The Wire

Real-time updates from ANZ tech sales

22 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
22 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
22 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
22 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
23 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
25 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
26 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
26 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
26 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
27 days ago
News

NSW public sector pushes flexible work over pay for hard-to-fill roles

## The Policy NSW Premier's Department told state agencies to pitch flexible work conditions before offering skill shortage allowances for hard-to-fill roles. The allowance caps at $20k on top of base salary for permanent employees. The directive sits in new "Skills Shortage Allowance Implementation Guidelines" sent to agency heads. It's designed to fill positions where talent won't come at standard government rates. ## The Tension This is the same government that issued a workplace presence directive in August 2024 requiring staff to be in the office more. Transport for NSW goes to 50% hybrid from February 2026. Audit Office of NSW implements full policy by March 31, 2025. So agencies are told: bring people back to the office, but also sell flexibility when you can't fill roles at ticketed rates. ## What Flexibility Actually Means NSW Public Service Commission guidance covers part-time, job sharing, compressed hours, and remote work. No eligibility waiting periods. Formal proposals get discussed within 21 days. The framework covers 400,000+ public servants across NSW and some ACT overlap. This is not about B2B sales teams: it is audit, transport, administration roles. ## The Market Context Public sector employers are competing with private companies that already offer hybrid work. Fair Work Act expansions (2023-2026) strengthened employee rights to flexible arrangements across ANZ. The strategy: use flexibility as a retention and attraction tool when budgets won't stretch to match private sector comp. It is a non-monetary benefit play when the money is not there. ## Why This Matters If you are hiring in ANZ and comp is tight, this is the playbook: flexibility before cash. Public sector is running this experiment at scale. Watch what works and what does not. That data will matter when your CFO says no to raising OTE but yes to hybrid work. The tension between office mandates and flexible work as a hiring tool is not unique to government. Every company trying to fill roles below market rate is running some version of this play.

SmartCompany
27 days ago
News

Google's AI opt-out for search: publishers call it too little, too late

Google announced it will explore letting websites opt out of its AI search features like AI Overviews and AI Mode. The move follows pressure from the UK Competition and Markets Authority (CMA), which wants publishers to control AI participation without losing traditional search visibility. Publishers are skeptical. Danielle Coffey, CEO of the News/Media Alliance, called it a response to "sustained regulatory pressure," not voluntary cooperation. The issue: Google's AI summaries pull content without sending traffic back to the source. Publishers need clicks to fund content creation. AI Overviews cut that pipeline. The proposal is light on substance. Google says it is "exploring updates" for site-wide and page-level opt-outs but has not shared implementation timelines, technical requirements, or how accessible the controls will be. Paul Bannister, CRO at Raptive, noted Google could separate its crawler systems "by tomorrow" but chooses not to because it provides competitive advantage. ## What this means for B2B sales teams If you rely on organic search for pipeline, watch this closely. Google's AI features are already changing how buyers research solutions. AI Overviews surface answers without sending users to your site. That means fewer inbound leads from content marketing and SEO investment. For sales orgs investing in content to drive top-of-funnel traffic: the ROI equation just shifted. If Google strips attribution and clicks, your content becomes free training data for AI that competes with your own lead gen. The opt-out might help, but only if it actually ships and works as promised. Right now, it is a proposal without details. If your pipeline depends on search visibility, you need a backup plan that does not assume Google will keep sending traffic your way.

SmartCompany
27 days ago
News

ServiceNow's $10B GTM engine: how they unified sales, CS, and partners

ServiceNow built a $10B revenue engine by doing what most enterprise software companies talk about but rarely execute: they actually unified their GTM motion. Paul Fipps, President of Global Customer Operations, runs sales, customer success, field marketing, and partners as one integrated team. The reason? He watched too many customers sign deals on Friday and meet an entirely new team on Monday. That handoff problem kills expansion pipeline before it starts. The company tracks customer health daily, not quarterly. Fipps blocks calendar time every week for direct customer conversations and responds within 24 hours. When asked how he would spot churn without dashboards, he pointed to usage patterns and executive engagement, not vanity metrics. ServiceNow's growth model leans heavily on expansion. They added 603 customers spending $5M+ annually in the latest quarter, up 20% YoY, averaging $14.7M per customer. Q4 saw 244 deals over $1M in net-new ACV. The business runs on large customers getting larger, not new logo hunting. On AI, Fipps shared a telling story: a CIO cancelled 900 AI pilots because none drove measurable ROI. ServiceNow's approach embeds agentic AI inside existing workflows instead of building standalone tools. Running their own platform, they generated $335M in annualized productivity gains across their 10,000-person GTM organisation. The company integrated Claude into GTM workflows, cutting account planning from days to minutes. They shifted from six-month product releases to monthly cycles, influenced by Fipps' experience running digital products at Under Armour, where he oversaw a 300 million-member connected fitness ecosystem. For GTM leaders, the takeaway is structural: ServiceNow eliminated organisational seams that create customer friction. Sales does not hand off to CS. Field marketing does not operate separately. Partners are not an afterthought. One motion, one customer view, daily health monitoring. Fipps' advice for building world-class GTM: put the best people in the right seats. Straightforward, but ServiceNow's results suggest they actually do it. Worth noting: no specific comp details emerged, but ServiceNow's scale and enterprise focus suggest competitive enterprise AE and AM packages. The company prioritises existing customer expansion over new territory development, which shapes quota structure and territory design.

Sales Hacker
28 days ago
News

Denholm review targets $4.6bn R&D tax scheme, removes $150m cap

## The Numbers The Strategic Examination of Research and Development (SERD) targets Australia's $4.6 billion annual R&D Tax Incentive scheme. Key proposal: remove the $150 million cap and kill the intensity thresholds. The review, chaired by Tesla's Robyn Denholm and released in March 2026, responds to a decade of declining business R&D investment. Panel included former Chief Scientist Ian Chubb, burns treatment pioneer Fiona Wood, and Kate Cornick. ## What Changes The R&D Tax Incentive reforms aim to: - Remove the $150 million annual cap - Simplify administration (current system is brutal) - Eliminate intensity thresholds - Make Australia competitive for multinational R&D spend The report identifies six "National Innovation Pillars": agriculture/food, defence, environment/energy, health/medical, resources, and technology. These sectors get priority for funding and incentives. Other recommendations: increase foundational research funding, standardise grant processes, reform superannuation rules for venture capital, and use the National Reconstruction Fund as a commercialisation vehicle. ## What This Means For sales teams at R&D-intensive businesses: this could expand your addressable market in ANZ. The reforms target companies that hit the current $150 million cap, typically large tech firms and multinationals. Business Council of Australia CEO Bran Black backs the RDTI changes. Cites Mandala research: $5 economic value per $1 spent. Universities Australia and the Australian Academy of Science (president Chennupati Jagadish) want 2026-27 Budget action. The review proposes a National Innovation Council reporting to the Prime Minister, suggesting government is serious about implementation. ## Reality Check The report has 20 recommendations across six pillars. Political, budgetary, and practical realities will determine what actually ships. No timeline confirmed for implementation. Worth watching: the 2026-27 Budget for specific funding commitments. Stakeholders are pushing for urgent action to reverse Australia's R&D decline and build competitiveness against global markets. Whether that translates to actual policy changes remains to be seen.

Startup Daily
28 days ago
News

60% of sales teams ignore enterprise AI licenses, use personal accounts instead

## The Enterprise AI Adoption Gap Nobody Talks About Larridin CEO Russ Laridan presented measurement data from their Scout platform at SaaStr AI Day that should make every VP of Sales uncomfortable. The workforce AI proficiency company tracks actual AI usage across enterprise sales teams, and the numbers expose a gap between procurement and reality. ## What The Data Shows **60% of employees with enterprise AI licenses still use personal accounts.** You negotiated the Claude Enterprise deal. You rolled out ChatGPT Teams. You ran training sessions. Most of your team logged into their personal account anyway. Zero data capture, zero ability to measure what works, six figures on tooling with no visibility. **Employees have found 5-6x more AI tools than IT sanctioned.** Larridin's internal team of 10 people had six different AI notetakers running. Russ joined a customer call early and counted four competing bots before any humans showed up. Most companies treat this as compliance risk. Wrong frame. Your best reps are running experiments for free. The question is not how to lock it down, it is how to capture what they are learning. **Most AI usage is glorified search.** When Larridin measured proficiency, not just adoption, a significant chunk of activity was sports scores and random lookups. Without distinguishing between a rep using AI to build custom pitch decks and a rep asking Claude what time dinner is, you have no idea if your AI investment generates pipeline or just burns tokens. ## The Real Opportunity **AI will not make your best reps much better. It will make your worst reps less bad.** That matters more. Every sales leader knows the feeling of reviewing a pile of leads and realizing reps just never followed up. Not your A-players. Your average and below-average ones. AI will not turn a C-minus rep into an A-player, but it will turn them into a B. Across a 500-person sales org, compressing that distribution and raising the floor on follow-up quality is a bigger revenue lever than most founders consider. Larridin's Utilization × Proficiency × Value Framework measures who uses AI tools, how well they use them, and what business value gets generated. Their research across 38,000+ engineers shows acceptance rates are misleading metrics for measuring AI adoption success. This aligns with broader market data: 81% of sales teams are experimenting with or fully implementing AI, but only 28% of revenue leaders report AI actually improves revenue-driving performance. One-third of sales ops professionals cite lack of resources or insufficient training as adoption hurdles. Only 35% of sales professionals trust their organisation's data accuracy. ## What This Means For Sales Leaders Stop saying "shadow AI." It tells your best people you do not trust them. At a startup, your employees literally cannot win if the company does not win. The incentives are aligned. Treat tool discovery like a free R&D programme. Bring the good tools into the fold, kill the duplicates, turn what one rep figured out into a playbook for everyone. The gap between AI investment and AI impact is measurement. You need instrumentation that shows which tools drive pipeline, which reps use them effectively, and where you are lighting money on fire. Without that visibility, you are flying blind on your biggest productivity bet.

SaaStr
28 days ago
News

Advanced Navigation raises $158M Series C, NRFC backs defence tech expansion

## The Numbers Advanced Navigation closed a $158 million Series C led by Airtree Ventures, with Quadrant Private Equity participating. The National Reconstruction Fund Corporation separately committed $50 million in preferred equity. Total raised to date: $92.66 million historically, plus this round. FY2024 revenue: $21.85 million. EBITDA: negative $14.27 million. The company is scaling, not profitable yet. ## What They Sell Inertial navigation systems, fibre optic gyroscopes, and GNSS tech for GPS-denied environments. Core customers: defence contractors including Rheinmetall, Boeing, Lockheed Martin, Raytheon. This is B2B enterprise sales, long cycles, high deal values. CEO Chris Shaw cited GPS vulnerability as the growth driver. GPS jamming incidents up 67% in 2025, spoofing attacks up 193%. Over 1,000 vessels affected near Iran last week. A full GPS outage could cost $1 billion daily globally. ## Sales Structure Chief Revenue Officer Christopher McNamara leads revenue. Recent hires include Michelle Toscan as Head of APAC (December 2025) to drive sovereign positioning, navigation and timing sales. Stephen Fujiwara handles US defence program development. No disclosed team size, but the vertically integrated operation runs facilities across Australia plus a Colorado office. Direct B2B model, selling to defence primes and research partners like CSIRO and RMIT. ## Market Context Australian manufacturer competing globally in resilient navigation tech. Recent wins: US Army testing success in February 2026. The company positions as critical infrastructure for autonomous systems in contested environments, where GPS interference is tactical, not theoretical. Series C usually means expansion hiring. Worth watching for AE and technical sales additions in defence verticals, particularly APAC and US markets. Defence sales cycles are long, but once you are in with primes, the book of business compounds. ## The Read Growing revenue, burning cash, raising capital to scale. Standard deep-tech trajectory. The defence tech market is hot, governments are spending, and GPS vulnerability is a real problem with budget behind it. If you are selling into defence or critical infrastructure, this is a signal on where procurement dollars are flowing.

SmartCompany
28 days ago
News

65% of Australian startups have less than 12 months runway

## The Numbers Carta's Australian Startup Outlook 2026 surveyed 500 senior decision-makers. The runway data is bleak: 65% have less than 12 months of cash, 32% have 12 to 17 months, and 3% have 18 to 24 months. Zero startups reported runway beyond two years. The burn rate tells the real story. 86% increased burn over the past year, with 29% calling the increase significant. Victorian startups are under sharper pressure (71% with less than 12 months) compared to NSW (49%). ## What Changed Australian startups raised $5.48 billion in 2025, up 31% on 2024. That sounds good until you factor in concentration: the top 10 Q3 deals accounted for 70% of the $1 billion deployed that quarter. One company raised $330 million, Firmos closed $500 million. Most founders are fighting for scraps. 76% plan to raise capital in the next 12 months. 86% describe the fundraising environment as intensely competitive. Valuations are rising, but only for companies with clear AI positioning. If you raised Series A in late 2021 or early 2022, you are stuck: growth has not justified boom-era prices, so graduating to Series B is near impossible. ## Sales Team Impact Startups are responding predictably. 42% increased prices. The rest split between slowed growth plans, marketing cuts, bridge rounds, and layoffs. Hiring freezes are standard now, especially for roles that do not directly generate revenue. For Series A and Series B companies, this means tighter headcount planning. The 2021 playbook (raise big, hire 8 AEs, figure it out later) is dead. Now it is: prove unit economics, extend runway, hire only when quota relief is locked. IPO timelines stretched. 47% now view public listing as a five-plus-year outcome versus 10% targeting two years. Carta's managing director Bhavik Vashi frames this as maturity, not distress. Maybe. But shorter runways mean fewer bets on unproven sales talent and more pressure on existing teams to hit number. ## What This Means If you are looking at a startup role, ask about runway and burn rate. Not vague answers: actual months of cash and monthly burn. Ask what happens if the next raise takes six months longer than planned. If they raised in 2021 or 2022, ask about the path to Series B and whether the valuation makes that realistic. Runway is not just a finance problem. It determines whether your patch gets cut, your quota gets adjusted, or your role gets eliminated when the bridge round falls through.

SmartCompany
29 days ago
News

Tesla chair Denholm wants manufacturing tax credits, expanded R&D grants for ANZ startups

Tesla chair Robyn Denholm delivered a government-commissioned R&D review recommending expanded research grants and new manufacturing tax credits for Australian startups. The Strategic Examination of Research and Development (SERD) panel issued 20 recommendations after 49 roundtables and 785 submissions. ## The Numbers Australia's R&D investment sits at 1.69% of GDP, well below the OECD average of 2.73%. The report targets raising that figure through: - Reversing cuts to research grants - Introducing manufacturing tax credits (no dollar figures specified) - Reforming the R&D Tax Incentive (RDTI) for startups and scale-ups - Establishing a National Innovation Council to coordinate efforts Worth noting: the review provided no budget, timeline, or specific credit amounts. That matters for tech sales teams planning territory strategies around R&D-heavy prospects. ## What This Means for Sales If the federal government adopts these recommendations, expect: 1. **More qualified pipeline in manufacturing tech**: Tax credits typically unlock budget for automation, AI tooling, and process software. That is addressable market expansion. 2. **Longer sales cycles initially**: Companies wait for policy clarity before committing to R&D-dependent purchases. The review lacks implementation details. 3. **Shift in buyer priorities**: Prospects may delay purchases until they understand RDTI qualification criteria. Your discovery needs to include their R&D tax strategy. The panel included Emeritus Professor Ian Chubb, Professor Fiona Wood, and LaunchVIC CEO Dr Kate Cornick. LaunchVIC runs about 20 staff, no disclosed revenue. Tesla employs roughly 140,000 globally, over $100 billion annual revenue, but has no major owned manufacturing in ANZ. ## The Reality Check This is a recommendation, not policy. The government commissioned the review. They have not committed to funding it. Sales teams selling into R&D-intensive accounts should track legislative progress but not bank pipeline on it yet. Historical data says government R&D programs take 18-24 months from announcement to first payments. Budget accordingly.

Startup Daily
29 days ago
News

AI layoffs in tech: 4.5% of cuts, not the story companies tell

## The Narrative vs The Numbers Tech companies are calling it AI-driven efficiency. Salesforce cut nearly 1,000 employees in early 2026. Block shed 40% of staff. Amazon, Atlassian, and dozens more followed. The pitch: AI made these roles redundant. The data tells a different story. Only 4.5% of 2025 US job losses cited AI as the reason. That is 55,000 positions out of 1.2 million cuts. In Q1 2026, 37,045 tech workers lost jobs across 59 firms. Most of those cuts had nothing to do with automation. ## What This Means for Sales Teams Salesforce replaced 4,000 customer support roles with AI agents. Support, not sales. The distinction matters. Goldman Sachs data shows computer programmers and data entry workers sit at highest risk. Sales roles, particularly those requiring relationship management and strategic problem-solving, show limited AI displacement so far. Accenture cut 11,000 non-AI roles while hiring 37,000 workers with AI skills. Their AI and data team grew from 40,000 to 77,000. That is not replacement. That is rebalancing toward different capabilities. For ANZ sales professionals, the implications are clear: high-salary roles without AI proficiency face pressure. Entry-level transactional roles are vulnerable. Complex enterprise selling, consultative approaches, and strategic account management remain largely human-led. ## The Real Story Most tech layoffs are reactive cost management, not proactive AI transformation. Companies overhired during pandemic growth, overcorrected in 2023-2024, and are now using AI as cover for standard restructuring. Salesforce CEO Marc Benioff dismissed widespread AI layoff concerns before announcing targeted "rebalancing." That language matters. It is workforce management, not technological obsolescence. Worth noting: workers in AI-exposed occupations show no higher job loss rates than others, per Goldman Sachs. Early strain appears in marketing consulting, graphic design, and call centers. Sales, especially relationship-driven enterprise work, remains comparatively stable. The threat is real for certain roles. The scale is overstated. The timeline is longer than headlines suggest. If you are carrying quota in enterprise or mid-market, your biggest risk is not AI. It is quota changes when the CRO leaves.

Startup Daily
29 days ago
News

Leigh: uni degrees no shield from AI cuts, judgment beats credentials

## The take Your degree is not protecting you from AI-driven layoffs. Andrew Leigh, Assistant Minister for Productivity, says the traditional credential ladder is breaking down as AI devalues cognitive expertise. For sales teams, this means rethinking how you hire and what skills you build. ## What Leigh actually said In a Brisbane speech, Leigh argued the relevant split is no longer "has degree vs no degree." It is "judgment vs execution, oversight vs production." Meta-skills matter more: framing problems, spotting errors, allocating attention, taking responsibility. The coding degree you were told to get? Less valuable than knowing when AI output is wrong. Jobs and Skills Australia estimates nine out of ten roles face augmentation, not full automation. But augmentation still changes headcount and comp structures. ## What this looks like in practice Atlassian: 1,600 layoffs (10% of workforce) to self-fund AI and enterprise sales investments. 30% of cuts hit Australia. Even the CTO is out. CEO Mike Cannon-Brookes was direct: AI changes skill mixes and role numbers. Cost: $225-236 million, mostly complete by June 2026. That is a major ANZ employer restructuring its sales and tech org around AI. Not in 2030. Now. ## What this means for sales professionals If you are hiring, credentials matter less than judgment. Can this person frame a complex enterprise deal? Can they spot when the AI-generated email is tone-deaf? If you are building skills, focus on oversight, not execution. AI can draft the follow-up. You need to know if it is any good. Leigh's point about inequality: previous tech waves increased the wage premium for degrees. This one might do the opposite. Worth noting if you are advising team members on upskilling paths. ## The ANZ context Atlassian is Australian-founded, Sydney-headquartered, dual-listed (ASX and NASDAQ). When a company this size restructures 30% of ANZ headcount around AI, that is a market signal. Leigh estimates AI could add $116 billion to GDP over a decade if adoption is broad. But adoption means different headcounts and different comp structures. No one is safe because they have a degree. You are safe if you can do what AI cannot: exercise judgment, take responsibility, know when the machine is wrong.

SmartCompany
29 days ago
News

Founder leaves $100M ARR SaaS with 10,000 customers to start AI company

# The Numbers Behind The Exit Another founder just announced they are leaving a $100M+ ARR SaaS business. Not struggling. Not burning cash. Not losing customers. **What they walked away from:** - $100M+ ARR - 100%+ Net Revenue Retention (existing customers are expanding) - 10,000+ customers - Real distribution, real revenue, real product-market fit The reason: "excited to explore what AI could do in the space." The employees learned about it on LinkedIn. ## Why This Matters For Sales Teams If you are working at a Series B+ company right now, watch for this pattern. Founders leaving profitable businesses to chase AI is becoming common. That decision has downstream effects: **What usually happens next:** - Leadership vacuum while the board finds a replacement - Quota adjustments (sometimes up, rarely down) - Strategic direction shifts - Team morale takes a hit when the founder exits via social media For reps at high-growth SaaS companies: this is your signal to ask hard questions about roadmap, leadership succession, and whether the company plans to compete or get disrupted. ## The Part That Does Not Add Up Starting from zero means starting from zero. No distribution, no customer relationships, no revenue. Every AI founder is making the same bet right now, in the most crowded market in tech. Meanwhile, the company they left has: - 10,000 customers who already trust them - Years of usage data and workflow insights - $100M+ ARR to fund R&D without begging VCs - 100%+ NRR proving customers want to expand The obvious move: build the AI product for the customers you already have. Use the revenue to fund it. Use the relationships to design it. Use the data to train it. Instead, most founders are walking away to fight for attention in a market where every pitch deck starts with "AI-native." ## What Sales Teams Should Watch For If your founder starts posting about AI exploration: - Ask about the product roadmap in your next leadership call - Check if comp plans are changing (they usually do during transitions) - Watch for headcount freezes or territory restructures - Update your LinkedIn: leadership exits often trigger team turnover The grass is not greener. It is just different grass. And the sales team is usually the last to know.

SaaStr
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