founder-led sales plus AI SDRs. If you skip this step, you will fire whoever you hire in 9 months. No exceptions. But the screening questions have evolved. The classic filters are still there: team size estimation, deal size fit, direct management experience, recruiting ability, tool stack opinions. If a candidate cannot answer those fluently, pass. What is new for 2026: two critical additions that separate modern sales leaders from people who just have the title on LinkedIn. **Question 5: How are you using AI agents in your current sales motion?** If they hedge, say "we are exploring it," or defer to ops, pass. The right answer sounds like specifics: Artisan for outbound, Qualified for inbound chat, Gong for call analytics, Clay for enrichment, Agentforce for win-back. If your candidate is not fluent here, they are going to be an expensive observer of what your competitors are doing. **Question 6: How has your ideal rep profile changed in the last three years?** Listen for evolution. The best VPs are hiring fewer SDRs because agents handle prospecting. They are hiring AEs who can run their own AI workflows. They are cutting the bottom 20% faster because AI raises the floor on what an average rep can produce. If they describe the same rep they hired in 2022, they have not been paying attention. The underlying reality: team sizes are often smaller than they would have been in 2023. If a candidate is pitching you 20 SDRs when 4 SDRs plus an Artisan deployment would do the same job, that is a tell. They are playing the old playbook. The full 15-question framework is worth reading if you are hiring or evaluating a VP of Sales role. The questions are designed to create dialogue and surface whether you have a real VP candidate or someone who just has the title. Give them enough data ahead of time so they can answer with substance. If they did not do the homework before the interview, that is your answer right there. One constant that has not changed: 50% of the job of VP of Sales is recruiting. AI does not recruit your reps for you. Your VP does. If a candidate cannot describe the reps they hired and where they found them, they are not a real leader. They are a manager who got promoted into something they do not actually do. Worth noting: this guidance aligns with what sales recruiters and sales ops leaders are seeing in the market. The bar for VP of Sales has moved. AI fluency is not a nice-to-have. It is table stakes.

SaaStr
2 months ago
News

SiteMinder share price jumps after 20-year pivot to AI booking channels

## The Setup SiteMinder, the Sydney hotel commerce platform founded in 2006, just announced integration with AI booking channels via Model Context Protocol. Share price is up. The company supports 41,000+ hotels across 150 countries, primarily independent and SME properties using their channel manager to distribute inventory across OTAs. The timing matters: SiteMinder got caught in the early 2026 software sell-off alongside every other SaaS company that wasn't immediately profitable. Their valuation dropped despite consistent revenue growth. Now they are pivoting product strategy while the market reassesses. ## What Changed SiteMinder is positioning beyond traditional channel management into what they call an "open hotel commerce platform." The Model Context Protocol integration means hotels can surface inventory through AI-powered booking agents, not just Booking.com and Expedia. The company has been delivering growth year-over-year. The question now: can they convert that growth into profitability while expanding into AI distribution? ## The Sales Angle For ANZ sales professionals, SiteMinder represents a rare local success story in hotel tech. Founded in Sydney by Mike Ford and Mike Prewitt, the company built a genuine global footprint in a category they essentially pioneered. What we don't have: current headcount data, recent ANZ hiring numbers, or specific comp ranges for their enterprise sales roles. Public sources confirm the founders but not the current CRO or VP Sales. That leadership matters when evaluating a "next growth phase" story. Worth noting: SiteMinder competes with integrated PMS vendors (Cloudbeds, Hotelogix) and standalone distribution tools. Their positioning has always been strongest with independent hotels that need channel management without full PMS replacement. ## The Numbers We Need The original article promises a financial teardown but the available sources don't provide ARR, revenue multiples, or EBITDA figures. For a SaaS comeback story, those metrics matter more than share price movements. If SiteMinder is genuinely entering a growth-plus-profit phase, the sales team structure and quota models would be shifting. Enterprise AE roles at a 20-year-old company moving toward profitability look different than at a growth-at-all-costs startup. ## What To Watch AI booking channels could expand SiteMinder's addressable market or commoditise their core channel management play. Either way, it changes the sales motion. If you are evaluating enterprise sales roles in hotel tech, the competitive landscape just got more interesting. For now: strong distribution footprint, proven founder story, unclear path to profitability. The AI pivot is worth monitoring but show us the attainment data.

SmartCompany
2 months ago
News

Meta AI chatbot let hackers reset Instagram passwords by asking nicely

## The hack that required no hacking Over the weekend, attackers took over multiple high-profile Instagram accounts by chatting with Meta's AI support bot. Targets included Barack Obama's former White House account, Sephora, and the US Space Force Chief Master Sergeant. The method: open a chat with Meta AI, ask it to add a new email address to the target account, paste the verification code the bot sends, then click "reset password." In some cases, attackers used a VPN to match the victim's region. At no point did they need access to the legitimate email already on the account. Meta says the issue is fixed and affected accounts are being secured. The structural problem has not changed: an AI agent with the authority to modify emails and reset passwords is a security control point, and this one failed. ## Why this matters beyond Meta Many ANZ SMBs use Instagram for customer acquisition, paid social, and brand presence. Account compromise interrupts lead generation and damages trust. The reporting shows that users hit by takeovers struggled to escalate to a human, which underscores the operational risk of relying on automated support for mission-critical recovery workflows. Meta rolled out AI-assisted support across Facebook and Instagram to handle account recovery tasks at scale. That decision made the chatbot a high-impact control point. When guardrails are weak, AI support does not just scale service: it scales risk. ## The support angle This is being framed as a hacking story. It is also a support story. Meta's AI agent had the permissions to change account ownership without sufficient verification. The same automation designed to reduce support load became the vector for account takeover. For sales and marketing teams that depend on social platforms for pipeline and customer engagement, the lesson is clear: verify what access your support automation actually has, and whether the trade-off between efficiency and control makes sense for your business. Meta's AI-assisted support is now being judged not only against social platforms like TikTok and Snapchat, but also against the trust standard set by identity providers and customer-support automation tools. This incident will be referenced in procurement conversations for months.

SmartCompany
2 months ago
News

Florida sues OpenAI, names Altman personally in first state lawsuit

Florida became the first US state to sue OpenAI and CEO Sam Altman personally, alleging the company knowingly released ChatGPT while concealing serious risks. Attorney General James Uthmeier claims OpenAI suppressed internal safety warnings and deceived users. The lawsuit references two shootings where alleged gunmen asked ChatGPT questions while planning attacks. Florida opened a criminal investigation in April after a shooting at Florida State University. OpenAI maintains its models "repeatedly encouraged the individuals to seek real-world support, including from mental health professionals." The company says it co-operated with law enforcement in both cases and that ChatGPT is "used by hundreds of millions of people every day for legitimate purposes." ## What This Means for Enterprise Sales If you are selling AI tools or using ChatGPT in your sales process, the regulatory environment just got more complicated. This is the first state-led action against OpenAI, but it follows existing EU GDPR concerns and enterprise compliance questions. Key considerations: **Procurement risk**: Enterprise buyers are now dealing with a vendor under active litigation. Security and legal teams will ask harder questions during eval cycles. Expect longer deal cycles and additional compliance requirements in contracts. **Competitive positioning**: If you are selling against ChatGPT Enterprise or using it internally, this creates an opening. Competitors with cleaner regulatory records can lean into compliance and safety positioning. If you are an AE selling Anthropic, Google, or other alternatives, this lawsuit is relevant context for your discovery calls. **Internal usage policy**: Sales teams using ChatGPT for email drafts, research, or prospecting need clear company policy. Legal and IT will be reviewing what data goes into these tools and what comes out. Florida alleges OpenAI prioritised speed and commercial gain over safety. Whether that claim holds up in court, the message to enterprise buyers is clear: regulatory pressure on AI vendors is real and escalating. Factor that into your tech stack decisions and procurement conversations. OpenAI remains one of the dominant AI providers globally, competing with Anthropic, Google DeepMind, Meta, and xAI. The company has not disclosed revenue or headcount, but ChatGPT has mass-market reach. For ANZ enterprise buyers, this is another data point in the ongoing conversation about AI vendor risk and compliance requirements.

SmartCompany
2 months ago
News

SaaStr runs 4 AI SDR agents, not one: Artisan, Qualified, Agentforce, Monaco

## The Stack SaaStr is running four AI SDR agents in production. Not one platform doing everything. Four vendors, four contracts, four different jobs. **Artisan for outbound.** Three instances running parallel. Different personas, different ICPs. 40,000+ messages sent. Does cold outbound at scale, does it well. **Qualified for inbound.** 100,000+ sessions processed. Over $1M closed through the inbound motion. When someone hits the site, Qualified qualifies, books, routes. Purpose-built for that moment. **Agentforce for Salesforce-native reactivation.** Close to 200,000 messages sent. 72% open rates on win-back campaigns. Lives inside Salesforce, has every data point already. No integration mess. **Monaco for net new logos.** Different ICP data, different outreach pattern than farming the install base. Four agents. Four admin consoles. Jason Lemkin (SaaStr founder, ex-EchoSign) says they would do it again. ## The Case for Specialised All-in-one platforms promise simplicity. Reality: mediocrity across every function. Each motion (outbound prospecting, inbound qualification, reactivation, new logo land) has a different shape. Different data, different success metrics, different optimal behaviours. Outbound is volume with tight personalisation. Inbound is speed with intent signal interpretation. Reactivation is context with deep CRM history. New logo is research with ICP precision. No platform today does all four at A+ quality. A platform that is 60% good at all four costs you more than four platforms that are 95% good at their one thing. The cost shows up in pipeline, conversion rates, closed-won dollars. ## The Real Cost Running four platforms costs more than one. Four contracts, four minimum commits, four implementation cycles. Real dollars, not just work. You pay in operational surface area: four sets of credentials, four data flows, four sets of prompts to optimise, four vendor relationships, four security reviews. You need headcount. At least one person, ideally two, dedicated to managing deployment. AI agents are not zero-headcount tools. One person cannot hold tribal knowledge of how four platforms are configured. Why pay it? Because the quality gap between specialised and generalist AI agents is big enough that the extra cost pays for itself in pipeline. Difference between $1M closed and $300K closed. Difference between 72% open rates and 22%. ## If You Are Starting Out Most companies do not need four AI SDR agents to start. For 90%+ of B2B companies deploying their first AI SDR, one vendor can make material gains. Two at most: one for outbound, one for inbound. SaaStr runs four because they have pushed each motion into highly segmented territory after 10+ months of production. Roughly 100 effective segments across 1,000 contacts at a time. At that level of segmentation, no single platform handles all of it well. If you are standing up your first AI SDR, do not start here. Pick the one platform that covers your biggest motion and go deep. Prove that motion works. Then layer in a second tool when the first is producing real pipeline. Starting with four will get you four mediocre deployments instead of one great one. The tool matters far less than the strategy you bring to it. ## What This Means The AI SDR market is splitting. All-in-one platforms for teams getting started. Specialised tools for teams at scale with segmented motions. If you are evaluating AI SDR tools, the question is not which single platform wins. The question is: what is your biggest motion, and which tool does that one thing best? Once that motion is working, you can layer. Until then, the complexity of managing multiple agents is not worth it. The specialisation advantage only kicks in once you have outgrown the generalist answer.

SaaStr
2 months ago
News

DataMasque raises $5.6M: NZ data privacy play targets enterprise AI spend

**DataMasque closed $5.6 million** led by Wavemaker Partners, with OIF Ventures and Icehouse Ventures participating. The New Zealand startup builds data masking software for enterprises that need to use sensitive customer information for AI training, testing, and analytics without compliance headaches. **The pitch:** synthetically identical data that preserves relationships and statistical properties while stripping personally identifiable information. CEO Grant de Leeuw describes it as changing a date of birth but keeping the age intact, so AI models train on realistic data without touching real customer records. **Deployment model matters here.** DataMasque runs inside the customer's environment (cloud, hybrid, on-prem) rather than shipping data externally. That addresses a common enterprise objection around exfiltration risk, particularly for regulated industries where data residency and compliance drive procurement. **Growth metrics:** six times ARR growth and triple headcount. Actual revenue and team size were not disclosed. The company appears to sell direct to enterprise and has leveraged AWS Marketplace for distribution, suggesting a partner-assisted enterprise motion alongside direct sales. **Market context:** this sits in the data security posture management and synthetic data category, competing with broader privacy platforms and specialist vendors. The regulatory compliance angle (particularly in banking and healthcare) is driving enterprise spend here. Gartner tracks this space under data security platforms and DSPM vendors. **Previous funding:** DataMasque raised $2.7 million from OIF Ventures and Icehouse Ventures previously. Whether the $5.6 million is cumulative or a fresh round was not specified. **What this means for sales teams:** if you are selling into regulated enterprises (financial services, healthcare, government), expect data privacy and AI compliance questions in procurement. Solutions like this enable deals that would otherwise stall on data governance concerns. Also worth tracking which competitors are building similar capabilities into existing platforms versus buying point solutions like DataMasque.

SmartCompany
2 months ago
News

Entrata IPO at $575m ARR, 23% growth tests PE software exit market

Entrata filed its S-1 on May 28 to list on the NYSE under ticker ENT. The multifamily property management platform is at $575m ARR, growing 23%, with 16% operating margins and real GAAP profitability. Silver Lake has held majority control since 2022. The numbers are solid but not exceptional. Growth held flat at 23% year-over-year in Q1 2026. Net revenue retention sits at 117%, also flat across 2024 and 2025. Rule of 40 score is 47 on a non-GAAP basis. This is efficient growth, not breakout growth. What makes Entrata notable is timing. The company is the leading edge of a backlog of PE-backed software trying to exit, and private equity tends to move first when the window opens. The problem: public markets have decided efficient growth is not enough anymore, and almost none of the companies lined up behind Entrata are accelerating. Entrata's core business is property management software for multifamily operators. The platform consolidates roughly seven systems: leasing, accounting, payments, insurance, screening, utilities, resident apps. The company has 233 customers spending more than $500k annually, accounting for 84% of ARR. Average customer pays $216 per unit, up from $175 two years ago. Top customers pay $580 per unit. Payments is mandatory. Every customer using the platform must process payments through Entrata. That forced attach is why the company still posts 60% gross margins despite booking payment processing fees gross, the same way Toast does. Three years ago, Entrata ran breakeven. In 2022 and 2023, GAAP operating margins were negative 1% and negative 2%. In Q1 2026, operating margin hit 26%. Revenue nearly doubled while the company flipped to $50m+ in annual GAAP net income. Before filing, Entrata paid itself a $356m dividend funded with a $400m term loan. The company now carries about $270m of net debt into its IPO. Part of the offering proceeds will pay that loan back down. Standard sponsor-backed IPO structure. For ANZ sales professionals watching software exit timelines, Entrata is the test case. If a $575m ARR company at 23% growth can price well, the PE-backed software backlog has a path. If it does not, expect the exit queue to get longer. No confirmed ANZ presence or sales team details available at this stage.

SaaStr
2 months ago
News

Scalare Partners buys Fishburners for undisclosed sum after administration

## The Deal Scalare Partners (ASX: SCP) acquired Fishburners in a cash-only transaction completed today. Terms were not disclosed. The ASX filing says the deal is "not material" to Scalare's financial position. What they bought: Fishburners brand, programs, IP, and community assets. What they did not buy: employees, physical assets, or liabilities. Clean acquisition of a distressed brand. ## Why This Matters Fishburners entered voluntary administration last month after failing to resolve $2 million in rental arrears owed to the NSW government. The Sydney Startup Hub location (now closed) cost more than $1.5 million a year in rent. The numbers did not work. Scalare is building a portfolio of founder-facing infrastructure: Tank Stream Labs (seven coworking locations across Sydney, Melbourne, Adelaide), Planet Startup, InHouse Ventures, The Founders Union. This is their fourth acquisition since listing on the ASX. Pattern recognition: they are consolidating startup support services, not just writing cheques. ## What It Means for Sales Teams Fishburners has supported 35,000 founders since 2011. Those founders need sales tools, SDR platforms, CRM systems, and go-to-market advice. Scalare CEO Carolyn Breeze now controls access to that community across multiple brands and locations. If you sell to early-stage tech companies in ANZ, Scalare's roll-up strategy matters. One buyer, multiple touchpoints, consolidated decision-making on vendor relationships and ecosystem partnerships. The administration write-down likely made this acquisition cheaper than building equivalent brand recognition from scratch. Worth noting: no staff were included in the deal. Any future Fishburners hiring will be new roles under Scalare's structure. ## The Broader Picture This is the second major Sydney startup infrastructure deal in recent months. Tank Stream Labs sold to Scalare for $5.5 million. The NSW government shut down Sydney Startup Hub last year, forcing Fishburners to relocate to Tech Central before the administration. Startup support services are consolidating. If you are targeting early-stage founders in ANZ, your potential buyer landscape just got smaller and more concentrated.

Startup Daily
2 months ago
News

Anthropic runs Clay, Salesforce, Gong: Claude updates the CRM, not the AEs

Anthropic is not running on some self-built, AI-native sales platform. The company uses the same six tools most enterprise SaaS companies run: Clay, LeanData, Salesforce, Gong, Ironclad, and Slack. Claude is the substrate, but it connects to the core B2B stack. The difference is what they do with each tool. **Clay is the funnel gate.** Most teams use Clay to enrich inbound leads. Anthropic uses Clay plus Claude to qualify every lead at the moment of capture and route it to either the AE-led path or the self-serve path within seconds. No human review. Result: 54% of new enterprise logos in 2026 came through self-serve. **LeanData routes to humans and AI.** The router no longer just decides which AE gets the lead. It decides whether a human gets it at all. Leads can route to a BDR queue, an AE directly, or to the Intercom Fin guided self-serve flow. **Salesforce is where Claude updates.** AEs do not manually log calls or update opportunity records. Claude does. The morning briefing reconciles opportunity records against context pulled from Gong calls, emails, and Slack threads. AEs inspect and approve. The forecast call is no longer a data-scrubbing exercise. It is a discussion about where AEs need help, because the data is already current. **Gong is the highest-value context source.** Claude pulls Gong transcripts into the morning briefing, the call prep workflow, the proposal-drafting workflow, and the weekly coaching loop. When a rep types `/call prep` before a meeting, Claude reads Gong transcripts of every prior call with that account to generate the briefing. The coaching loop is dynamic: Claude surfaces six coaching moments per week based on call analysis. **Context for ANZ sales leaders:** Anthropic is hiring a Head of GTM Systems to own CRM, CPQ, Salesforce architecture, billing, order management, and revenue-recognition workflows. The company is also building out international GTM with a Head of Enterprise Sales for Industries in ANZ and a broader Head of International GTM Strategy and Operations role. That signals Anthropic is building a conventional enterprise sales organization even as it markets itself as an AI-native company. The stack is not new. The connective tissue is. If you are running Salesforce, Gong, and Clay today, the question is not whether to replace them. It is what happens when AI can read, write, and route across all of them without waiting for a rep to log in.

SaaStr
2 months ago
News

Dashdot liquidates, cuts 40 jobs, blames CGT changes for investor collapse

## What Happened Property investment advisory Dashdot collapsed into voluntary liquidation last week, cutting more than 40 jobs. The seven-year-old Australian startup appointed Teneo's Rebecca Gill and Martin Ford as liquidators. CEO Gabi Billings (co-founder alongside former cricketer Glenn McGrath) blamed federal budget capital gains tax reforms, Meta advertising platform changes, and broader economic conditions for tanking investor demand. Customers who paid thousands in upfront advisory fees are now waiting to see what happens to their money and their property deals. ## Why It Matters This is a demand-collapse story, not a product failure. Dashdot's business model relied on steady investor appetite for property advisory services. When federal tax changes spooked the market, the customer pipeline dried up faster than the company could adjust its cost base. Forty-plus jobs gone suggests either a small total headcount or a service-heavy model with high people costs relative to revenue. Either way, when your revenue is tied to investor confidence and policy changes tank that confidence, you are exposed. ## What Sales Teams Should Note If you are selling to property investors or adjacent markets (mortgage brokers, wealth advisors, tax accountants), watch for ripple effects. Dashdot's collapse signals that retail property investment is cooling, which means related B2B sales pipelines could slow. For anyone in advisory or service businesses with big upfront payment models: this is what happens when demand drops and you cannot pivot fast enough. Dashdot bet on continued investor appetite. That bet did not land. Worth noting: Meta ad changes got cited alongside tax reforms. If your customer acquisition depends heavily on Facebook and Instagram ads, you are vulnerable to platform risk. Diversify your channels or accept that exposure. The liquidators are from Teneo, a major restructuring firm. That means creditors (including staff owed entitlements and customers owed refunds) will be queuing up. Unsecured creditors rarely get much back.

SmartCompany
2 months ago
News

WiseTech cuts 2,000 jobs, blocks staff from joining four rivals for 12 months

## The Numbers WiseTech Global announced 2,000 redundancies in February, roughly 30% of its workforce. The ASX-listed logistics software company ($1.19 billion revenue, 975 employees in controlled subsidiaries per IBISWorld) is now inserting non-compete clauses into severance agreements that ban affected workers from joining four named competitors for 12 months: Expedient Software, Clear.AI Systems, Yojee, and Trade Window. Professionals Australia, the union representing affected employees, wants the clauses removed. WiseTech is holding firm. ## Why This Matters for Sales Teams If you are in enterprise software sales in ANZ, this is your market reality check. WiseTech sells CargoWise, mission-critical logistics platform software to freight forwarders globally. The company has framed these cuts as an AI transformation. Staff reportedly sat through months of uncertainty while leadership talked up AI doing work "faster, cheaper, and with less human constraint." Now the severance terms are restricting where people can work next. That is unusual for redundancy packages in Australia, where non-competes during employment are common but post-termination restraints face higher legal scrutiny. ## What Sales Professionals Should Know Severance terms are negotiable, even when HR says they are not. Non-compete clauses in redundancy agreements can be challenged, especially if: - The restriction is broader than necessary to protect legitimate business interests - You were made redundant (you did not resign or get fired for cause) - The payout does not compensate you for the income restriction WiseTech has not publicly disclosed the severance quantum or whether additional compensation offsets the 12-month restraint. That matters. If you are being asked to sign away your ability to work in your field, the package should reflect that cost. ## The Broader Pattern This is WiseTech's second workforce story in a month. CEO Zubin Appoo reportedly received a threatening letter as redundancy consultations began. Founder and Executive Chair Richard White called in police. The company has been writing a narrative of leadership choices under pressure: AI pivot, mass redundancies, long consultation periods, now restrictive post-employment terms. For sales professionals watching from the sidelines: when a company makes you redundant, it is saying your role is no longer needed. Blocking you from using your skills elsewhere for a year is a different conversation. One that usually costs more than standard redundancy pay. ## What You Can Do If you are facing redundancy with a non-compete: 1. Get the severance offer in writing 2. Calculate what 12 months of lost opportunity costs you (not just base, but OTE and career progression) 3. Ask for legal advice (many employment lawyers offer free initial consults) 4. Negotiate. Severance terms are not take-it-or-leave-it, despite what the first offer implies WiseTech is a founder-led company (Richard White co-founded it in 1994). That can mean strong culture and vision. It can also mean decisions get made top-down without the usual HR checks. Either way, if you are holding a severance agreement that limits where you can work, you have more leverage than you think.

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