The Wire

Real-time updates from ANZ tech sales

21 days ago
News

Graduates booing AI at ceremonies: warning for sales teams cutting SDRs

## The booing heard across LinkedIn Graduation season brought viral clips of something uncommon: crowds of graduates loudly booing speakers the moment they mentioned AI. Eric Schmidt at University of Arizona. Gloria Caulfield at University of Central Florida. Scott Borchetta at Middle Tennessee State. Same story: mention AI as opportunity, get drowned out. The footage split viewers into two camps. One dismissed graduates as anti-progress. The other said the speakers misread the room, selling AI as pure upside to a cohort watching entry-level roles vanish. ## What this means for sales orgs Australian sales teams are automating SDR and BDR work at pace. Sequence tools handle outbound. AI qualifies inbound. Chatbots book meetings. The logic is simple: cut headcount, protect margin, scale faster. The problem: you are eliminating the cohort that grew up with this tech. Fresh graduates understand LLMs, prompting, and AI limitations better than most VPs. They also spot when automation breaks personalisation or when your AI-generated emails sound like every other AI-generated email in the prospect's inbox. Sales orgs that cut all junior roles are trading short-term cost savings for long-term capability gaps. Who trains your future AEs? Who tests your new tech stack? Who tells you when your AI outreach is getting flagged as spam? ## The reckoning no one is prepping for The booing is not about rejecting technology. It is about graduates entering a market where the traditional pathway (SDR to AE to manager) is closing. ANZ tech companies that historically hired 10 SDRs per quarter are now hiring two and a chatbot. Meanwhile, enterprise deals still require human relationship-building. Mid-market still needs discovery calls. Complex sales still need people who can read a room. Automating everything assumes AI can replace judgement. It cannot. Not yet. Smart sales leaders are not asking whether to use AI. They are asking which parts of the role actually benefit from automation and which parts get worse. Cutting all junior roles because you can is not strategy. It is cost accounting. The graduates booing AI are not anti-technology. They are anti-being-replaced-before-they-start. If your sales org is automating without a plan to develop the next generation, you are building a team with no bench and no institutional memory. That shows up in quota attainment two years from now, not two quarters.

SmartCompany
22 days ago
News

OpenAI CEO calls AI email tools dehumanising, admits revenue model unsolved

OpenAI CEO Sam Altman told business leaders in Sydney he tried letting AI handle his emails and Slack messages, then stopped. "I found it surprisingly dehumanising to watch, even when I had it reply to messages," Altman said during a virtual appearance at Commonwealth Bank's AI conference. "It was an amazing example to me of like, we really do care about people and we really do care about our interactions with people." The admission matters because every SDR and AE is being pitched AI email tools right now. Subject line optimisation. Sequence automation. Reply generation. The CEO of the company behind ChatGPT just said he will not use that tech for his own communication. Altman also confirmed OpenAI's revenue model is still evolving: "Revenue will take a bit longer to figure out." The company runs on a mix of ChatGPT subscriptions, API usage, and enterprise deals, but no mature sales organisation yet. That tracks with what we are seeing in market: strong product adoption, unclear go-to-market motion. For ANZ sales teams, the gap between AI capability and actual adoption is the story. Tools exist. Usage is growing. But Altman's comments suggest even true believers hit a wall when automation replaces human connection. OpenAI has positioned itself beyond chatbots and into workplace productivity. Altman previously called Slack "fake work," arguing AI agents could handle routine coordination. Now he is saying AI should not handle his own messages. The tension is real: efficiency versus authenticity. Practical takeaway for sales professionals: AI can draft sequences and summarise calls. It cannot replace the relationship work that closes enterprise deals. The companies building these tools know it. The question is whether procurement teams buying AI sales assistants know it too. OpenAI remains privately held with strong ANZ product usage but limited public disclosure on local operations. The company's enterprise motion will matter more than its consumer chatbot when evaluating market impact for ANZ sales organisations.

Startup Daily
22 days ago
News

Owner.com reps closing $2M ARR each: AI workflow, not AI theatre

## The Numbers Owner.com reps are closing $2M+ in ARR per year. Average, not top performer. A $150K OTE rep brings in 20x their comp in closed-won revenue. BDRs are closing $100K+ ARR per month, not booking pipeline. Owner sells vertical AI to independent restaurants: websites, ordering, marketing automation, loyalty. Think HubSpot plus Shopify for the corner takeout spot. They are at roughly $100M ARR, up from $2M when CRO Kyle Norton joined in 2022. Flat $499/month per location, 10,000+ restaurants. At SaaStr AI 2026, Norton walked through how they built the GTM motion. The talk matters because these are real B2B subscription numbers, not usage revenue or token sales. ## The Architecture Norton's thesis: most companies are stuck at "Level 1" AI adoption (reps building custom GPTs, Slacking markdown files to each other). Owner is at Level 3: centralized infrastructure, shared skills, context library. The gap between Level 3 and everyone else is widening exponentially, not linearly. Three decisions drove the outcome: **Centralized AI, not decentralized.** A small applied AI team owns production builds. Ideas bubble up from reps, but a central team ships the tools. What their AI lead builds is 5-10x better than what a rep builds on a weekend. Why have 20 people build 20 mediocre tools when one team can build one that moves a number? **Build intelligence, buy infrastructure.** Norton's framework: run every decision through five questions (uptime criticality, customization need, engineering ROI, proprietary intelligence, competitive advantage). Dialers and sim platforms: buy. Pre-call research built on Owner's proprietary restaurant marketing data: build. That AI pre-call research tool cost two weeks of one engineer's time. BDRs now book 85% more meetings. **Start with data, not demos.** Third-party data (full market map, scored accounts, right contacts) and first-party data (CRM hygiene, closed-loop attribution, what actually converts). Norton's take: most companies skip straight to the fun part (building agents, running experiments) and wonder why nothing scales. The constraint is not the AI, it is the data. ## What This Means These numbers (20x close-won to OTE, $100K+ closed ARR per BDR per month) are not normal SMB SaaS metrics. Owner's closest comp is the website builder plus online ordering plus marketing automation stack for independent restaurants. They are selling a premium bundle ($499/month) with strong personalization and claiming LTV:CAC of 4.5:1. The broader point: AI is not about reps using ChatGPT as a smarter search engine. It is about workflow architecture that removes friction from the entire motion. Norton's warning: the gap between companies with centralized AI infrastructure and everyone else is compounding fast. Not 10-15% productivity lift. Per-rep output doubling. Worth noting: Owner is a US-focused vertical AI play. No material ANZ presence in available data. The framework still applies to any B2B sales org evaluating AI investment.

SaaStr
22 days ago
News

Cable raises $4m pre-seed, targets SME energy savings with battery play

# Cable raises $4m pre-seed, targets SME energy savings with battery play Sydney energy startup Cable closed $4m in pre-seed funding and opened public beta access for businesses in the Sydney metro area. The round came from UK firm Systemiq Capital (first Australian investment) and Black Nova VC, plus angels. ## The model Cable installs batteries at SME premises at no upfront cost, uses them to access cheaper electricity prices, then bills customers based on usage. Founder Dominic Reardon claims savings of up to 40% compared to standard retail rates. The startup owns the batteries. Customers pay for energy consumed, not hardware. The pitch: SMEs get household-style battery economics without capex. Cable has been running a private beta for six months. Public beta is now live for Sydney businesses. ## Market context This is battery-as-a-service for the SME segment. Households have had solar-plus-battery options for years. Large commercial operators negotiate demand-response deals. Cable is targeting the gap: businesses too small for custom energy contracts, too large to ignore their power bills. The 40% savings claim assumes specific usage patterns and rate arbitrage. Real outcomes will vary by site, consumption profile, and how pricing evolves. ## Not that Cable Worth clarifying: this is not Sun Cable, the Northern Territory solar export project backed by Andrew Forrest and Mike Cannon-Brookes that entered voluntary administration in January 2023. Different business, different model, different founder. Cable (the SME energy startup) was founded mid-2025. Sun Cable was founded 2018 and was pursuing a $30bn infrastructure play. ## What this means Pre-seed at $4m suggests early traction but no revenue scale yet. Public beta in one metro area means the model is still being proven. If it works, the sales motion is likely field-based: site assessments, install coordination, ongoing billing relationships. For sales context: this is not a SaaS motion. It is capital-intensive (batteries cost money), operationally complex (install crews, energy trading), and involves long sales cycles (site surveys, credit checks, contract negotiations). The team composition is likely more project managers and energy traders than SDRs. Systemiq's first Australian investment signals European capital is watching ANZ climate tech. Whether the unit economics work at SME scale remains to be seen.

SmartCompany
22 days ago
News

Medtech startup Oli raises $6.5M, total funding hits $22M

Sydney medtech startup Oli has raised $6.5 million in a Series A3 round. Scale Investors, Clare Ventures, and the University of Sydney backed the round. Total capital raised now sits at $13 million in equity plus $9.5 million in non-dilutive grants. That is $22.5 million total since the company was founded in 2018. Oli builds wireless wearable devices that monitor maternal and fetal signs during labour. The tech captures physiological data across 10 biosensors and runs it through what the company calls Predictive Maternal-Fetal Signal technology. The goal is to flag birth complications before they happen. The company was formerly called Baymatob. Founder Dr Sarah McDonald, a mechatronic engineer, started it after a traumatic birth experience with her second child. ## What this means for medtech sales Medtech sales is a different game to SaaS. Longer cycles, clinical validation requirements, hospital procurement committees. Oli is selling into hospitals and health systems, which typically means: - 9-18 month sales cycles - Clinical champions required for each site - Budget tied to capital equipment or departmental allocation - Comp structure often weighted toward base (70/30 or 60/40 splits are common in hospital medtech) - Territory coverage by state or regional health network No public information yet on Oli's commercial team structure, quota model, or whether they are hiring AEs or clinical sales specialists. Most early-stage medtech startups at this funding level run lean: 1-3 commercial hires covering ANZ, with founders still carrying the bag on key accounts. For reps considering medtech, the appeal is usually higher base salaries and more consultative selling. The trade-off is longer deal timelines and quota cycles that do not align with monthly or quarterly targets. Enterprise medical device OTE in Australia typically ranges from $140k to $200k depending on patch and product complexity. Worth watching whether Oli starts posting clinical sales or account manager roles in the next 6-12 months as they move from pilot programs to scaled hospital deployment.

SmartCompany
22 days ago
News

Birchal cuts valuation 87% to $5m in down round

## Birchal cuts valuation 87% to $5m in down round Melbourne equity crowdfunding platform Birchal has opened expressions of interest for a new raise at a $5 million pre-money valuation, or 9 cents per share. That is down 87% from the $40 million valuation it recorded in 2022, and 81% from its $26 million valuation in late 2024. CEO Kirstin Hunter told SmartCompany the diminished valuation reflects a business that has downsized through the broader crowd-sourced funding (CSF) market downturn. The company employs 11 to 50 people, according to Dealroom, though no breakdown of sales or go-to-market roles is publicly available. Birchal has helped 45-plus Australian businesses raise $29 million since 2018, operating under ASIC's CSF regime, which caps fundraising at $5 million per company across all platforms in a 12-month period. The company is raising at that statutory ceiling, which makes the valuation reset notable: Birchal is valuing itself at the maximum it can legally raise in a year. Hunter framed the down round as an honest reset. "A pessimist would look at this investment opportunity and say, 'Well, it hasn't hit its strides in the first eight years, why would I think this would be any different?' Whereas an optimist would look at it and say, 'Well, this has got eight years' worth of market-leading assets, it's been through a volatile time, had a leadership change, but its best days are still ahead of it.'" No revenue figures, quota structures, or sales leadership hires were disclosed. For context, Dealroom estimates Birchal's enterprise value at $10 million, which sits above the new pre-money valuation but reflects a company that has contracted significantly from its 2022 peak. Worth noting: Birchal previously highlighted that one Australian startup hit the $5 million CSF cap, positioning itself as a leader in the niche. This raise suggests the platform is applying that same ceiling to its own valuation, whether by design or necessity.

SmartCompany
23 days ago
News

Cars4Us founder invests $3 million in three founders after $120 million exit

## The Deal Matt Wright sold Cars4Us to Toyota Tsusho Corporation for $120 million earlier this year. He was 33. The Brisbane-based used-car marketplace had scaled to $500 million in revenue over six years. Now he is deploying $3 million of that exit into three founders: one in Australia, one in the UK, one in the US. Each gets $1 million equity investment in local currency, plus a year of mentorship through his Founder Finds Future initiative. ## The Numbers Context Most founders do not see $120 million exits. When they do, the actual take-home depends on funding rounds, dilution, and investor preferences. Wright founded Cars4Us in 2019, operated it through MCT Automotive Group, and appears to have retained meaningful ownership through the sale. The business was marketplace-focused, not SaaS, so no traditional sales org structure applies here. Typical founder equity after Series A sits around 50-70%, dropping to 20-40% by Series B or C. A $120 million exit at those ownership levels means $24-84 million before tax, which puts Wright's $3 million deployment at roughly 2.5-12.5% of potential proceeds. ## What He Learned "You can't outsource caring. No one's going to want it more than you. You set the pace," Wright told SmartCompany. The business grew from $182 million to $356 million revenue in two years. His explanation: "We obsessed over the numbers every single day. There's no clever trick to it." The sale process took 18 months with multiple parties at the table. Wright did not disclose final ownership structure or investor returns. ## Why It Matters This is not a VC fund or accelerator. It is a founder using exit capital to back other founders directly. The $1 million ticket size sits above angel checks but below institutional Series A. For sales professionals considering startup equity offers, the story reinforces the importance of understanding founder dilution and exit scenarios before signing. Applications for Founder Finds Future are open now.

SmartCompany
23 days ago
News

CBA testing AI agent for business loan apps, no human contact required

## CBA testing AI agent for business loan apps, no human contact required CommBank is piloting an AI agent that can process business loan applications without human involvement. The tool, called CommBank Companion, lives inside the bank's mobile app and handles income verification plus other application stages using customer data already on file. This is agentic AI, not a chatbot. The system takes action while it answers questions. It pulls your transaction history, analyses cash flow, and walks you through borrowing capacity. All automated. The catch: it will not recommend products. Banking regulations prevent AI from giving financial advice, so the agent stops short of suggesting which loan to take. You get data and eligibility, not a pitch. CBA has been running AI across fraud detection and internal productivity tools for a while. CEO Matt Comyn has pushed agentic systems that act autonomously but keep humans in the loop for final decisions. The business loan workflow is a natural target: document pre-population, credit reviews, onboarding automation. All tasks that eat hours when done manually. For context, CBA is Australia's largest bank by market cap. Roughly 50,000 employees. It deployed ChatGPT Enterprise to almost all staff and has highlighted partnerships like the Apate.ai fraud collaboration. This is scale automation, not a startup pivot. ### What this means for fintech sales If CBA's AI agent works, expect the other big four (NAB, Westpac, ANZ) to follow. That creates downstream pressure on fintech vendors selling loan origination systems, underwriting tools, or business banking software. When the banks automate internally, third-party sales cycles get harder. For professionals in fintech sales roles, this is the signal: AI is moving from productivity tool to process owner. If your patch includes banks or lenders, start mapping which workflows are getting automated and where human judgment still matters. That gap is where deals still close. The broader shift: loan processing automation is becoming table stakes. Fintech sales reps pitching AI underwriting or approval workflow tools need to show differentiation beyond "we automate applications." So does everyone else now. CBA has not published comp details for roles building or selling these systems, but the bank's business-banking and tech teams are the ones shipping this work. Worth tracking if you are eyeing fintech or financial services sales positions in ANZ.

SmartCompany
24 days ago
News

AI agents cost $257 monthly, handle SDR and ops work

## The economics have shifted SaaStr founder Jason Lemkin published numbers on two production AI agents: one handles marketing ops, one manages sponsor relationships. Combined monthly cost: $257. That figure covers LLM calls (mostly GPT-4o mini at under a cent per call), hosting, and database storage. The agents run 24/7, send personalised emails, update dashboards, compare year-over-year data, and manage a chatbot used by 100+ contractors. For context, the marketing agent handles work Lemkin's Director of Demand Gen used to do: weekly reporting, newsletter drafts, social posts, event prep. The sponsor agent sent 83 personalised emails at 12:20am without human involvement. ## What this means for SDR economics The cost comparison is stark. An entry-level SDR in Sydney costs roughly $80k base plus super, benefits, and desk space. That is $6,600+ monthly before commission. The agent stack runs at $257. But cost is not the full picture. The agents cannot do strategy, navigate cross-functional politics, or handle crisis response. What they can do: high-volume personalised outreach, continuous dashboard updates, and ops work that does not require judgment calls. Lemkin's admission: "The sliver of the VP role 10K does will get bigger every month." That trajectory matters more than today's capabilities. ## The constraint is not budget anymore Building these agents 11 months ago meant burning money on throwaway code and mistake loops. That friction is mostly gone. Lemkin built an applicant tracking system at midnight in 10 minutes for $2. The real cost stack: LLM calls ($257/month), Salesforce and connected apps (~$22k/year), hosting (included in Replit), and authentication tooling ($30/month). Most of the spend is in existing sales tech, not the agents themselves. This changes the build-versus-hire calculation for ops and SDR work. If you are evaluating whether to hire a junior SDR or deploy an agent for high-volume outreach, the budget is no longer the blocker. The questions now: quality control, deliverability, and whether the output is good enough to represent your brand. Worth noting: these are not vendor products. This is assembled tooling running on Replit with OpenAI calls. The market for packaged "AI SDR" tools is still pricing at enterprise levels, but the underlying economics suggest that will not hold.

SaaStr
24 days ago
News

Why your CSM cannot become an FDE, and what to hire instead

## The role swap does not work Forward deployed engineer job postings increased 12x in one year, according to ICONIQ's 2025 GTM survey of 205 B2B SaaS executives. That is not a hiring trend. That is a structural shift in how AI companies deploy product. The problem: most companies are looking at their customer success teams wondering if they can bridge the gap. They usually cannot. A CSM manages relationships across 8 to 12 accounts, mitigates renewal risk, drives expansion. An FDE embeds with 1 to 3 customers, writes workflows, debugs integrations, clears deployment blockers daily. Those are different skill sets. They are barely the same profession. ## The economics are unforgiving FDE work is expensive and slow. A single customer deployment can take 30 to 60+ days of embedded time. Most CSMs cannot do that inside their existing book of business without dropping accounts. The ACV math: - **Over $50k ACV:** FDEs are profitable and necessary - **$10k to $50k ACV:** Hybrid models with automation can work - **Under $10k ACV:** You must systematise implementation or the economics never close High-growth AI companies are already running a different post-sales org. Traditional B2B: 60% CSMs, 20% support engineers. AI-native: 25% CSMs, 40% FDEs and implementation specialists, 15% ML specialists. One Series B VP put it plainly: "We spend 3x as much in the first 90 days as traditional SaaS. But our churn is half, our expansion rate is double, and customers require 40% less ongoing support after month 3." ## Who can make the switch There are CSMs who can become FDEs. They have engineering backgrounds or deep technical domain expertise. They have spent time in the product, not just around it. But they are rare. Maybe 5%. Even then, you are usually better off hiring purpose-built FDEs than trying to retrain relationship managers into builders. ## What actually works Hire one strong FDE. Embed them with your top 3 to 5 customers. Document exactly what they do. Build the playbook. Then hire three more and systematise the deployment process around what actually works in production. The companies that crack this will win the AI enterprise market. Most have not figured it out yet. ## ANZ context This is highly relevant for ANZ enterprise SaaS, fintech, and AI vendors selling into regulated environments. These markets typically have smaller headcounts and leaner post-sale teams, which makes the temptation to "upgrade" CSMs into FDEs real. The article's underlying message: you will need to hire purpose-built technical customer-facing talent instead of repurposing relationship managers. Worth noting: FDE salaries in ANZ typically sit higher than CSM comp. Base ranges from $120k to $180k depending on market and technical depth, with OTE structures less common than in pure sales roles. The role is closer to solutions engineering or implementation consulting than traditional customer success.

SaaStr
26 days ago
News

Labor needs Greens votes for CGT reform, Greens want tougher tax

Labor's budget includes capital gains tax changes that startup founders are pushing back on. To pass them, Treasurer Jim Chalmers needs the Greens. The Greens hold the Senate balance of power. Early-stage talks have started, per the AFR. Timeline is tight: Labor wants this through by July 2. The Greens want more aggressive tax reform than what Labor proposed. Their platform includes a 1% annual wealth tax on assets above $10 million (2% above $1 billion), aligning capital gains tax with income tax rates, and higher taxes on investment income. Greens economic spokesperson Nick McKim called the budget "defined by caution, by timidity and by protection of corporate profits." For sales professionals, this matters if your comp includes equity or if you work for companies structured around capital efficiency. Labor's CGT changes already shift the calculus on startup equity packages. If the Greens push Labor further left on capital taxation, that changes the math again. The Greens are a minor party but punch above their weight in the Senate. They have used this leverage before on budget measures. How far Labor moves to secure their votes will signal how serious the government is about tax reform versus political survival. Coalition is against the CGT changes. Greens want tougher changes. Labor is in the middle. Watch the compromise: it will tell you what equity comp and capital structures look like for the next funding cycle. No final deal yet. Negotiations continue. If you are modeling OTE that includes equity, factor in policy risk until this clears the Senate.

SmartCompany
26 days ago
News

AI agents now doing 80% of SDR work: what that means for quota-carrying reps

## The New Hiring Test For years, the standard management test was: given what you know now, would you hire this person again? In 2026, that question is incomplete. The real test is now: would you replace them with an agent? That is a different calculation. If an agent costs $200/month and can do 60-80% of most knowledge work, the comparison is no longer human versus human. It is human versus agent, or human plus agent versus agent alone. ## What This Looks Like in Production SaaStr runs on 3 humans and 20+ agents. Revenue moved from -19% to +47% YoY after the shift. What stayed human: strategy, judgment calls, relationships requiring trust, and work where the human voice matters more than the task. What got replaced or augmented: SDR work (Artisan, Qualified, Monaco), win-back campaigns (Salesforce Agentforce), customer success workflows, content production, sponsor coordination. For SDR work specifically, agents are now handling 80-90% of the job in production. Not demos. Not pilots. Production, at scale, with minimal oversight. ## The Three Questions Underneath When you run the replacement test, you are asking: **1. What is the job?** Most job descriptions list tasks, not outcomes. An SDR's job is not 'send 100 emails a day.' It is 'generate qualified pipeline.' Once you articulate the outcome, you can ask what mix of humans and agents gets you there most efficiently. **2. What can an agent actually do?** For SDR work, 80-90% today. For VP of Marketing, maybe 40% but climbing. For CFO, maybe 30%. For CEO, close to zero. The skill is being precise about capability in production, not in demos. **3. What is the remaining human work worth?** If an agent can do 70% of a role, is the remaining 30% worth a full-time human? Sometimes that 30% is the judgment that matters most. Sometimes it is 'being the face of the function' and could be consolidated under a more senior person running multiple functions with agent support. ## What Matters in 18 Months In 18 months, everyone will know how to build a good agent. Prompt engineering was a hot job title for 12 months, then became irrelevant. Agent building is on the same trajectory. The skill that matters is not building the agent. It is deciding which humans to replace with one. That is a management skill, not an engineering skill. ## How to Run the Test Every quarter, or at minimum every time you are about to hire: 1. Write down the outcome the role is supposed to produce, not the tasks 2. List what an agent could do today toward that outcome in production, not in demos 3. Estimate what is left for the human: both tasks and judgment calls 4. Ask whether that remainder is worth the fully-loaded cost of a human hire The managers who learn this fast will run leaner, faster companies. The ones who do not will be the ones getting replaced themselves. ## ANZ Context ANZ Banking Group is rolling out Salesforce Agentforce across its business banking teams, consolidating data from 20 separate platforms. The bank says the system will save relationship managers about one working month per year through real-time account summaries and workflow automation. That is not a pilot. That is production deployment across roughly 40,000 employees globally. The composition of the team is now a variable, not a constant. Every open req is a chance to ask: do we need a human here, or do we need an agent plus a supervisor?

SaaStr
26 days ago
News

Okta CRO: How specialisation flipped $812M loss to profit

## The Turnaround Nobody Saw Coming Okta posted an $812M operating loss in fiscal 2023. Three years later, under CRO Jon Addison, it closed FY26 with $766M in non-GAAP operating income and $252M in free cash flow in Q4 alone. Most turnarounds are cost stories. This one is a GTM rebuild. Addison, who took the permanent CRO role in November 2023, restructured the entire sales motion. The core problem: asking generalist reps to carry five products meant they sold the one they understood and left the rest in the deck. New modules never got real pipeline. ## Four Levers That Moved Revenue **1. Specialisation unlocks platform value** Addison split the field into separate motions: install base, new logos, Auth0/customer identity, and broader platform. Each motion builds its own muscle instead of asking one AE to be an expert at everything. The numbers moved. New products (Identity Governance, Privileged Access, AI agent security) made up roughly 30% of Q4 FY26 bookings. Deals with new products came in 40% higher ACV. Identity Governance alone now has 2,000+ customers, three years post-launch. **2. Partner-led growth requires cultural rebuild** Okta's top 100 deals last fiscal year: 95% were partner-led. That is not a channel programme. That is a complete rewiring of how deals get sourced, scoped, and closed. Addison's line: "We need seven partners to surround that customer who also trusts us." Enterprise identity touches every system. Solo selling does not work at scale. **3. Discovery is dead, validation is everything** "The first call is no longer discovery. It is validation," Addison said. Buyers have already done the research. They know your product. The AE's job is to confirm they understand the buyer's context and prove the solution works. This changes quota, ramp, and comp. If discovery is validation, you need reps who can run technical proof-of-concept conversations, not just relationship-building calls. **4. Match GTM to the disruption phase** Addison frames markets in five phases: crisis, adoption, consolidation, maturity, disruption. Okta is in the disruption phase. AI agents need identity. That means new wedges, new ICPs, and new sales plays. The GTM implication: you cannot sell AI-agent identity the same way you sold SSO in 2018. The motion has to change with the phase. ## What This Means for ANZ Sales Teams Okta operates in Australia and New Zealand through regional sales and channel teams. If the global playbook holds, ANZ enterprise AEs are likely working more partner-led deals and carrying narrower product scopes than they did two years ago. For sales leaders: specialisation works when you have enough product surface area to justify it. If you are a three-product company asking AEs to be generalists, that is fine. If you are a ten-product platform still running a generalist model, you are leaving revenue on the table. For AEs: the skill set is shifting. Validation-first selling rewards technical fluency and proof-of-concept execution. If your close rate is dropping because buyers already know your pitch, the problem is not discovery. It is that you are still running a discovery motion in a validation market. ## The Bigger Pattern Okta's turnaround is not just about identity or security. It is about what works when a platform company hits the profitability wall. You cannot cut your way to growth. You can specialise your way there. Addison's playbook: narrow the focus, deepen the expertise, rewire the comp model, and match the motion to the market phase. That is not a marketing strategy. That is a sales operations rebuild. Worth watching: how this model scales as Okta pushes from $3B to $5B ARR. If partner-led deals stay at 95% and new products keep landing at 30% of bookings, the GTM model holds. If those numbers slip, something in the specialisation structure is not working. For now, the data says it is working.

Sales Hacker
27 days ago
News

Anthropic rebuilt sales org in 4 months: 54% of enterprise logos now self-serve

## The Problem: Demand You Cannot Hire For When Claude Opus 4.6 shipped in December 2025, Anthropic's commercial team returned from break to find demand had gone vertical. They had not hired for it. They had not planned for it. Eleanor Dorfman, Head of Industries at Anthropic, put it plainly at SaaStr AI Annual 2026: even if they had been ready to 3x the sales team, you cannot absorb that many bodies fast enough without burning quality. So in January 2026, they rebuilt the entire sales org around AI. Four months later: **54% of new enterprise logos in 2026 came through self-serve.** Real enterprise logos. Real ACV. Real terms of service. Self-served. ## Four Constraints, One Bet Dorfman's team had four immovable constraints: 1. Demand already in the door that could not be slowed 2. Headcount they could not add fast enough without lowering the bar 3. An existing tech stack they would not rip out (three years of investment) 4. Supporting functions (legal, deal desk, RevOps) that had to scale alongside sales The bet: do not buy a new stack. Thread Claude through the existing stack (Clay, LeanData, Salesforce, Gong, Ironclad, Slack, Intercom Fin). Make Claude the connective tissue. ## Investment One: Kill the PLG vs SLG Orthodoxy For 15 years, B2B has operated on a religious split: product-led growth is for SMB, sales-led is for enterprise. Self-service gets you to a landing page. Enterprise gets you an AE. Dorfman threw that out in January. They launched an enterprise self-service MVP in January 2026. Production in February. The funnel works like this: - Every lead gets enriched and qualified by Clay plus Claude - Two parallel funnels open: self-serve or sales-assisted - In self-serve, Intercom Fin guides the buyer through the journey - The buyer lands on an enterprise plan with real ACV, terms, invoicing, provisioning, and training enrolment. Completely self-serve. - If qualified for sales, the lead goes to BDR, then AE **54% of new enterprise logos in 2026 came through self-serve.** If you are still treating self-service as the consolation prize for buyers who do not deserve a human, you are leaving most of your 2026 motion on the table. ## Investment Two: Claude as Connective Tissue, Not Seventh Tool Claude is not the seventh tool bolted on. Claude makes the six core tools (Gmail, Gong, Slack, Salesforce, Intercom, Ironclad) talk to each other. What a Tuesday looks like for an Anthropic AE: **Morning.** Every rep starts the day in Claude. A "morning brief" Skill pulls context from Gmail, Gong, Slack, Google Docs, calendar, Salesforce, Intercom, and Greenhouse, then prioritises the day. Three actions to take. These emails to respond to. These deals at risk. Dorfman has hers delivered to Slack at 7am ET. She says she does not know how she used to operate without it. **Before a call.** A "call prep" Skill replaces 30 minutes of research. The rep types `/call prep` and gets a tailored one-pager: who is on the call, what they care about, historical context, discovery questions, competitive landscape. **Proposal time.** Instead of opening nine tabs of deal desk guidance and scrubbing Gong transcripts, the AE prompts Claude. Claude knows the product, the roadmap, where Anthropic has won and why. Claude drafts the proposal, validates it against policy, and uploads it to Ironclad. **Forecasting.** Still a work in progress. Dorfman was direct: they still spend at least 10 minutes at the top of every forecast call discussing how they should be forecasting. The ground is moving too fast. But the actual forecasts are now largely run by Claude and inspected by managers. Forecast calls become discussion forums about where AEs need help, not data-scrubbing exercises. ## What This Means for ANZ Sales Teams Anthropic does not have a large disclosed ANZ headcount or major office footprint in the region. Its ANZ go-to-market is likely being driven through partners, cloud marketplaces, and direct enterprise selling rather than a visibly large local sales team. But the playbook matters here. For ANZ sales leaders watching hypergrowth SaaS companies scale in 2026, the lesson is not "hire faster." It is "what can you automate so your best AEs focus on the deals that actually need them?" The self-serve enterprise motion is not a compromise. It is not the consolation prize. It is how you scale when demand moves faster than headcount ever could. ## The Shift For 15 years, the B2B sales playbook said: enterprise deals need enterprise AEs. Self-serve is for SMB. Anthropic just proved that wrong at scale. 54% of enterprise logos. Self-serve. Real terms. Real ACV. Worth noting: Anthropic is not publishing exact sales headcount numbers, and the broader workforce is estimated in the low thousands as of 2025/26. This is not a story about hiring 100 AEs. This is a story about not needing to. If your sales org is still treating AI as a toy or a seventh tab, this is the wake-up call. The reps who figure out how to thread AI through their existing workflow will close faster, forecast better, and scale harder than the ones still doing it the old way. The quota did not change. The tools did.

SaaStr
27 days ago
News

GTM teams 20% leaner, reps generating 2x revenue: ICONIQ 2026 benchmark

## The Numbers ICONIQ Growth's 2026 GTM benchmark, based on 150+ B2B SaaS executives surveyed in January, shows a structural shift: companies with AI fully embedded in GTM are generating roughly 2x the net new revenue per FTE compared to medium and low adopters. The AI productivity gap now sits at $270k per GTM rep. Post-sales saw the biggest delta. One AI-native company in the data set put a single human alongside an AI CSM and covered the work of roughly 20 human CSMs. Another voice-powered AI SDR handles 90%+ of EMEA inbound before routing to humans. ## Org Structure Changed High-performing sales orgs now run 9.2 to 9.8 ICs per manager. Everyone else sits at 4.4 to 5 ICs per manager. That is roughly twice the span of control. Sales management and leadership is 12% of the sales org in high performers versus 17% in everyone else. Flatter orgs are a design choice, not a default outcome. AI tooling makes wider spans possible. Reps need less hand-holding when AI handles pipeline research, call summaries, and follow-up drafts. ## AI Adoption Hit Critical Mass Share of companies where more than 50% of the function uses AI daily: Marketing 65%, SDRs 71%, AEs 57%. RevOps jumped from 34% to 54% in a single year. AI experimentation is eating 10% of RevOps time. Top-of-funnel conversion rates are 10 points higher with AI. New lead to MQL: 38% for AI-heavy pipelines versus 27% for light AI. MQL to SQL: 37% versus 29%. The lift is concentrated at the top of the funnel, where it should be. ## Hunter-Farmer Model Returned 65% of high performers have Sales owning cross-sell versus 49% of other companies. 55% have Sales owning upsell versus 44%. High performers are deliberately giving AEs both the hunter and farmer remit. The cleanest expansion motion is the AE who closed the deal continuing to own it. AE comp tied to net new recurring revenue jumped from 25% to 33% year-over-year. AE comp tied to NDR jumped from 18% to 23%. The hunter-farmer model is showing up in the comp plan, not just the org chart. ## What It Means This is a sales operations story as much as an AI story. Buyers serving sales, marketing, and RevOps should expect more ROI-driven conversations and benchmarking against efficiency metrics like net new ARR per FTE, not just pipeline volume. If your team is using AI heavily but not seeing top-of-funnel conversion lift, your AI deployment is not working. The data says so.

SaaStr
27 days ago
News

Ordermentum raises $55M, Arkeus and Lume close rounds in $81M ANZ week

## The Numbers Three ANZ startups raised $81 million this week. Ordermentum took $55 million. Arkeus and Lume split the rest. All three are at different stages, which matters if you are watching the hiring market. ## Ordermentum: $55M, Established SaaS Sydney hospitality platform Ordermentum closed $55 million from Five V Capital. This is their third major round: they raised $20M in 2021, $50M in 2024, and now this. They connect 45,000 venues to food wholesalers across Australia and the UK. The platform handles ordering, payments, supplier catalogues, and integrates with accounting systems. Founder and CEO Jamie Woollard has been running this since 2012. **Sales relevance:** Ordermentum is past the founder-led stage. They have a scaled GTM motion, established customer base, and likely a full commercial team: SDRs, AEs, CSMs. When a company this size raises, watch for expansion hiring in 6-12 months. They already operate in two markets, so territory splits and remote roles are likely in play. ## Arkeus: Defence Tech, Series A Melbourne defence tech startup Arkeus closed a Series A. Amount not disclosed. They build autonomous sensing and AI for security and defence applications. Public data is thin, which is normal for early defence tech. These companies operate in regulated environments with government customers. **Sales relevance:** Arkeus is likely still founder-led on sales. Defence tech GTM is enterprise and government driven: long cycles, relationship-heavy, no high-velocity SDR model. If they are hiring, expect senior AEs with government or defence experience, not a volume play. ## Lume: Music Platform, Early Stage New Zealand digital music platform Lume raised funding ahead of launch. Backers include artist Lorde. Co-founders are Tim Harper, Justin Warren, Sacha Judd, and Duncan Greive. Lume is pre-scale. Not much public signal on revenue or GTM structure yet. **Sales relevance:** Early-stage consumer platform. Sales motion is likely partnerships and artist acquisition, not traditional SaaS sales. Hiring will be product, marketing, and maybe a head of partnerships. Not a place to expect AE roles in the next quarter. ## Market Context ANZ startup funding in 2024 has been lumpy. Large rounds still happen, but earlier-stage companies are raising smaller amounts or staying lean longer. Defence tech and SaaS infrastructure are attracting capital. Consumer platforms are harder unless there is celebrity backing or proven traction. For sales professionals: Ordermentum is the one to watch for near-term hiring. Arkeus might hire senior sellers with defence backgrounds. Lume is too early to move the hiring needle. ## What This Means When a scaled SaaS company raises $55M, expect hiring. Ordermentum has the customer base, the market, and now the capital to expand commercial teams. If you are an AE with hospitality SaaS or UK market experience, that is the signal. Defence tech raises look different. Arkeus might hire, but it will be selective and specialized. Consumer platforms like Lume are a wait-and-see unless you want to bet on pre-product-market-fit upside. ANZ sales hiring follows funding with a lag. Track the capital, then track the headcount announcements 4-8 weeks later. That is when comp details and territory splits get real.

SmartCompany
27 days ago
News

Diraq, PsiQuantum land US$138m government quantum deals

## Diraq, PsiQuantum land US$138m government quantum deals Sydney-founded quantum computing company Diraq signed a Letter of Intent for up to US$38 million in proposed US government funding through the CHIPS Research and Development Office. PsiQuantum, the larger player with US$7 billion valuation, signed for US$100 million. Both deals include proposed minority equity stakes for the US government. The funding comes from a US$2 billion Department of Commerce push into quantum computing and semiconductor manufacturing announced overnight. Diraq, a UNSW spinout founded in 2022, is developing silicon-based quantum processors using existing CMOS semiconductor manufacturing. The company hit US$120 million total funding after a US$15 million Series A-2 in February 2024, led by Quantonation. This latest LOI signals public-sector validation and an industrialization push. PsiQuantum is the more capitalized bet. Founded by Australian-linked founders, it raised a US$1 billion Series E in 2025 led by BlackRock, Temasek and Baillie Gifford. The Australian federal and Queensland governments committed A$940 million combined in 2024 to support a Brisbane buildout. The company is targeting utility-scale, fault-tolerant quantum computing using photonic technology, with sites in Brisbane and Chicago. ### What this means for sales professionals Both companies are in deep R&D and infrastructure-build mode, not classic enterprise software selling. Their customers are primarily governments, research institutions, semiconductor partners and strategic investors. The commercial motion is heavily partnership-led and public-sector driven, not quota-carrying AEs working enterprise deals. Neither company publicly discloses a broad sales organisation. Available material suggests very small commercial teams relative to contract scale. Diraq highlights technical leadership and government relations over sales hires. PsiQuantum appears to rely on executive-led dealmaking and strategic partnerships. These are capital-intensive, government-backed quantum hardware bets rather than revenue-generating SaaS vendors. ANZ relevance centres on Australia as a build location, funding source and talent base. For sales professionals watching the quantum space: the big money is flowing to infrastructure and manufacturing deals, not software licenses. The sales playbook here is public procurement and strategic partnerships, not traditional B2B enterprise motion.

SmartCompany
28 days ago
News

Google AI search cuts organic traffic: ANZ B2B startups lose low-cost acquisition channel

## Google AI search cuts organic traffic: ANZ B2B startups lose low-cost acquisition channel Google shipped its biggest Search redesign in 25 years at I/O, replacing the traditional results page with AI Overviews, conversational answers, and persistent "information agents" that monitor topics and send updates. The commercial risk: AI answers satisfy intent without a click, compressing organic acquisition for startups that used SEO as a low-cost channel. For ANZ B2B sales teams, this matters because top-of-funnel traffic is shifting. SaaS, martech, and sales tech startups historically used long-tail content, comparison pages, and how-to articles to capture demand. AI Overviews now handle those queries inline, meaning fewer visitors land on your site, fewer MQLs enter the pipeline, and acquisition costs go up. The new playbook: optimise for "AI visibility" instead of traditional rankings. That means structured data, brand mentions in trusted sources, and content designed for extraction rather than click-through. Digital PR and topical authority matter more than keyword density. If your go-to-market relied on organic search, budget for paid media to replace that channel. For sales leaders, the implication is direct: if marketing's organic pipeline drops 20% to 30%, you need to know where the replacement volume comes from. Google is turning Search into an AI concierge that answers questions without sending traffic. Startups that can afford brand-building and paid acquisition will scale. Smaller teams relying on SEO as their primary demand channel will feel the squeeze. The competitive dynamics shift too. Enterprise buyers researching "best CRM for mid-market" or "AI prospecting tools Australia" might get AI-generated answers citing 3 to 5 vendors, drawn from high-authority sources. If your company is not mentioned, you are invisible. Ranking seventh on page one used to mean something. In AI search, it means nothing. Bottom line: Google extended its dominance by making Search an interface, not a gateway. For ANZ startups, that compresses organic demand capture and forces higher spend on partnerships, brand, and paid channels to maintain pipeline velocity.

Startup Daily
28 days ago
News

HubSpot hits $3.45B ARR, stock drops 16% on flat growth

## The Numbers That Matter HubSpot reported Q1 2026 revenue of $881M, up 23%. Subscription revenue hit $862.3M, putting ARR run-rate at $3.45B. Customer count reached 299,458, up 16% year-over-year. Non-GAAP operating margin expanded to 17.8%. Operating cash flow came in at $198.8M. The stock dropped 16% after hours. ## Why the Market Sold The 23% headline growth is mostly FX tailwind. Constant currency growth was 18%, flat from Q4's 18.2%. Q2 guidance steps down to 16% CC growth. CFO Kathryn Bueker called it "a slow start to Q2" tied to sales retraining around new AI pricing. Three weeks ago, Twilio went from 4% to 20% growth in one quarter. Atlassian went 14% to 32%. The market in mid-2026 is paying for visible reacceleration. HubSpot showed the opposite: flat-to-decelerating underlying growth with FX doing the heavy lifting. ## AI Revenue: Still Mostly Story Everyone wanted proof that AI drives real B2B revenue. HubSpot is not there yet. Customer Agent has roughly 8,000 customers activated. Prospecting Agent hit 10,000, up 57% quarter-over-quarter. Total credits consumed grew 67% QoQ, but off a small undisclosed base. Outcome-based pricing launched April 14, giving three weeks of data on the earnings call. Bueker described AI seats and credits as "emerging" growth levers, not core ones. When pushed on net revenue retention, she pointed to seat expansion, not AI consumption. The AI pricing transition is actually hurting near-term execution, with deals slipping while reps learn the new model. ## What Actually Drives Growth The same mechanics that have worked for six quarters: 62% of new Pro+ customers landed multi-hub in 2025. 40% of the Pro+ base by ARR owns four or more hubs, up six points year-over-year. Deals over $10K MRR grew 41%. Platform consolidation and upmarket motion remain the compounding levers. AI is secondary. ## What This Means for ANZ HubSpot has meaningful ANZ presence through direct offices and partners, with strong SMB penetration. The playbook here matters: multi-hub expansion and seat growth are proven revenue drivers at scale, while AI monetization is still being figured out. For sales leaders evaluating platforms or comp models tied to consumption revenue, the timeline just got longer. The company bought back $211M in stock this quarter and remains well-capitalized. Leadership is stable under CEO Yamini Rangan. But if you are betting on AI-driven reacceleration in mid-2026, this print suggests that story has more chapters to write.

SaaStr
28 days ago
News

PepsiCo picks two Sydney startups for APAC accelerator, deployment track

PepsiCo selected two Sydney startups for its 2026 APAC Greenhouse Program: Adiona Tech (logistics optimisation) and X-Centric Sciences (digital soil analytics). The program runs seven months and culminates in a Singapore showcase in October. This is not a typical accelerator. PepsiCo shifted from pilot-only support to commercial integration. The company says the cohort will fast-track startup solutions into its supply chain. Non-equity, grant-based, but clearly designed as a route to procurement-scale deployment. That makes these startups more relevant to enterprise buyers than most accelerator cohorts. ## What They Do **Adiona Tech** has been working with PepsiCo since 2023. The company provides AI-powered fleet routing and logistics optimisation. Early deployments delivered a 19% reduction in fleet distance travelled. That is a strong proof point for sales conversations in transport-heavy industries. Adiona recently closed a $1.8 million CRC-P grant and signed a deal with Australia Post's StarTrack. Competitive set: route optimisation and fleet telematics vendors. **X-Centric Sciences** has been working with PepsiCo since 2024. The company provides digital soil analytics for regenerative agriculture: measuring soil health, optimising inputs, supply-chain traceability. Competitive set: agtech and precision agriculture platforms. No public revenue or funding figures, but inclusion in PepsiCo's program suggests enterprise pilot stage at minimum. ## Why It Matters Both are specialist B2B sustainability tech vendors. Both are Sydney-based and already embedded in PepsiCo APAC pilots, which gives them credibility for further enterprise sales across food, beverage, logistics, and agriculture supply chains in ANZ. The program itself signals where corporate procurement is heading: sustainability metrics are moving from nice-to-have to procurement requirements. That creates sales opportunities for vendors who can prove ROI on emissions reduction, fleet efficiency, and supply-chain optimisation. Last year's cohort included two other Australian startups: Endua and Calyx.eco. The 2026 cohort includes five Greenhouse alumni, suggesting PepsiCo is doubling down on proven solutions rather than early-stage bets.

Startup Daily
Load More