The Wire

Real-time updates from ANZ tech sales

2 months ago
News

AI agent booked 614 meetings from one event. Here is the actual workflow.

## The Numbers Qualified ran an AI agent at SaaStr AI Annual 2026. From that single event: - 2.2M website sessions handled - 442,000 individual chats - 614 qualified meetings booked - Average sponsor ASP around $85,000 No human SDR team could have handled that volume without burning out or missing leads. The alternative would have been 3 to 10 BDRs, probably churning every 3 to 6 months. Instead: one agent, connected to Salesforce, trained on the full context. ## Where the ROI Actually Lives The play is not A leads. Enterprise inbound closes itself. Your slowest AE will respond to a $1M opportunity in 60 seconds. The money is in B leads: real signal, real ICP fit, but not worth a human rep's time per-lead. SaaStr's outbound agent recovered $500,000 in sponsor revenue this year from B leads that would have sat in Salesforce otherwise. If you are running an AI startup with a "Contact Us" form in 2026, you are leaving pipeline on the table. Replace the form. Today. ## How Agents Actually Get Built None of SaaStr's 20+ agents started as agents. They started as boring tools: - 10K (AI VP of Marketing) started as a dashboard to stop copy-pasting numbers from Marketo into Notion. - QBee (AI VP of Customer Success) started as a project management tool. - Annie (event producer) started as a Squarespace replacement. Each became an agent through 600 to 1,000 commits over a few months. The pattern: pick something broken in your stack, rebuild it so you can vibe code it, then keep adding context and tools until it starts acting like an agent. ## The Headless CRM Move If you do one thing after reading this: spin up Replit or Lovable or v0. Connect it to Salesforce via API. Build a dashboard or workflow you cannot do natively. SaaStr's founder has not logged into Salesforce in two companies. He queries it in real time instead: ticket sales by hour, VC attendees by region, look-alike sponsor scoring. None of that works in native Salesforce. Whoever owns your CRM owns the maximum context for your agents. Use it. ## Time Investment, Not Fire-and-Forget The narrative that autonomous agents work on their own is dangerous. The number one lesson from running 20+ agents in production: the more time you spend with them, the better they get. Last week, SaaStr's marketing agent started writing better re-engagement emails than any human marketer they could hire. The answer is not magic architecture. It is hours of interaction and context building. Your best human rep gets better when you spend time with them each week. Agents are exactly the same. ## What This Means for ANZ Sales Teams The signal here is not that Qualified ran an event in the US. It is that AI agents are now being used to qualify demand at event scale. That affects: - SDR workflows (what gets routed to humans vs. agents) - Lead routing (A leads vs. B leads) - Event follow-up automation (442,000 chats is not a human-scalable number) If your team is still running "Contact Us" forms or manually qualifying event leads, you are competing against teams that are not. The ROI is sitting in your CRM right now, in the B leads your reps will not touch because the per-lead expected value does not justify their time. Wire up an agent. The math works.

SaaStr
2 months ago
News

Salesforce reaccelerates to 13% growth at $45B ARR, core apps grow 7%

Salesforce grew revenue 13% to $11.1B in Q1 FY27, reaccelerating subscription growth from 9% to 12% at $45B+ run rate. At this size, that is rare. Most enterprise SaaS companies this large are decelerating into the teens. The headline hides the mix. Salesforce split its revenue reporting this quarter into two buckets: core apps with Agentforce embedded (7% growth in constant currency) and data platform plus other products (23% growth). The 13% total is the blend, plus roughly 3 points from acquiring Informatica. **The growth came from three levers at once:** Agentforce crossed $1.2B ARR, up 205% year over year. That is the fastest-scaling product in Salesforce history. The company delivered 1.6B agentic work units in Q1, up 111% quarter over quarter. More than 50% of Agentforce bookings came from existing customers, meaning they are buying agents on top of seats, not replacing them. The data and platform layer (Data 360, headless platform) grew 23%, three times faster than core apps. Strip out Informatica and the combined Agentforce plus Data 360 ARR is $2.3B, still up more than 100%. Informatica added roughly $1.1B in cloud ARR from the acquisition. That is bought growth, not organic, but it counts. **What this means for sales teams:** The seat compression fear has not shown up yet. Core apps still grew 7%, and revenue attrition held at 8%. If AI agents were cannibalizing seats, you would see flat or shrinking core revenue and rising churn. Neither happened in Q1. But 7% core growth is not booming. The enterprise SaaS playbook at $40B+ scale is now layering consumption and outcome-based pricing on top of seats, not replacing the seat model outright. Salesforce is running that playbook: agents, data infrastructure, and acquisitions all feeding the growth engine. For ANZ enterprise sales teams selling into the same accounts, this matters. Salesforce has meaningful regional presence across financial services, telecom, government, and retail. When they expand wallet share with agents and data products, that is budget you are competing for. The broader takeaway: reaccelerating at this scale took the entire kitchen sink. AI product line, acquisition, margin expansion, and a full revenue reporting overhaul. One lever does not move the number when you are this big.

SaaStr
2 months ago
News

AI-generated PR pitches killing startup media coverage, says Jason Lemkin

## The Problem Jason Lemkin, founder of SaaStr, says AI-generated PR pitches have become so common he now blocks domains daily. Before AI, he did not block anyone. The volume increased sharply over 12 months. PR firms and in-house comms teams adopted AI tools for media outreach. Muck Rack data shows generative AI usage in PR workflows jumped from 23% to 64% in a year. That scale created a new problem: pitches are well-written but generic. Good enough to open, not good enough to respond to. ## What Changed Lemkin used to reply to mediocre human pitches with feedback: here is what we actually want for SaaStr speakers or podcast guests. That feedback loop helped PR reps learn. Sometimes they came back months later with something great. He stopped doing that. Two reasons: giving feedback to an AI is pointless, and the same firm sends the same templated pitch the following week with a different founder name swapped in. Gergely Orosz, who also receives high volumes of PR outreach, says he reads then blocks the entire domain. Some senders now use throwaway domains to get around blocks. ## Why This Matters for Startups If you are using AI tools to scale PR outreach, you are likely damaging credibility with the journalists you need. Volume does not equal coverage. Reporters already receive huge volumes of pitches. AI made it easier to send more, which made it easier for them to ignore all of it. Effective PR still depends on relevance, specificity, and trusted relationships. Industry guidance from Cision and others says use AI for research, timing, and analytics. Keep final judgment, tone, and fact-checking human-led. The startups getting coverage are not the ones blasting templated pitches. They are the ones doing the work to understand what each journalist actually covers and why their story matters to that beat. ## The Parallel to Sales This mirrors what happened with SDR outreach. AI tools made it easier to send 1,000 emails. Response rates collapsed because everyone else also sent 1,000 emails. The reps who still get meetings are the ones doing account research, writing specific openers, and earning replies. Same principle applies here. AI can help with the scaffolding. It cannot replace the work of making your pitch actually relevant.

SaaStr
2 months ago
News

Australia back in global top 10 startup ecosystems, Melbourne growth outpaces Sydney

Australia is back in the global top 10 startup ecosystems for the first time since 2023, climbing three spots to ninth place in the 2026 StartupBlink report. The local ecosystem grew 22.9% in 2025, more than double the 10.3% global average. Australia also ranked fifth globally for return on investment and sixth for attracting talent and capital. ## What this means for sales teams Ecosystem rankings track venture funding, exits, and infrastructure. When Australia climbs, it signals more capital flowing to local startups, which historically translates to hiring. Q1 2025 saw A$1.3 billion raised across 100 deals, maintaining momentum after the 2022-2024 slowdown. Sydney remains the commercial anchor with 3,000+ tech startups and ranks 30th globally among cities. Melbourne is growing faster (37.8% versus Sydney's 11.7%) but sits at 34th. For AEs and sales managers, this means Sydney still has the deepest enterprise patch, but Melbourne's growth could shift where the best opportunities land in 2026-2027. Australia produces 1.22 unicorns per US$1 billion of VC investment, the highest rate globally according to ecosystem reports. That capital efficiency matters because it suggests local startups can scale on smaller rounds, which impacts how quickly they build out sales teams. ## The hiring context Ecosystem strength concentrates in enterprise SaaS, fintech, deep tech, and climate startups. Major players include Canva, Airwallex, and Morse Micro. When these companies scale, they pull sales talent from across ANZ and increasingly hire remote. The practical signal: Australia's ecosystem recovery is real, backed by funding data and growth metrics. If you are tracking ANZ sales opportunities, watch Melbourne's momentum. Sydney remains the largest market, but the gap is narrowing. Worth noting: Australia had negative momentum and fell out of the top 10 before this rebound. This is a recovery story, not a structural leap. The concentration in two cities also means regional sales opportunities remain limited compared to other top 10 ecosystems.

SmartCompany
2 months ago
News

Gartner: AI software spend hits $453B in 2026, up 60%

## The Numbers Global AI software spending will hit **$453 billion in 2026**, up 60% year on year, according to Gartner's updated worldwide AI spending forecast released last week. The research firm projects another 41% growth in 2027, taking the category to $638 billion. That is the largest single-year jump in B2B software spending on record. By the end of 2027, AI software alone will be bigger than every existing B2B software category combined was just a few years ago. Total AI-related spending across all categories is forecast to reach $2.59 trillion in 2026, up 47% year over year, with software driving the bulk of growth. ## What This Means for Sales Teams If your software company is growing at 30% while the AI software category grows at 60%, you are losing budget share. The new benchmark is category growth rate, and anything below that means CIOs are spending more on AI but a larger share is going to competitors. The math is harsher in faster segments. AI cybersecurity is growing 98% in 2026. AI models: 110%. AI data: 278%. A vendor growing at 50% in a segment expanding at 98% is getting outflanked. For sales teams, this creates two realities. First, if you are selling AI-adjacent products, this is the largest tailwind in B2B software history. Second, if you are not, you are fighting for a shrinking slice. Overall IT budgets are not growing 60%, which means non-AI software spend is getting rationalised to fund AI purchases. ## ROI Is the New Battleground The vendors that win will be those that help CIOs prove ROI to their boards. This is a customer success problem disguised as a product problem. Deployment playbooks, time-to-value metrics, and post-sale support will determine who captures this spend. For ANZ sales professionals, Gartner's forecast signals enterprise budget expansion in AI software, sales enablement tools, and automation platforms. If you are carrying quota in these segments, the tailwind is real. If you are not, the pressure to shift focus or product positioning is about to increase. Worth noting: Gartner, the 45-year-old Stamford-based research firm, remains one of the most influential sources for CIO budgeting and vendor planning decisions. When Gartner forecasts category growth at this scale, enterprise procurement teams take notice.

SaaStr
2 months ago
News

Chalmers consulting on CGT hit to zero-cost startups, founders

## Chalmers consulting on CGT hit to zero-cost startups, founders Treasurer Jim Chalmers says the government is consulting on how its capital gains tax overhaul will affect businesses with "low or zero cost base", narrowing the focus of potential carveouts for startups. The Budget replaces the 50% CGT discount with an inflation-based discount and a minimum 30% tax on gains from 1 July 2027. The changes apply only to gains arising after that date. For startups and small businesses that launch with almost nothing, this is where the pain sits. The reform taxes real gains above inflation, so a founder who bootstraps from zero and later sells their business creates only taxable gains. No cost base means no offset, which could mean larger tax bills on exit. Chalmers introduced the legislation on Thursday. Labor wants it passed before Parliament breaks on 2 July. The government argues the change makes the tax system fairer by aligning how capital gains and wages are taxed. The startup sector argues it discourages risk-taking and makes Australia less competitive for early-stage investment. The Budget does include measures aimed at early-stage businesses: loss refundability for eligible companies from 2026–27, and from 2028–29 a refund mechanism for small startups in their first two years, subject to caps linked to fringe benefits tax and withholding tax paid on wages. Treasury says this is meant to support new startups and improve cash flow. The $20,000 instant asset write-off is now permanent for businesses with turnover up to $10 million. Chalmers told media the reforms would let businesses make decisions based on economics rather than tax outcomes. Consultations with the startup sector are continuing. Worth noting: the policy debate is not just about CGT mechanics. It is about whether the changes alter incentives for founders, investors, and small-business formation in a market that already lags the US on risk capital and exit multiples. The clock is running. Parliament breaks in five weeks.

SmartCompany
2 months ago
News

Three Aussie startups raise $15.5 million: Oli, AlleSense, Cable close rounds

Three Australian startups raised $15.5 million in new funding this week, with medtech and energy companies leading the activity. ## Oli: $6.5 million Series A3 Sydney medtech Oli closed a $6.5 million Series A3 for its maternal and fetal monitoring technology. Scale Investors, Clare Ventures, and the University of Sydney backed the round. Total private capital now sits at $13 million across three Series A rounds: $4.7 million in 2022, $1.8 million in 2024, and this week's $6.5 million. The company has also secured over $9.5 million in non-dilutive grants. No sales team expansion announced yet. The capital is earmarked for product development, not go-to-market build-out. ## AlleSense and Cable: $9 million combined Medtech AlleSense and energy startup Cable closed the other two rounds, combining for roughly $9 million. Specific round sizes and investor details were not disclosed. ## What it means for sales These raises fit the current ANZ funding pattern: deep tech, medtech, and climate startups are securing capital while traditional SaaS activity stays quiet. Series A3 is an unusual structure. Most companies either raise a larger A or move to Series B. Multiple A extensions can signal either strong investor support or difficulty closing a full B round. For sales professionals evaluating Oli, check whether the repeated A rounds reflect intentional capital efficiency or fundraising challenges. Watch for hiring announcements in the next 60 to 90 days. Series A capital typically triggers AE and SDR hiring once product milestones clear. If you are tracking ANZ medtech opportunities, Oli's total capital and grant funding suggest they are building for scale, but timing matters. No comp details available. Standard Sydney medtech AE roles currently sit around $110k to $130k base, $170k to $200k OTE, depending on stage and segment.

SmartCompany
2 months ago
News

Dropbox hit $1B ARR faster than any B2B company, then stopped growing

## The Numbers Tell the Story Dropbox grew to $1B in revenue faster than any B2B company before it. Revenue went from $603.8M in 2015 to $1.107B in 2017, growing 40% then 31%. The company generated positive free cash flow of $137M in 2016 and $305M in 2017. Then the deceleration: 2018-2019 grew 26% then 19%. By 2022-2023, growth slowed to 8% both years. Fiscal 2025 revenue came in at $2.521B, down 1.1% year over year. Drew Houston is moving to Executive Chairman after 19 years as CEO. Ashraf Alkarmi, who joined as GM of Core in November 2024 from Vimeo, takes over as co-CEO and will eventually become sole CEO. ## What Happened After $1B The core wedge commoditised. Google Drive, OneDrive, iCloud, Box all came for file sync. Cloud storage went from a paid product to a free feature inside Workspace and Microsoft 365. Drew tried multiple second acts: HelloSign for e-signature, DocSend for sales document tracking, FormSwift for forms. Each added revenue. None re-accelerated the company. The one that hurts: enterprise AI search. Dropbox had the unfair advantage. They had the files, hundreds of millions of users, the document graph everyone else was trying to reach. By November 2023, Glean had hit $100M in ARR, growing 203% year over year, with plans starting at roughly $30K per year and scaling to over $5M for Fortune 500 customers. Dropbox launched Dash. It is a fine product. It is not the agentic Glean-killer that should have been the natural Dropbox 2.0. ## What This Means for Sales Teams If you are selling into enterprise accounts, this is the pattern to watch: incumbency in the AI era is worth far less than people thought. Data moats do not automatically convert to AI moats. The AI-native startup with no users beats the legacy player with 700M users more often than not. For sales professionals at SaaS companies approaching $1B ARR: the deceleration is real. The core wedge commoditises. The second act is harder than it looks. Drew did the things almost no founder does: built a $1B+ recurring revenue business, ran it profitably, took it public, stayed CEO for 19 years, returned real capital to shareholders, never blew up the company. The no-second-act critique is real. It is also a luxury problem. Most companies never get a first act. Q1 2026 came in at $629.5M with management raising full-year revenue and operating margin guidance. Ashraf inherits a massive, profitable, slightly declining core with 18 million paying users and an AI mandate from the board.

SaaStr
2 months ago
News

Bad hires cost ANZ SMEs $7.3 billion annually, Seek data shows

## Bad hires cost ANZ SMEs $7.3 billion annually, Seek data shows Seek released research today estimating Australian small and medium businesses collectively lose $7.3 billion per year on hires that do not work out. The average cost per wrong hire: $16,000. The research, conducted by advisory firm Nature in February 2026, surveyed over 950 small businesses across Australia and New Zealand. It breaks down the cost into three buckets: turnover (55%), training and performance management (34%), and direct business impact (11%). ### What the numbers mean for sales teams Turnover costs include recruitment, advertising, interviews, and onboarding replacement staff. For sales organisations, this is the visible part: reposting the SDR role, running discovery calls with candidates, ramping a new hire while the territory goes dark. Training and performance management is the 34% that hurts quietly. An AE who is not hitting quota still requires coaching, pipeline reviews, and manager time. That is time not spent with reps who are performing. Direct business impact, the remaining 11%, includes lost productivity, workflow disruption, and customer service issues. For sales, this translates to: deals that slip, pipeline that stalls, accounts that churn because the rep was not a fit. ### The ramp reality Seek's data does not break out sales-specific costs, but the $16,000 figure is conservative for quota-carrying roles. A mid-market AE at 6-month ramp who churns at 90 days costs closer to $50,000 when you factor in: base salary during ramp, manager time, lost pipeline, and the opportunity cost of an empty territory. The research confirms what sales leaders already know: hiring wrong is expensive. The question is whether businesses are measuring it. ### Context Seek is a Melbourne-based recruitment marketplace, founded 1997, and the dominant online jobs platform in ANZ. The research reflects its employer audience: SMBs hiring across functions, not just sales. But the cost structure applies: every role that turns over fast costs more than the job ad. For sales teams, the takeaway is simple. Measure time-to-productivity, track early churn, and calculate what a bad hire actually costs your business. It is probably more than $16,000.

SmartCompany
2 months ago
News

Hyperscalers spending $12 on AI infrastructure for every $1 earned

## The Infrastructure Bet Nobody Expected Hyperscalers are spending $12 on AI infrastructure for every $1 they earn from AI. Annual capex sits at $575B. Meta, Google, and Oracle are levered 7:1 on a cash flow basis, burning all free cash and borrowing heavily to fund data centers. This is the fifth-largest infrastructure project in history. Bigger than everything except railroads and the two world wars. By 2030, data center spending could hit 5-7% of US GDP. ## What This Means for Software Sales The buying process just got more complex. "Software is moving toward a two-buyer reality," Tunguz says. Technical and business buyers both have a seat at the table again. For AEs selling AI tools: you need dual fluency. The engineer cares about intelligence per watt. The CFO cares about whether this $575B bet pays off. Your pitch needs to land with both. Data teams are now reporting to heads of engineering. That org chart shift changes who controls budget and who signs deals. If you are still routing through the old data team structure, you are selling to the wrong people. ## The Sales Cycle Reality Foundation models broke the old product-market fit playbook. It is not binary anymore. It is continuous. Models grow 5-10x in size. Inference demand is infinite. Your customer's needs shift every quarter. Second-time founders are winning because they understand domain history and distribution. For sales teams: domain expertise is table stakes now. You need to know the customer's infrastructure reality, not just pitch features. PR is a major distribution channel for AI companies in a way it never was for software. That changes how deals get sourced and how urgency gets created. ## The Numbers That Matter Anthropicreportedly has high gross margins. First wave competition is margin-driven, not just feature-driven. When you are qualifying deals, ask about their infrastructure spend ratio. Ask who owns the AI budget. Ask whether they are building or buying. The next frontier: images and video. That data is 1,000-10,000x larger than text. Infrastructure spend will grow accordingly. If you are selling AI tools, the market is expanding faster than anyone expected. Bottom line: the biggest infrastructure bet since World War II is happening right now. Sales teams need to understand the two-buyer reality and adjust qualification, pitch, and close strategy accordingly.

Sales Hacker
2 months 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
3 months 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
3 months 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
3 months 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
3 months 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
3 months 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
3 months 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
3 months 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
3 months 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
3 months 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
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