The Wire

Real-time updates from ANZ tech sales

about 17 hours ago
News

SaaStr deploys 1 of 25 AI vendor pitches: deployment beats demo

# SaaStr runs 30 AI agents. 25 vendors pitched them this week. One got deployed. The difference: that vendor deployed the agent in five minutes instead of booking a demo. Jason Lemkin's team at SaaStr operates with three humans and 30+ AI agents. Their capacity for new tool evaluations is zero until after their May event. When five leading AI agent vendors reached out this week (plus 20 more via LinkedIn), the answer was uniform: talk in June. Except one vendor replied: "Give us five minutes. We will deploy it for you right now." They made time for that one. It is live. The other four are on the June list, if SaaStr has not found another solution by then. ## Deployment is the sale The winning vendor understood what most AI sales teams miss: Forward Deployed Engineers matter before the contract, not after. Every AI agent SaaStr runs successfully had dedicated FDE time. Every one. Palantir invented this model in the early 2010s because government agencies could not get to production without an engineer in the room handling messy data and specific workflows. Most AI vendors today use FDEs post-sale. The ones winning use them pre-sale. Marc Benioff told Lemkin on 20VC that even at $40B ARR, his biggest wish is getting AI agents deployed before contracts sign. Not pricing. Not product. Deployment. Salesforce did exactly that with SaaStr. They assigned FDE resources to configure Agentforce before the deal closed. Results: 1,000 ghosted sponsorship leads from SaaStr Annual, zero prior follow-up, 72% open rate after Agentforce deployment, 10%+ response rate, deals closing from six-month-old dead contacts. Salesforce is now SaaStr's AI agent hub because they deployed first and let results make the argument. ## Why this matters for sales teams SaaStr is not skeptical of AI agents. They run 30, generate over $1M in revenue from them, and spend $500k yearly on AI tools versus $10k on Salesforce. The technology works. The constraint is capacity. Every new agent takes minimum 30 days to production: data integrations, routing logic, edge cases, ongoing management. When a vendor says "we would love to get you set up" and the next step is a kickoff call, the honest answer is: not right now. The mental load is too high. When a vendor says "we will handle it" and actually does, the calculus changes completely. The deployment gap disappears. Value shows up immediately. Nothing goes on the list because it is already running. ## What this means for AI vendors The FDE model scales better than it used to. That is the part traditional software vendors have not internalized. Deployment before signature is not a services business. It is what sales looks like for AI agents in 2026. Vendors likely pitching SaaStr include Relevance AI, Beam AI, Ruh AI, Salesforce Agentforce, Zapier AI Agents, and Microsoft Copilot Agents. Most target enterprise customers (finance, healthcare, retail) with global integrations. ANZ-specific presence is minimal across leading vendors. The deployment rate Lemkin describes (1 in 25 pitches) tracks with broader AI agent adoption challenges: implementation complexity, integration friction, and capacity constraints hit even teams already running dozens of agents successfully. Worth noting: SaaStr spends 50x more on AI tools than their CRM. That ratio tells you where budget is moving for sales ops teams evaluating 2026 stack decisions.

SaaStr
about 17 hours ago
News

Sophos scales CS for 600k customers, threat response under 4 hours

## How Sophos Built CS Ops for 600k Customers Teresa Anania (now CCO at Verint, formerly SVP Customer Experience at Sophos) built customer success into a revenue engine at scale. Sophos protects 600,000 organisations globally, runs over $1B in ARR, and operates 24/7 CS ops because cyber threats do not wait for business hours. The threat landscape shifted. AI accelerated attack speed and sophistication. Attackers now move in 3 to 4 hours, logging in rather than breaking in. Sophos structured CS to respond before customers know there is a problem. By the time a support ticket arrives, you have already failed your customer. ## The Attribution Model Anania ties CS touchpoints directly to retention and expansion. No vanity metrics. She tracks which CS activities drive renewals, upsells, and churn prevention. Dynamic segmentation assigns coverage based on risk, spend, and growth potential, not just ACV hard lines. For early-stage companies without perfect data: start at the end of the renewal cycle. Automate what you can measure. Crawl, walk, run. ## Structure and Scale Sophos uses a two-by-two matrix: customer risk versus revenue potential. High-touch CSMs for enterprise accounts showing growth signals. Digital-led motions for stable mid-market. The customer should never feel your org chart. Anania hires for "humble confidence", a specific combination of expertise without ego. Her 5-to-1 scorecard evaluates how CS earns trust over time. Inner and outer feedback loops turn NPS data into cross-functional action, not just a CS slide. ## ANZ Context Australia ranks among top countries for Sophos adoption. The company maintains ANZ presence with global 24/7 operations supporting the region. No specific ANZ headcount disclosed, but rapid MDR expansion (37% customer growth in 2024, 26,000+ MDR customers globally) suggests scaling in customer-facing ops. Sophos holds #1 rankings in G2's 2026 reports for Endpoint Protection, XDR, MDR, and Firewall across enterprise, mid-market, and SMB segments. Privately held following management buyout. Competing in a cybersecurity market projected to hit $267.7B by 2026. ## What This Means Retention is an all-company play. CS attribution models tie activity to revenue. Dynamic segmentation beats rigid ACV lines. If you are building CS at scale: measure what moves the number, automate the repeatable, and structure coverage around customer outcomes, not your reporting lines.

Sales Hacker
about 17 hours ago
News

AI SDR deployment takes 60 days of training, not 3 days of setup

AI SDR deployment takes 60 days of real work, not the 3 days vendors quote you. The tech is live fast. The training that makes it perform like your best rep takes 60 days of focused effort. Most companies skip the training. That is why most AI SDR deployments fail. ## Week 1-2: Foundation work (2-3 hours daily) Pull 50+ real conversations from your best BDR. Not scripts. Actual conversations, exact tone, real objection handling. Feed the AI your product knowledge: customer data, past conversations, why anyone should care. Read every message the AI sends. Every one. Flag anything robotic or off-brand immediately. Most teams stop reading after day three. That is where it goes wrong. ## Week 3-4: Optimisation (1-2 hours daily) One variable at a time. Subject lines, CTAs, send timing, opening lines. Not all at once. The bar: is this response better than what your best rep would say? Not better than a mediocre rep. Better than your best one. Track which approaches get replies. The data will tell you things your instincts will not. ## Month 2+: Maintenance (30-60 minutes daily) By now the AI is performing. Your job shifts to catching edge cases, refreshing the knowledge base as your product changes, tightening guardrails based on real conversations. This is not set-it-and-forget-it. It is lighter-touch, but still real attention. ## Why most deployments fail 90% of companies skip the training work. They deploy, wait two weeks, see mediocre results, conclude AI SDRs do not work. They are wrong about the conclusion. They are right that it did not work. It did not work because they did not train it. Best-performing deployments share one thing: the team invested heavily in the first 60 days alongside the vendor. The vendors who actually help show up for 80% of that heavy lifting. They do not just hand you a login and a tutorial video. ## The actual timeline - Days 1-7: Technical deployment, data ingestion, initial config. Live quickly. - Days 8-30: Foundation training. Daily, intensive, non-negotiable. - Days 31-60: Optimisation. A/B testing, voice refinement, performance analysis. - Day 61+: Ongoing maintenance. Lighter lift, but still requires attention. Total time to a well-trained, high-performing AI SDR: 60 days if you do the work. Six months of frustration and a vendor switch if you don't. ## ANZ context This timeline matters more in ANZ markets where AI SDR adoption is tracking 6-12 months behind US deployments. Local teams asking about AI SDR ROI need to factor in the real 60-day ramp, not the 3-day vendor pitch. That changes the cost comparison versus hiring another human SDR on $80k base. The tools are not magic. The training is the product. *Source: SaaStr, Jason Lemkin*

SaaStr
about 17 hours ago
News

Rumin8 raises $4.3m, expands to NZ: agtech hiring watch

## Rumin8 raises $4.3m, expands to NZ: agtech hiring watch Perth-based Rumin8 closed US$3 million ($4.3m AUD) from New Zealand investor AgriZeroNZ to expand its livestock methane reduction business across the Tasman. The startup develops feed additives that cut cattle emissions while claiming to boost production and farm profitability. Founded in 2021, Rumin8 started with seaweed-based solutions but pivoted to what it calls "nature-inspired pharmaceutical ingredients." The company aims to decarbonise 100 million cattle by 2030. Big goal, now entering final commercial trials. ### The funding context This follows a $17m seed round in 2023 that brought in Bill Gates via Breakthrough Energy Ventures and Twiggy Forrest through Harvest Road Group. Other backers include Aware Super Sentient WA Growth Fund and Prelude Ventures. Total funding not disclosed, but the company is clearly raising to scale. ### What this means for sales No sales team hiring announced yet, but worth tracking. NZ expansion usually means local market entry: think regional AEs, partnerships, potentially field sales given the agtech vertical. Dairy is New Zealand's largest export, so the addressable market justifies boots on the ground. Agtech sales cycles run long (12-18 months is common for farm inputs), and closing farmers requires product validation and local relationships. If Rumin8 follows the playbook, expect NZ-based commercial roles once trials wrap. ### Agtech hiring patterns Recently funded agtech startups typically hire sales 6-12 months post-raise, after product-market fit validation. Comp in agtech lags pure SaaS (enterprise AE OTE in agtech sits around $140k-160k vs $180k+ in tech), but territory sizes can be massive in ANZ given farm distribution. Competitors in the livestock emissions space include ASX-listed Sea Forest and CSIRO spinout FutureFeed. Rumin8's pharma-ingredient angle differentiates, but it is still selling into conservative farming budgets. CEO David Messina mentioned aligning with commercial partners in target markets. Translation: channel strategy likely, which could mean partner account management roles rather than direct field sales initially. No public data on current headcount or sales org structure. Watch for NZ commercial lead appointments in Q2-Q3 2026 if trials progress.

Startup Daily
about 17 hours ago
News

ACS cuts executives two weeks into new CEO transition

## ACS cuts executives two weeks into new CEO transition Dr Prins Ralston wasted no time. Two weeks into his role as CEO of the Australian Computer Society, he cut multiple executive positions. "A number of executive roles are being made redundant," Ralston told staff in a Tuesday email. "These are realignment decisions, driven by the need for a leaner and more appropriately focused organisation, not a reflection of the individuals involved." The ACS management committee approved the executive restructure on Monday. An all-staff meeting followed Wednesday. Ralston is the fourth ACS CEO in six years. He replaced Josh Griggs, who left suddenly after 18 months in March 2026. Griggs ran his own leadership purge during his tenure, shutting Melbourne's Bay City Labs and Brisbane's River City Labs in favour of a virtual offering. ### What the restructure looks like Operations director Betsy Gregg now reports directly to Ralston, overseeing Strategic Initiative Executives and their boards. Member Products and Services is being established as a new function under Enzo Cocotti, reporting to the CEO. Shared Services, led by CFO Wynand de Wet, now includes Sydney's Harbour City Labs, though ACS did not confirm whether that facility will remain open. ### More cuts coming "I want to be honest with you: this is the beginning of a transition, not the end of it," Ralston told staff. "There will be further decisions ahead as we shape ACS for the future as external factors such as the 26/27 Federal budget is announced." Ralston outlined priorities: member focus, operational efficiency, and growth in AI and cyber security. ACS recently received a $1.9 million federal government grant to co-design a voluntary national Cyber Security Professionalisation Scheme. ### What this means New CEOs often restructure in the first 90 days. What is notable here is the speed and the acknowledgement that more cuts are coming. Ralston signalled budget pressures and a need to streamline before growing. For sales professionals considering tech association roles or membership org sales positions, this is a reminder: non-profit does not mean stable. CEO transitions often mean executive churn, territory changes, and quota resets. ACS did not respond to questions about total headcount impact or specifics on which executive roles were cut.

Startup Daily
1 day ago
News

Halter hits $2.9B valuation, $314M Series E: What it means for agtech sales

## The Numbers Halter raised $314.4 million Series E led by Founders Fund, valuing the NZ agtech at $2.9 billion. That is 3x their Series D valuation from June 2025, when they hit $1 billion on a $100 million raise. The company now has 1 million solar-powered GPS collars deployed across 2,000+ cattle farms in New Zealand, Australia, and the US. ## What This Means for Sales Teams Series E at this scale typically signals aggressive go-to-market expansion. Halter already employs 300+ people and operates on a subscription model: monthly fees per cow per collar. They expanded into the US in 2024 and are targeting UK, Ireland, and South America next. For context: Halter reported $17.5 million revenue with 600,000+ collars across 1,000+ customers as of 2024. The math suggests they are scaling fast, which means territory expansion and quota changes for existing reps. ## The Funding Stack Founders Fund led, with participation from Blackbird Ventures (Australia), DCVC, Bond, Bessemer, and others. Rocket Lab founder Peter Beck is an investor and board member. Andrew Fraser serves as President. ## Market Context Halter won NZ's Deloitte Fast 50 as the country's fastest-growing company in 2024. The company was founded in 2016 by Craig Piggott, who left Rocket Lab to build tech he saw his family's Waikato dairy farm needed. The product: virtual fencing via collar that uses audio cues and vibrations to herd cattle, controlled via smartphone app. US farmers have built nearly 100,000 kilometres of virtual fencing since Halter's 2024 launch there. That adoption rate matters if you are tracking agtech sales cycles and enterprise deployment timelines. ## What We Are Watching Geographic expansion plans, particularly UK and Ireland rollout timing. Sales team buildout in new territories. Comp structures for AEs selling into agriculture, which historically has different sales cycles than SaaS. Whether the subscription model scales as they move from early adopters to mainstream dairy operations. Worth noting: agtech sales often require longer educational cycles and hands-on demonstrations. If they are hiring into new markets, expect field-heavy roles with territory ownership.

SmartCompany
1 day ago
News

Canva acquires Doohly for $30M, adds DOOH to platform

Canva acquired Melbourne-based Doohly for $30M, adding digital out-of-home (DOOH) advertising to its platform. The deal means Canva now handles everything from design creation to physical billboard placement. Doohly, founded in 2020 by Sean Law and Tom Sawkins, runs a cloud-based platform managing digital billboards and retail screens. The company operates across ANZ and UK, with clients including KX Pilates, Mobil, Rebel Sport, and Liquorland. Previous raise: $650K from Archangel Ventures and Skalata. ## What It Means for Enterprise Sales Canva is building an end-to-end marketing platform play. Design tools brought in SMBs. DOOH capabilities target enterprise clients with physical retail presence. Worth noting: this is acquisition number six in two years, following Affinity and Leonardo in 2024. For sales teams selling into retail or physical locations, Canva just became a more complete solution. Previously, you designed in Canva, then exported to a separate DOOH platform. Now it is one workflow. ## The Numbers Law owns nearly 50% of Doohly, Skalata around 17%, Sawkins 14%. At $30M exit, that is $15M+ for Law, $5M+ for Skalata, $4M+ for Sawkins. Not bad for a company that raised $650K. Doohly was serving 4 billion+ creatives across 100+ networks in 13 countries. Client count grew from 11 to 19 since mid-2023. Lean operation, tech-driven revenue model. ## ANZ Context Second Melbourne adtech exit in recent memory. Doohly had strong ANZ partnerships: LUMOS in Australia, HYPER in New Zealand (500+ retail locations). Canva gets immediate local market access without building infrastructure from scratch. No word yet on Doohly team integration or whether Law and Sawkins stay on. Standard acquisition playbook suggests product gets absorbed, founders stick around for 12-18 months, then move on. This matters if you are selling design tools, martech, or advertising platforms. Canva keeps adding capabilities. They are not staying in their lane.

Startup Daily
1 day ago
News

Cauldron closes $13.25M Series A2, no sales team disclosed

## The Numbers Cauldron, an Orange NSW biotech, closed a $13.25 million Series A2 led by Main Sequence Ventures. Total funding now sits at roughly $26 million across seed ($10.5M in 2023) and Series A ($9.5M in 2024). The company develops continuous precision fermentation tech that cuts costs 30-50% versus traditional batch methods. Applications span food, agriculture, biofuels, cosmetics, and chemicals. ## What We Don't Know No public data on: - Sales team size or structure - Recent hires or hiring plans - CRO, VP Sales, or senior go-to-market roles - Compensation ranges for any roles - Revenue numbers or ARR For a company citing "faster-than-expected demand" and planning multi-facility expansion, the absence of sales org details is notable. Either they are not hiring yet, or the information is not public. ## The Context Cauldron runs a 25,000-litre facility in Orange, acquired via seed funding from CEO Michele Stansfield's prior firm Agritechnology (which included 35 years of R&D). Plans include a 500,000-litre facility and a network of plants across regional Australia. The company holds Australia's first 10,000-litre gene tech licence for scale testing. Fast Company named them among Asia-Pacific's most innovative companies this week. ## What This Means for Sales Pros Biotech startups at this stage typically build commercial teams post-Series A, especially when citing customer demand. If Cauldron starts hiring AEs or business development roles, expect: - Technical sales requirements (bioprocessing knowledge) - Long sales cycles (industrial contracts) - Enterprise deal sizes - Regional NSW or Sydney-based roles Worth tracking if you are looking at early-stage deep tech sales. Just do not expect comp transparency yet. **Series B equity note:** At $26M raised, Cauldron sits between Series A and B. Early-stage biotech comp typically skews toward equity over cash, with OTE structures less common than tech SaaS roles until commercial traction is proven.

SmartCompany
1 day ago
News

Mr Yum CEO on merger reality: integration costs, nervous customers, profitability

When Mr Yum and me&u merged in November 2023, plenty of people quietly assumed it would fail. Kim Teo, now CEO of the combined entity, says the scepticism was not irrational. The first year looked ugly on paper. Integration costs were significant. The company carried a loss that doubters pointed to as proof. But Teo says the real work was not about the balance sheet: it was about keeping focus while everything changed. ## The merger reality Two rival hospitality tech firms, both based in ANZ (Mr Yum in Melbourne, me&u in Sydney), merged via all-stock deal. The combined entity now processes over $2 billion in annual dining transactions across 6,000+ food brands. It operates under the me&u brand with Teo as CEO. The first year priorities: customer migration, systems integration, team consolidation. Not glamorous. Expensive. Teo describes it as the "hard, unsexy work" that sets up the next phase. ## What they actually did No major changes during peak trading seasons. Focus on continuity of product, support, and platform. The goal: avoid disrupting customers while integrating two sales organisations that had competed fiercely for four years. Teo does not sugarcoat the challenge. Integration costs hit hard. Customers were nervous. The work was messy. But the alternative, she implies, was staying separate while burning resources on competition. ## Sales team implications The article does not detail sales team sizes, comp structures, or how many roles were consolidated. That is the transparency gap in most merger coverage: lots of talk about "culture" and "focus," not enough about what happened to the teams doing the selling. What we know: the merger aimed to build a "super product" and scale innovation. What we do not know: how many AEs, SDRs, or AMs lost roles, what the comp looked like post-merger, or how territories were redrawn. For sales professionals watching merger news, Teo's advice centers on focus and culture, not the operational details that determine whether your role survives integration. Worth noting for anyone evaluating a company mid-merger: ask about the roadmap, but also ask about quota relief, territory changes, and what "integration" actually means for your patch.

SmartCompany
1 day ago
News

Australia's AI edge: Data-rich industries, not frontier models

Australia's AI advantage sits in data-rich industries, not building the next ChatGPT competitor. That is the view from Lee Hickin, executive director of the National AI Centre, speaking at ARM Hub's Propel-AIR 2.0 robotics accelerator in Brisbane. "Where does Australia have data and insights and knowledge that is unique to us," Hickin told SmartCompany. The answer: mining, agriculture, healthcare, and other sectors where ANZ companies already own proprietary datasets that global players cannot easily replicate. While governments pour billions into sovereign AI capability and tech giants build data centres, Hickin argues the local edge is not in frontier model development. It is in sector-specific applications where Australia has decades of domain expertise and unique data sources. ## What this means for sales teams For sales professionals selling AI tools in Australia, this matters. The buyers are not chasing general-purpose models. They want tools that solve specific problems in industries where Australia actually leads. Salesforce pushed AI certifications hard in 2024. The Australian market response: cautious adoption in finance and retail, stronger uptake in resources and agriculture where the data story resonates. AI sales automation tools from Australian vendors are gaining traction because they understand local compliance and industry workflows. The comp play: Enterprise AEs selling industry-specific AI solutions in mining or agriculture are seeing stronger close rates than those pitching generic automation. Territory assignments are shifting to vertical specialisation. If you are carrying an AI quota in 2026, knowing the difference between frontier models and applied AI is table stakes. Australia's AI market is projected to exceed AUD 80 billion annually by 2033. The government committed AUD 2.5 billion through its National AI Plan. But the sales opportunity is not in competing with OpenAI. It is in tools that leverage Australia's unique industry data and expertise. Worth noting: 68% of Australian businesses have moved AI from pilot to production. That is higher than most markets. The buyers are ready, but they want solutions that fit local industries, not generic automation promises.

SmartCompany
3 days ago
News

Silicon Quantum Computing lands $20M NRF funding, no sales team details

## SQC adds $20M, still R&D-heavy Silicon Quantum Computing closed $20 million from the National Reconstruction Fund via SAFE note. The cash funds production scaling for quantum processing units and Watermelon, its quantum machine learning product. The investment is part of an ongoing round. No total raise amount disclosed. SQC has pulled in $280 million since 2017, including $83 million in seed from Australian government, UNSW, Telstra, and Commonwealth Bank. ## The revenue picture SQC reports "millions of AUD" in revenue from two products: Watermelon (quantum ML) and Quantum Twins (molecular simulation). They are targeting commercial-scale error-corrected quantum computers by 2033. Worth noting: that is a seven-year timeline in a market where timelines tend to slip. The company employs around 90 to 100 people. Breakdown: 70-plus technical staff, 20 commercial. No CRO. No VP Sales. No sales team size disclosed. For a B2B play targeting multinationals in defense, pharma, finance, telecoms, energy, and materials, that is a light commercial footprint. ## What this means for ANZ tech sales SQC operates as Australia's quantum computing champion: full-stack development from atomic manufacturing to software, fabricating chips at UNSW Sydney labs. CEO Michelle Simmons (2018 Australian of the Year) runs a research-first operation competing against IBM and Rigetti on silicon spin qubit technology. The sales angle: SQC sells via cloud and hardware deals to enterprise clients. But the org structure tilts heavily toward R&D. If you are tracking quantum computing sales roles in ANZ, this is not where the action is yet. The $20 million goes to production capacity, not go-to-market expansion. Funding rounds like this signal government backing and long-term potential. They do not signal near-term sales hiring. SQC's 2033 commercialisation target puts it in the "strategic partnership" phase, not the "build out an enterprise sales team" phase. ## The comp reality No sales roles posted. No comp data. If SQC does hire sales, expect it to look more like technical account management or strategic partnerships than traditional quota-carrying AE roles. Quantum computing sales at this stage means educating C-suite on seven-year roadmaps, not closing quarterly deals.

SmartCompany
3 days ago
News

Cuttable raises $5.7M, doubles valuation to $100M, opens New York office

**Cuttable closed a $5.7 million round at a $100 million valuation, doubling from its August 2025 raise.** The Melbourne AI ad tech startup is opening a New York office after US demand reached 50% of inbound enquiries. Square Peg and Rampersand increased their stakes. AirTree, Glitch Capital, and Benjamin Duncan joined. Total raised: $16 million across three rounds in 18 months. **CEO Sam Kroonenburg** sold his previous company, A Cloud Guru, for $2 billion in 2021. He cofounded Cuttable in 2023 with Jack White (Sunday Gravy) and Ed Ring (former Swisse marketer). The platform automates ad production, testing, and iteration for performance marketing teams. Client base: 200 brands across ANZ and US. Recent programme data: 13x return on ad spend. Notable clients include Catch (Wesfarmers), Nando's, and Powershop. **Why this matters for sales teams:** Cuttable is automating creative workflows, similar to how Clay and other AI sales tools automate prospecting. Performance marketing teams are the buyers here. If you are selling into marketing or ad tech, watch how fast AI is eliminating manual work in adjacent functions. Same pattern: AI automates grunt work, teams get smaller, buying decisions consolidate. The New York expansion follows demand, not ambition. When 50% of inbound comes from one market, you go there. Worth noting: Kroonenburg has done this before. A Cloud Guru hit similar inflection points before the $2B exit. **Funding timeline:** - July 2024: $5.5M seed (Square Peg) - August 2025: $4.5M seed extension, $44.5M valuation - March 2026: $5.7M, $100M valuation Valuation more than doubled in seven months. That pace suggests strong unit economics or aggressive growth targets. The company is hiring in Melbourne and staffing New York. Kroonenburg compared Cuttable's current stage to A Cloud Guru at similar traction: strong product, customers pulling into new markets, fast-moving team. If the pattern holds, this is early innings.

Startup Daily
3 days ago
News

IREN hits $17B: Aussie founders pivot Bitcoin miner to AI infra

## The Pivot IREN (formerly Iris Energy) started as a Bitcoin mining operation in 2018. Founders Daniel and Will Roberts, both ex-Macquarie Group, pitched renewable-powered data centres locally. The ASX rejected them. They listed on Nasdaq instead. The 2022 crypto crash crushed the stock 95%. Debtholders nearly took the company. But in 2023, the brothers pivoted hard: Bitcoin mining plus AI data centres. They bought 9,000 Nvidia Blackwell chips. Stock is up 300% this year. Market cap: $17 billion. That would make them the 37th largest company on the ASX, except they are not on the ASX. ## The Numbers Revenue up 168% year-on-year. Net profit: $86 million. The company raised $205 million in equity before the IPO. Recent executive adds include Anthony Lewis as CFO (focus: aggressive capital raising) and David Shaw as COO (focus: physical infrastructure). The co-founders each cashed out $33 million recently, selling one million shares as the stock hit record highs. They remain co-CEOs. ## The Australia Problem IREN has zero facilities in Australia. All operations moved to Texas. The brothers cited regulatory barriers and slow tech infrastructure adaptation. Sydney headquarters, Texas operations. This mirrors a broader pattern: Australian founders building infrastructure businesses offshore because local markets move too slowly on data centre approvals and energy policy. ## What It Means IREN competes in two markets: Bitcoin mining (where it is now the world's most valuable public miner) and AI data centres (where those Nvidia chips matter). The company positions as renewable-energy-powered high-performance computing. The AI thesis is driving valuations across the data centre space. IREN's 300% gain this year tracks similar moves in infrastructure plays. Whether that holds depends on AI compute demand staying strong, not just hype. For sales teams selling into this sector: the money is real, the budgets are large, and the buying cycle has compressed. Enterprise AEs covering infrastructure, energy, or hardware should be tracking these plays closely. This is where the procurement action is happening right now.

SmartCompany
3 days ago
News

AI AEs outperform humans on product knowledge, not trust

## The Trust Objection Does Not Hold The most common pushback to AI account executives: buyers only trust humans. The reality is different. Most B2B deals happen over Zoom with a stranger who knows the product maybe 20% as well as the product team, needs to pull in an SE for technical questions, and pivots away from hard ones. That stranger is not someone anyone trusts. Trust has not been established. It has to be earned, in both directions. ## Where AI AEs Actually Win Here is what the AI AE brings: - **Knows the product cold.** Every feature, integration, edge case, pricing scenario. No "I will check with the team." Buyers burned by reps who overpromise find AI precision more trustworthy. - **Answers every question directly.** No friction. No loop-ins. Friction kills deals. - **No quota pressure.** Human reps push. They create urgency. Sometimes they shade the truth because they need the number. AI AEs do not have those incentives. - **Does not make things up to close.** Not in general. ## Where Humans Still Win Humans build genuine rapport over time. They read rooms, navigate political complexity, sense when a champion is losing support. In high-ACV enterprise deals with long cycles and many stakeholders, great human AEs have an edge. But most B2B deals are not that. Most are mid-market or SMB, two to four people on the buying committee, 30 to 90 day cycle. For this volume, an AI AE that knows the product perfectly and answers every question accurately will outperform the average human rep. Not all the time. But more often than the trust objection suggests. ## The Real Question Is Familiarity Buyers saying they do not trust AI AEs are expressing unfamiliarity. That goes away fast. Every generation adapted: websites over door-to-door, e-commerce over catalogues, self-serve trials over scheduled demos. The buyers of 2026 already interact with AI in most parts of their lives. The mental model is shifting. ## What This Means Now The teams that win over the next 24 months are not debating whether buyers will trust AI AEs in theory. They are figuring out where AI AEs perform well right now, deploying them in those segments, and measuring actual outcomes. SaaStr data from 100,000+ AI SDR emails shows higher open rates, higher meeting rates, higher close rates. As long as the AI agent is really good, buyers do not mind. The trust objection is temporary comfort. The data will change the conversation. Worth noting: 81% of sales teams already use AI tools, and high performers using AI agents are 3.7x more likely to meet quota. Before you assume a human AE is inherently more trustworthy, ask: has that human actually earned your trust? Or did they just show up on Zoom and you gave them the benefit of the doubt because they were human? That benefit of the doubt is eroding. Fast.

SaaStr
3 days ago
News

Tech sector hits 9% of GDP, but jobs growth stalls

## Tech sector hits 9% of GDP, but jobs growth stalls Australia's tech sector contributes $248.5 billion to GDP, representing 8.9% of the national economy, according to new data from the Tech Council of Australia. The headline number sounds strong. The detail is messier. Direct tech (software companies, IT services, telcos, hardware) accounts for $126.2 billion, or 4.6% of GDP. That is up from $63.5 billion in 2015, but it has grown modestly over the past five years. The direct sector's GDP share actually dropped from 4.7% in 2021 to 4.6% now. The rest of the growth came from indirect tech: companies in finance, healthcare, retail, and construction using software and digital tools. That contribution more than doubled since 2021, from $55.9 billion to $122.3 billion. ### What this means for sales jobs The TCA targets 1.2 million tech jobs by 2030. Current employment sits at 980,000 workers (1 in 15 Australians). The math: they need to add 220,000 roles in five years. For sales professionals, the indirect tech growth matters more than the direct numbers. When a construction company adopts project management software or a healthcare provider deploys telehealth, someone sold that deal. Enterprise software sales, implementation services, and ongoing account management all follow. The report positions tech as Australia's most significant productivity contributor over the past decade. TCA chair Robyn Denholm (also Tesla's chair) and CEO Damian Kassabgi are lobbying Parliament this week to support the sector. ### The jobs reality Direct tech sector growth has slowed. Indirect adoption is accelerating. For AEs and SDRs, that means enterprise deals in traditional industries (finance, health, construction) remain the growth opportunity. The TCA is an advocacy body, not a hiring company. They do not have sales teams or comp data to report. But their 2030 target of 1.2 million tech jobs means roughly 44,000 new roles per year, many in sales and customer success. Comp data for these roles: SDR salaries in Australia range from $60k to $80k base with OTE of $80k to $100k. Enterprise AEs typically see $100k to $120k base with OTE of $160k to $200k. Senior AE roles can hit $140k base with OTE above $240k. The sector is worth nearly $250 billion. The jobs growth needs to catch up.

Startup Daily
4 days ago
News

Google pauses Australia data centre plan over tax structure concerns

Google has paused a potential $20 billion data centre investment in Australia over concerns about tax structure, according to reports from the Australian Financial Review. The company is evaluating whether building significant local infrastructure would establish a permanent establishment in Australia, triggering higher tax obligations. Google currently pays a 20% effective tax rate in Australia through offshore service delivery structures. The standard corporate tax rate is 30%. In 2024, Google paid $83 million in Australian income tax on revenue primarily from advertising (76% of global revenue), cloud services (12%), and other segments. Total global revenue exceeded $307 billion. ## What this means for ANZ cloud sales The investment would have positioned Australia as a potential Asia-Pacific hub for AI and data centre infrastructure, directly competing with AWS's announced $20 billion Australian data centre spend over five years. Google Cloud already operates cloud regions in Sydney and Melbourne. The company maintains multiple subsea cables in the region but has not disclosed ANZ headcount or sales team size in public reports. Meetings between Google's VP of Global Infrastructure and Treasurer Jim Chalmers have occurred. A Google spokesperson stated the company has not requested tax incentives while emphasising prior infrastructure investments. ## The sales context For enterprise AEs selling cloud infrastructure in ANZ, this matters. Google's hesitation creates opportunity space for AWS and Microsoft Azure to position themselves as committed local players. The pause also signals how tax structure influences major infrastructure decisions, potentially affecting enterprise contract negotiations around data residency and local presence requirements. The timing mirrors Amazon cofounder Sergey Brin's move from California over proposed billionaire taxes, though the scale and context differ significantly. Google's last major Australian announcement was a $1 billion cloud and AI investment in 2021. No ANZ-specific CRO or VP Sales roles have been publicly disclosed in recent reports.

Startup Daily
6 days ago
News

AI SaaS Founders: Hire FDEs Before CSMs or Watch Deployment Kill You

# AI SaaS Founders: Hire FDEs Before CSMs or Watch Deployment Kill You Jason Lemkin, founder of SaaStr and former EchoSign CEO, has a framework for the FDE vs CSM hiring debate that cuts through the usual CS playbook. The question: should AI agent companies hire more Forward Deployed Engineers or Customer Success Managers? Lemkin's answer: it depends on where your bottleneck actually is. In AI B2B, deployment is the new constraint, not retention. ## The Real Diagnostic Hire FDEs first if: - Deals close but time-to-value is 60+ days - Customers train agents themselves and hit 40-50% of potential performance - You're seeing silent churn: customers sign, go quiet, disappear - NPS gets dragged down by "couldn't get it working" feedback Hire CSMs if: - Agents are already live and performing for most customers - Churn happens at renewal despite successful deployments - You have predictable, repeatable onboarding that doesn't require customisation - Most customers hit their goals in the first 30-60 days ## The Sequencing Play Lemkin's actual recommendation: don't choose. Sequence it. Get one strong FDE embedded with your top 3-5 customers. Document what they do. Systematise the training. Then hire CSMs to maintain those relationships at scale. The worst outcome: massively scaling CS before deployment is solved. You are just hiring people to manage unhappy customers. ## Why This Matters for ANZ Sales Teams This is the FDE vs CSM question reframed for AI products. Traditional SaaS let you scale CSMs early because onboarding was predictable. AI agent products have a deployment problem that looks like a retention problem. For sales teams selling AI tools: if your close rate is strong but your customers aren't going live, this is your signal. The quota stays the same whether customers deploy or not, but your comp next quarter depends on renewals. Lemkin built EchoSign to $100m ARR and sold to Adobe. He runs a $90m venture fund and the largest B2B/SaaS founder community globally through SaaStr. His take on this comes from seeing hundreds of companies make this exact mistake: scaling sales, then wondering why the metrics break. The framework is simple. The execution is not. But if you are selling AI SDR tools or any AI agent product, deployment velocity determines whether your patch stays viable.

SaaStr
7 days ago
News

NVIDIA forecasts $1T revenue, Meta cuts 16,000 roles in comp rebalance

## NVIDIA's $1T Forecast Was Already Priced In Jensen Huang put a $1 trillion revenue forecast on the table at GTC. The stock moved less than 1%. That flat reaction tells you everything: NVIDIA did $215B last fiscal year, analysts already forecast mid-300s for next year, and the trillion-dollar number is a two-year round-up of consensus estimates. The real bet is capex investment at these levels continuing for four to five more years. When NVIDIA hits $600B in revenue, global capex spend behind it is probably north of $1.2T. Cumulative revenue of $10T over five to seven years is plausible, driven by inference running at scale. The risk worth naming: token consumption may grow 3,000x over five years, but if price per token falls 6x simultaneously, revenue growth is not linear. The bull case requires demand to outrun price compression at massive scale. So far, every data point says it is. Put the probability of something breaking at around 30%. ## Meta's 16,000 Layoffs Are Not What They Look Like Meta is cutting 16,000 roles out of 79,000, roughly 20% of its workforce. Coverage frames this as AI forcing downsizing. That misses what is actually happening: Meta does not have to lay off anybody. Operating margins are still in the 40s. Here is what is really driving this: you spent tens of billions on compute. The depreciation is coming. You do not have the operating cash flow to have both NVIDIA and people. Compute eats jobs. That is literally what is happening. The more important shift: companies are cutting not to shrink, but to restock. They do not need 20 engineers who know C++. They need eight who are genuinely elite at building with AI. They will pay twice the salary for half the headcount. This is a talent shuffle happening in real time, and it probably should be happening at every company regardless of growth rate. ## The One Question That Tells You If Someone Is Actually AI Fluent What commercial AI tool have you brought into your organisation this month? Not which tools they have read about. Not which demos they watched. What did they actually buy, configure, deploy, and put in front of their team in the last 30 days. Anyone on the bleeding edge has done this repeatedly. There are enough great products now that there is no excuse for any functional leader, sales, marketing, engineering, product, to not have evaluated and partially deployed at least one agentic tool recently. Of all even the best startups, maybe 30% of the management team meets this standard at best. In general interviews, it is single-digit percentages. The job that matters right now is not prompt engineer, that existed for about a year and is already gone. The job is agentic deployment expert: someone who can identify, test, deploy, and measure AI tooling at speed. ## What This Means for ANZ Sales Teams If your CRO cannot name an AI tool they shipped to the team this quarter, they are behind. If your comp plan still assumes 2021 headcount models, you are overpaying for underperformance. If your hiring brief says "rockstar AE," you are fishing in the wrong pond. The restock is happening now. Companies are cutting average performers and paying 2x for elite talent who can deploy, measure, and iterate with AI tooling. That is the new bar for quota-carrying roles in 2025.

SaaStr
7 days ago
News

Three Australian startups raise $161 million in one week

# Three Australian startups raise $161 million in one week Advanced Navigation led the week with a $158 million Series C from Airtree Ventures, Quadrant Private Equity, and the National Reconstruction Fund Corporation (NRFC), which separately confirmed $50 million in preferred equity. The Sydney deeptech company builds positioning and navigation systems that operate without GPS, targeting vehicles, ships, and autonomous systems in environments where GPS is vulnerable to interference. MiAI Law and Deftbiotech accounted for the remaining $3 million, though specific round details were not disclosed. MiAI Law is building homegrown legal AI. Deftbiotech is working on health solutions, though sector specifics remain unclear. ## Market context: selective, not surging The $161 million week fits broader ANZ VC patterns. The market raised approximately $1.4 billion in the first ten weeks of Q1 2026, tracking toward $1.8-2.0 billion for the quarter. That is flat with Q1 2025 but still below 2022 peaks. Median deal size sits at $6.2 million as early-stage rounds slow. VC firms are backing fewer companies but writing bigger cheques for quality bets in AI, fintech, healthtech, climate tech, and SaaS. Blackbird Ventures, Square Peg Capital (recently closed a $650 million fund), AirTree Ventures, and Main Sequence Ventures dominate activity. Typical cheque sizes: $250K-$2M for seed, $10M-$30M+ for growth. ## What this means for sales teams Series C raises like Advanced Navigation typically precede hiring expansions, especially for enterprise sales roles. Deeptech companies moving into commercialisation need AEs who can sell complex, high-ACV solutions to government and enterprise buyers. Worth watching for ANZ sales hires in Q2. The broader funding environment remains tight. Portfolio companies report 77% have conducted layoffs, likely including sales teams. Runway pressures are real: 71% of Victorian startups have under 12 months of cash. If you are evaluating startup roles, ask about runway, burn rate, and what the hiring plan looks like if the next round does not close on schedule. Funding concentration in NSW (33%) and Victoria (37%) means most sales roles will be Sydney or Melbourne-based. Remote ANZ roles remain rare at early-stage companies. ## The AI narrative shift Eighty percent of Australian startups sense an AI bubble, yet they are pivoting pitches to investors around AI integration. Sales teams at these companies will be asked to sell AI features that may or may not deliver measurable ROI. Ask hard questions about product-market fit and whether AI is solving real buyer problems or just ticking VC boxes. IPO timelines are extending. Forty-seven percent of startups are targeting 5+ years to public markets, which means longer equity lockup periods and more uncertainty around stock option value. Factor that into comp expectations when evaluating offers from late-stage startups.

SmartCompany
7 days ago
News

SaaStr hits 140% of Q1 revenue with 1.25 sales humans, 20 AI agents

## The Numbers SaaStr hit 140% of Q1 2025 revenue this quarter with 1.25 humans in sales and 5 core AI GTM agents doing work that previously required 4+ people. One agent closed a $70,000 sponsorship deal with zero human involvement. The agents are touching and scheduling qualified meetings with 2x the number of prospects compared to last year's human team. ## What the Agents Actually Do The 5 core GTM agents handle: outbound sequencing, inbound qualification, meeting scheduling, lead reactivation, and Q&A. That last function matters more than it sounds. A human SDR who does not know an answer will guess, punt, or delay. The agent gives an accurate answer in seconds. The lead reactivation piece is worth noting. A meaningful percentage of new meetings are coming from leads the human team had written off. The agent reached back out. It worked. ## What Did Not Get Better The emails are good but not great. The best human sales execs at SaaStr still write better outreach than the AI agents on their best day. The agents hallucinate. Amelia, their Chief AI Officer, spends 30% of her time on agent management and error correction. Complex negotiations, custom sponsorships, relationship building: still require humans. SaaStr would hire another elite human sales exec tomorrow, specifically one who works well with AI agents rather than resenting them. ## The Real Story SaaStr's results are not just about AI agents being better than humans. The company repositioned itself around AI for GTM and caught the vibe coding wave. New sponsors (Salesforce, Replit, Vercel) came in because SaaStr was relevant to what they were building. The agents helped find them, nurture them, and in some cases close them. But the underlying interest was real. Product always matters. The agents scaled what was already working. ## What This Means for Sales Teams The comp math is straightforward: 5 AI agents cost a fraction of 4+ human salaries. The coverage math is clear: 2x the prospects touched. But the quality trade-off is real. Peak human performance still beats peak AI performance on complex deals. The lesson is not that AI replaces sales teams. The lesson is that 1.25 great humans plus well-trained agents is higher leverage than 4+ humans doing everything manually. The question for sales leaders: what are your humans doing that agents could handle at B- quality, freeing them for work that requires A+ human judgment? Worth noting: SaaStr contracted from 20+ employees to 3 humans plus 20+ AI agents over the past year. That is not typical scaling. That is deliberate headcount reduction powered by automation. The revenue grew. The team shrunk. Those are the numbers.

SaaStr
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