The Wire

Real-time updates from ANZ tech sales

about 14 hours ago
News

AI agent rollouts hitting wall: FDE shortage stalling enterprise deployments

## The Bottleneck No One Saw Coming Every company rolling out AI agents at scale is running into the same problem: forward deployed engineers are impossible to hire. The shortage is not just a hiring challenge. It is a structural issue about what it actually takes to get AI working inside a real enterprise. FDEs sit at the intersection of product, engineering, and customer success. They go on-site, understand actual workflows, and configure the product to work inside those workflows. They are not building from scratch. They are not doing basic support. They are doing the hard middle work of making software actually land in the real world. Palantir built their entire go-to-market around this model. You needed their people inside your organisation, configuring and training the system for your specific context. That model worked. It was expensive and it did not scale the way SaaS was supposed to scale. But it worked, because complex software in complex environments requires human judgement to deploy well. Now almost every serious AI product has the same requirement. And almost no one has enough people who can do it. ## Why CS Cannot Fill This Gap The instinct at most companies: solve this with customer success. CS is already post-sale, already focused on adoption. Just upskill them, right? Wrong. Traditional CS was built for a different era. The job was: help customers use software they have already decided to buy, make sure they hit their renewal metrics, escalate bugs. It was reactive, relationship-driven, and optimised for retention. FDE work is different in almost every way. It is proactive, technical, and optimised for deployment. You are going in before the problem exists and configuring the system so the problem never happens. The skill set required is closer to a solutions engineer or a junior product manager with strong customer empathy than it is to a traditional CS rep. Most CS teams do not have it. Retraining takes longer than most companies want to admit. ## Agents Cannot Deploy Themselves. Yet. The whole premise of AI agents is that they automate work. But deploying an AI agent is itself significant work, and it is work the agent cannot do for you. Not yet. Someone has to understand the customer's workflows deeply enough to know where the agent fits. Someone has to train the agent on the right data, the right context, the right edge cases. Someone has to test it, catch where it breaks, and iterate. Someone has to get internal buy-in from the people whose jobs will change when the agent goes live. That is FDE work. And it is manual, high-judgement, human work. Palantir announced recently that they have gotten deployment times down over 90% using forward deployed engineers. That is remarkable. It also means the best-in-class operator in this model is still deploying manually, just faster. 90% reduction in deployment time is not the same as automating deployment. The human is still in the loop. ## What This Means for Sales Teams Every serious AI vendor is now competing for the same small pool of people who can do this work. The companies that came up through Palantir, the solutions engineers from the major cloud platforms, the implementation consultants from the enterprise software world: everyone wants them, and there are not enough of them. Meanwhile the demand is exploding. Every enterprise that decides to deploy AI agents needs FDE-calibre people to make it work. For sales teams, this creates a few realities: **Longer sales cycles.** If you cannot deploy the product, you cannot prove value. If you cannot prove value, the deal stalls. **Higher implementation costs.** Companies are paying premium rates for FDEs. That cost gets passed somewhere, usually to the customer or to margin. **New comp structures.** Some vendors are tying commission to successful deployment, not just closed deals. If the product does not land, the rep does not get paid out fully. The companies winning at deployment are building serious enablement programmes: not just documentation, but hands-on training that gives customer-side operators the skills to configure and train agents themselves. If you are selling AI tools, ask your leadership what the deployment plan actually looks like. If the answer is "CS will handle it," the answer is wrong.

SaaStr
about 14 hours ago
News

Future Fund cutting 10 roles, banking $15m from tech automation

## Future Fund cutting 10 roles, banking $15m from tech automation The Future Fund is reviewing 10 roles across investment and operations teams after investing in data systems and automation. The cuts follow a tech overhaul that CEO Raphael Arndt says will save $10-15 million in FY2026/27. The $335 billion sovereign wealth fund, which manages public sector super liabilities, expects the technology investment to shave 5-7% off operating costs next year. Further savings are projected for subsequent years. "We're baking in the benefits and maximising the efficiencies of our technology overhaul," Arndt said. The fund has around 140-150 total headcount, concentrated in Melbourne and Sydney. The role reviews cover both investment professionals and support functions. The fund said it is consulting with affected staff before finalising decisions. ### Finance sector automation trend The Future Fund joins a growing list of financial institutions cutting roles after deploying AI and automation. Bendigo and Adelaide Bank announced hundreds of job cuts in April after signing two technology deals. Unlike traditional B2B companies, the Future Fund operates without sales teams or commercial revenue targets. It invests globally in equities, fixed income, property, and alternatives. The fund does not have a CRO or VP Sales: its structure centers on portfolio managers and investment analysts. Arndt said the tech investment has been "critical to investment performance" and positions the fund for what he calls a "new investment order" reshaping markets. The savings come from improved data systems and renegotiated external service contracts. Costs and staffing remain "appropriate for the scale and complexity" of the fund's mandate, Arndt said, but the organisation will continue assessing resource needs. Worth noting: this is a government entity with no traditional sales function, but the automation trend mirrors what commercial enterprises are doing. When large, well-funded organisations start cutting roles to automation, the rest of the market usually follows.

Startup Daily
about 14 hours ago
News

Deteqt raises $5M seed, no sales team yet

Deteqt, a University of Sydney spinout, closed a $5 million seed round today. Main Sequence led, with ATP Fund, BOKA Capital, Beaten Zone Venture Partners, Uniseed, and the university participating. The company builds chip-scale quantum magnetometers using diamond-on-silicon tech. Target markets: GPS-denied navigation for defense (drones, submarines), autonomous vehicles, and potentially portable MRI. They already have an Australian Defence Force contract. Founded in 2025 by CEO Dr. Jim Rabeau and Professor Omid Kavehei, with Rupal Ismin as COO. This follows a $750k pre-seed in March 2025. ## What This Means for Sales No sales team details disclosed. No CRO, no VP Sales, no AE count. This is pre-revenue, pre-GTM team. Defense tech sales roles at quantum startups typically look different from SaaS: - Longer sales cycles (12-24 months for defense contracts) - Heavy on government procurement experience - Equity compensation often outweighs base (early-stage defense tech) - Remote roles rare due to security clearance requirements For context: aerospace and defense contractor sales roles in ANZ are heating up. Quantum sensing sits at the intersection of deep tech and defense, a niche but growing market. Companies like Infleqtion (US-based quantum tech) offer remote roles, but most defense-focused positions require on-site presence. ## The Numbers Total raised: $5.75M ($5M seed + $750k pre-seed). Funds go to product development, diamond chip manufacturing scale-up, and team growth. No revenue disclosed. No current sales headcount disclosed. Deteqt is Sydney-based, targeting Australia-US-UK investor and customer networks. Named a 2025 InnovationAus Awards finalist in Defence and Dual Use. ## Bottom Line Early-stage deep tech with defense applications. If they build a sales team in the next 12 months, expect equity-heavy comp and a focus on government procurement experience. Not hiring yet, but worth tracking if you are in defense tech sales.

Startup Daily
1 day ago
News

Canva hits $4B ARR but AI tools are eating power users

## The Numbers Look Great. The Usage Pattern Does Not. Canva went from $23M ARR in 2018 to $4B at end of 2025. That is 173x growth in seven years. They have 265 million monthly active users, 31 million paid subscribers, and their B2B segment alone is $500M ARR, doubling year over year. By every traditional metric, they are crushing it. Profitable for eight consecutive years. Sydney-based, built a global design platform that competes with Adobe. But here is the problem: power users are going quiet. ## What Stealth Churn Actually Looks Like No single competitor replaced Canva. Instead, specialty AI tools are eating individual use cases. Reve handles thumbnails. Opus Pro cuts video clips. Higgsfield does short-form video. Each tool does one thing better than Canva's all-in-one approach. The power user who drove the original purchase, who would have championed expansion, stops logging in. The team still uses Canva for social graphics and event collateral. Usage metrics look fine. NPS stays high. The account renews. But the person who would fight for budget at renewal just checked out. Quietly. Without even noticing. ## Why This Matters for B2B Sales When your topline is growing 100% year over year, you cannot see this pattern in your numbers. New revenue masks quiet disengagement at the edges. By the time it shows up in retention metrics, you have lost 12 to 18 months of leading indicators. Your most engaged customers are exactly the ones most likely to discover purpose-built AI alternatives. They care about output quality. They are early adopters. They are your expansion revenue. Your casual users stick around because switching costs still matter and $12 per month is not worth the effort to cancel. But inertia-based retention is the worst kind of retention. It means your product became a rounding error in someone's budget. Not essential. Just cheap enough to ignore. ## The Category Risk This is not a Canva problem. Canva will probably be fine. $4B ARR, strong execution, massive distribution. But every horizontal B2B tool faces this dynamic right now. When AI tools can do one specific job better than your all-in-one platform, power users will find them. Your metrics will not warn you until it is too late. Worth asking: who are your power users, and what are they actually using right now?

SaaStr
3 days ago
News

Public software stocks down 50% in six months, AI spend hits sales budgets

# Public Software Stocks Down 50% in Six Months The SaaStr.ai Index of the top 25 public B2B software companies hit a 50.5% decline over six months, from October 2025 to April 2026. Half the market cap, gone. This is not a 20% correction. This is a structural re-rating of software as an asset class. For the first time ever, public software companies trade at a P/E discount to the S&P 500. Not at parity. Below. Forward P/E multiples for application software collapsed from 84x in 2021 to 22.7x today. The market's implied long-term growth rate for public SaaS dropped from 4.7% three months ago to 1.1% now. The market is saying: software is no longer a premium business. ## What This Means for Sales Teams Two forces are hitting simultaneously: **Budget displacement.** When Anthropic hits $19B in annualised run rate, growing $6B in a single month, that spend comes from somewhere. Approximately 75% of new hyperscaler infrastructure spending in 2026, over $450 billion, targets AI infrastructure. That money used to buy Salesforce seats, ServiceNow modules, HubSpot licenses. Not anymore. **Substitution fear.** AI agents might replace seats instead of complementing them. Seat-based revenue models depend on headcount growth. If agents replace headcount, the model reverses. Investors are pricing this into terminal value, which explains why current earnings do not explain the decline magnitude. Category leaders are getting crushed: - **Atlassian (TEAM):** Down 57.91% in the recent quarter, 67.84% over the past year. Founded in Sydney in 2002, the company that built Jira for every engineering org is now 71.80% below its May 2025 high. - **HubSpot (HUBS):** Down 50%+ over the past year. $2B+ ARR, one of the best go-to-market motions in B2B history. - **Salesforce (CRM):** Down 30%+ in Q1. The defining CRM platform of the last 20 years. - **ServiceNow (NOW):** Down 30%+ in Q1, despite actually accelerating. - **Adobe (ADBE):** Down from $638 to under $350. These are not speculative bets. These are cash-generating, deeply embedded businesses. The market is treating them like they face existential risk. ## ANZ Context Atlassian maintains ~500-1,000 headcount across Sydney HQ and Auckland offices, focusing on enterprise sales to government and finance sectors. The company reports no major 2026 hires or cuts amid the downturn, relying on inbound and partner-led models over large direct sales teams. Sales organisation emphasises efficiency under President Anutthara Gose, promoted in 2024. Broader SaaS firms report stalled net retention at ~90% gross as AI shifts divert budgets. Sales teams are feeling this in quota design, comp structures, and territory planning. When your product category loses half its market cap in six months, quota relief conversations get harder. ## What Is Holding Up Not everything is down equally. Companies performing better share characteristics: **Palantir (PLTR):** +135% in 2025, cooling now but still outperforming. Rule of 40 score hit 127 in Q4 2025. Revenue growth at 70% YoY. They are not a seat-based SaaS vendor. **Cloudflare (NET):** Guided 2026 at $2.79B revenue, 28-29% growth. AI agents generate an order of magnitude more outbound requests than user-driven apps. All of that flows through Cloudflare infrastructure. **DigitalOcean (DOCN):** Up nearly 50% YTD in an index down 50%. Simpler stack, smaller companies. The bifurcation is clear: infrastructure that enables AI outperforms applications that AI might replace. For sales professionals, this matters. Comp packages are tied to equity. Territory planning assumes growth. Quota is built on market assumptions. When the market re-rates your entire sector by 50% in six months, every one of those assumptions changes. Worth noting: if you are carrying a bag at a company down 50%, your equity-based OTE just got a lot less attractive.

SaaStr
4 days ago
News

SaaStr AI agents: $4.8M pipeline, 3 humans, 90 days of daily management

## The Numbers SaaStr deployed 20+ AI agents across SDR, support, and GTM functions. Headcount dropped from 20+ employees to 3 humans. Revenue growth shifted from negative 19% to positive 47% year over year. AI-attributed pipeline hit $4.8M, closed-won $2.4M. Outbound volume reached 60,000+ personalised emails with 5 to 7% response rates against an industry average of 2 to 4%. Jason Lemkin, SaaStr founder and former EchoSign co-founder (acquired by Adobe, scaled to $100M+ ARR), shared why most AI agent implementations fail. The pattern: teams deploy AI SDRs, check back in two weeks, see 0.02% conversion, and blame the tool. ## What Actually Works SaaStr's Chief AI Officer spends 30% of her time managing agents. The team invests 60 to 90 minutes daily: reviewing output, refining prompts, QA-ing emails, iterating on what converts. Lemkin is clear: give it 90 days of this discipline before drawing conclusions. The failures follow predictable patterns. Teams deploy AI on top of broken processes (bad messaging does not improve at 10x speed). CRM data quality collapses under AI load (agents need clean data, humans can work around it). Segmentation stays lazy (generic outreach scales into generic spam). SaaStr runs 15+ email variants across segments: company stage (seed through public), role (CEO, CRO, VP Sales), past event engagement, vertical, deal size. A Series A CEO who has never attended SaaStr gets different outreach than a returning enterprise sponsor's VP of Marketing. ## The AI Implementation Failure Rate Most AI projects fail because teams treat agents like software: deploy once, let it run. That works for static tools. It does not work for AI that needs training, feedback loops, and constant refinement. The companies succeeding with AI agents are managing them like junior reps, just with higher volume potential. Lemkin's advice: audit your CRM before deployment, fix your messaging with humans first, budget real time for daily management, and segment radically. If your best human SDR cannot book meetings with current messaging, your AI SDR will not either. AI scales what works. It does not fix what is broken. Worth noting: SaaStr's results came after months of painful iteration. The 47% revenue growth and $4.8M pipeline did not happen in week one. Most teams churn before they get there.

SaaStr
5 days ago
News

Swyftx cuts 45 roles, replaces CEO after $100M acquisition spree

## Leadership Out, Layoffs In Swyftx replaced CEO Jason Titman after less than two years and is cutting 15% of staff, roughly 45 roles from a 300-person headcount. Cofounder Alex Harper and CFO Andrea Yuen (hired early 2025) are now acting co-CEOs. The Brisbane-based crypto exchange, founded in 2019, serves 1.5 million users and processes over A$1 billion in monthly trades. It is the largest crypto platform in ANZ. ## Post-Acquisition Cleanup The cuts follow an aggressive M&A run: Easy Crypto (NZ, $33M, March 2025) and Caleb & Brown (US-focused, $100M+, July 2025). The Caleb & Brown deal was the largest crypto M&A in ANZ history and pushed headcount to 300. Swyftx says it is removing duplication and simplifying operations after the business "increased in size and complexity." Translation: two acquisitions in six months created overlap. Now they are fixing it. ## What We Don't Know No details on which roles are affected. Sales teams? Engineering? Support? The company started "discussions" last month but has not finalised the list. No severance details, no timeline, no clarity on whether this hits revenue-generating roles or back office. For context: crypto exchanges typically run lean sales teams (mostly inbound, partnerships, and enterprise/institutional). If Swyftx is cutting 45 roles post-acquisition, the real question is whether they are consolidating sales coverage across ANZ, NZ, and US markets or just trimming support functions. ## Market Context This fits the broader crypto layoff trend. Multiple exchanges and Web3 startups cut staff through 2024-2025 as the crypto-friendly regulatory environment failed to materialise as expected. Swyftx avoided specifics on regulatory pressure but mentioned "prioritising investment in innovation," which usually means cutting headcount to fund product. Worth noting: Swyftx tried to merge with Superhero in 2022 to create a fintech unicorn. That deal collapsed six months later. Now they are back to running the business, except bigger and with fresh redundancies. ## Bottom Line CEO out, 45 roles gone, two cofounders running the show. If you are in crypto sales in ANZ, this is another data point: growth through M&A often means short-term headcount cuts. The specifics matter, and Swyftx has not shared them yet.

Startup Daily
5 days ago
News

MYOB locks five-year Microsoft AI deal, chases Xero in accounting arms race

## MYOB locks five-year Microsoft AI deal, chases Xero in accounting arms race MYOB confirmed a five-year Microsoft partnership to build AI agents into its accounting platform, announced April 8. The deal comes days after rival Xero revealed its Anthropic collaboration, marking an escalation in the accounting software AI arms race. The partnership gives MYOB access to Microsoft Foundry, Copilot Studio, and Agent 365 to accelerate AI feature deployment. Microsoft is providing dedicated engineering support to MYOB's team. Initial focus: intelligent AI agents for cash-flow forecasting and compliance automation across MYOB's platform. ### What this means for the market MYOB serves 3.2 million SME customers across ANZ, competing directly with Xero, QuickBooks, and Sage. The Microsoft deal positions MYOB to defend its dominant ANZ market share as AI adoption accelerates. Current SME AI adoption sits at 29%, according to available data, leaving significant upside for platforms that ship useful AI features first. The companies are jointly funding the expansion. No financial terms disclosed. MYOB was acquired by Bain Capital in 2019 for A$3.4 billion and remains privately held, so no recent revenue figures are public. ### The sales angle MYOB is running an "AI Everyday" program to train internal teams, including likely sales, on AI productivity tools. The goal: enhance customer experiences and accelerate product adoption. Team size and recent sales hires are not disclosed in available sources. For sales professionals selling into SMEs or accounting firms: the AI accounting software category is moving fast. MYOB and Xero are both racing to ship AI features that automate reconciliation, forecasting, and compliance. If you are selling adjacent tools or services, expect your buyers to ask how you integrate with AI-native accounting workflows. Jane Livesey, president of Microsoft ANZ, said the partnership will "embed AI directly into the workflows Australian and New Zealand businesses already rely on." Translation: Microsoft is betting MYOB's regional dominance and compliance expertise will accelerate enterprise AI adoption across ANZ SMEs. The deal runs five years. Watch for feature velocity as the key metric: who ships useful AI agents faster wins the next wave of SME accounting market share.

SmartCompany
5 days ago
News

Five Aussie startups raise $30M: Haast leads with $17M Series A

Five Australian startups raised $30.1M this week, with Sydney-based Haast leading at $17M Series A. ## The Deals **Haast: $17M Series A** Peak XV Partners led, with DST Global Partners, Airtree, Aura Ventures, and Black Sheep Capital participating. The Sydney compliance automation platform embeds policy frameworks into enterprise tools. Founded by Kunal Vankadara, it plans to scale "agentic workflow products" and expand globally. No sales team size disclosed. No hiring numbers. No revenue metrics. **Kimia: $7M seed** Airtree led, Blackbird and Skip Capital joined. The chemical industry AI platform helps commercial teams access technical knowledge. Co-founders Farid Mirmohseni and Sajjad Azami are targeting fragmented information workflows in chemicals. Again: no team size, no hiring plans, no comp data. **Also This Week:** - **Rosella**: $5.7M AUD pre-seed for AI insurance brokerage (US-focused, minimal ANZ presence) - **Future Maintenance Technologies**: $8M first external round for industrial robotics (Brisbane, ~$40M valuation) - **Arlula**: $3.4M for defence-focused space tech ## What It Means for Sales Series A and seed rounds typically trigger hiring. Haast's enterprise focus suggests AE and CSM builds. Kimia's commercial team positioning implies sales enablement roles. But here is the pattern: five funding announcements, zero hiring specifics, zero comp transparency. The usual "we are scaling" language with no actual numbers. Meanwhile, **Koala** (mattress DTC) hit ASX via $20M IPO at $380M+ market cap. That is a scaled operation with real revenue, but still no CRO or sales leadership details public. ## ANZ Funding Context Strong 2025-26 Aussie funding environment continues. Airtree and Blackbird remain active in early-stage B2B. Peak XV (formerly Sequoia India/SEA) co-leading Haast signals international investor confidence in ANZ enterprise software. But for sales professionals evaluating opportunities: funding announcements mean nothing without team-building plans and comp structures. Call the founders directly if you want real numbers.

SmartCompany
5 days ago
News

HubSpot switches to pay-per-resolution AI pricing, following Sierra and Intercom

HubSpot is switching its Breeze AI pricing to pay-per-resolution from April 14. Customer Agent drops from $1.00 per conversation to $0.50 per resolved conversation. Prospecting Agent moves from flat monthly per contact to $1.00 per lead recommended for outreach. Chief Customer Officer Jon Dick framed it simply: "You pay when it works, full stop." The numbers so far: Breeze Customer Agent resolves 65% of conversations across 8,000+ customers, cuts resolution time by 39%. Prospecting Agent activations up 57% quarter-over-quarter. HubSpot is not first here. Sierra launched with outcome-based pricing in early 2024 and hit $150M ARR by February 2026. One in four customers has revenue over $10 billion. Founder Bret Taylor has been vocal about why this model gives startups an edge: legacy providers on seat-based pricing face a conflict when their AI gets better and clients need fewer seats. Intercom's Fin agent ran the same playbook. Launched at $0.99 per resolution, grew from $1M to $100M ARR. Now resolves 2 million customer issues per week. Resolution rates climbed from 27% at launch to 66-67% across the customer base. Intercom backed it with a $1M performance guarantee: hit 65% resolution or they pay you $1M. That kind of bet forces the product to work. Salesforce went a different direction with Agentforce: three pricing models at once. Per-conversation, per-login session, and subscription. Covers more buyer preferences but adds complexity. For ANZ sales teams evaluating CRM stack, the pricing shift matters less than the trend it represents. Every major platform is moving towards agents and outcomes. HubSpot's $2.7B ARR and 17% year-over-year growth gives it scale to absorb the transition risk. The 5,000+ ANZ customers on HubSpot will see the new pricing roll out the same as global. Real question: does outcome-based pricing change your CRM decision in 12 months when Salesforce, HubSpot, and every other platform offers the same model? Or does it just become table stakes and you are back to evaluating on feature depth, integration quality, and whether the AI actually lifts close rates? HubSpot says Prospecting Agent users see 10% close rate improvement. That number matters more than the pricing structure. Show me attainment data, not billing innovation.

SaaStr
5 days ago
News

Haast raises $17M Series A, relocates to US

## Haast raises $17M Series A, relocates to US Sydney-founded compliance startup Haast closed a US$12 million (A$17M) Series A led by Peak XV Partners, with DST Global Partners and existing backers Airtree, Aura Ventures, and Black Sheep Capital participating. The company has now raised US$17.05M total since launching in 2023. Here is what changed: Haast relocated to New York. The US is now the primary market. ### The pitch Haast automates marketing and content compliance for enterprises in regulated industries: financial services, pharma, FMCG, retail. The problem they are solving: legal and compliance teams cannot keep pace with AI-driven content production. Manual review processes create bottlenecks. CEO Kunal Vankadara says the platform embeds policy and risk standards directly into workflows, letting teams move at AI speed without breaking governance rules. Translation: marketing and sales teams get their content approved faster, compliance teams stop being the blocker. ### The traction Haast reports 4.5x revenue growth in 12 months and zero customer churn. Client list includes Telstra, Zurich ANZ, Aviva, and Future Super. Worth noting: no public revenue figures, so scale remains unclear. The company claims the platform reduces manual compliance review by up to 80% and accelerates approval timelines by 3x. If those numbers hold across enterprise deployments, that is a meaningful operational unlock for sales and marketing teams stuck waiting on legal sign-off. ### What this means for sales teams For ANZ sales professionals in regulated industries, this matters if your comp is tied to campaign velocity or content-driven pipeline. Compliance friction directly impacts time-to-market. If Haast's automation actually works at scale, it removes a bottleneck that sales teams cannot control but constantly blame for missed numbers. The Series A and US move signal they are chasing enterprise scale, not ANZ mid-market. That usually means longer sales cycles, bigger deals, and if you are selling into these accounts, expect procurement processes that reflect the compliance obsession this product is built around.

Startup Daily
6 days ago
News

Canva acquires two more AI startups, Stayz founders join

Canva acquired two Sydney startups: Simtheory (AI collaboration platform) and Ortto (marketing automation, 11,000+ customers). Both founded by Chris and Mike Sharkey, who sold Stayz to Fairfax in 2006, then to HomeAway for $225M in 2013. This is Canva's fourth and fifth acquisition in six weeks. MagicBrief in January, MangoAI and Cavalry six weeks ago, Doohly two weeks ago (rumoured $30M). Financial terms not disclosed. Blackbird backed Ortto, which raised $46M total including a $16M round in 2017. The Sharkeys join Canva leadership: Mike ran both startups as CEO before the deals. Canva is at $4B annualised revenue with 265M monthly users, 31M paid. That revenue number suggests significant enterprise traction, but sales team size and structure not disclosed. Context for sales professionals: Five acquisitions in six weeks signals aggressive expansion. Marketing automation (Ortto) and AI collaboration (Simtheory) acquisitions point to enterprise play beyond freemium design tools. When companies buy this fast, integration teams grow: implementation, customer success, account management roles typically follow. Ortto served 190 countries pre-acquisition. That customer base needs coverage. Simtheory raised $5M seed 12 months ago, still early but validates AI workflow thesis. No hiring announcements yet. When Canva moves, they move fast: watch for Sydney-based sales roles supporting enterprise AI and marketing automation products. The Sharkey brothers have enterprise sales DNA from Stayz days, expect that experience to shape go-to-market. Worth noting: Canva does not publish sales team metrics. $4B ARR with 31M paid users suggests strong product-led growth, but enterprise deals at that scale need humans carrying bags. Acquisition spree of this pace usually means team expansion within 90 days.

Startup Daily
6 days ago
News

Zapier makes AI fluency a hiring requirement, shares assessment rubric

## Zapier makes AI fluency a hiring requirement, shares assessment rubric Zapier now tests AI fluency in every interview. Not nice-to-have. Requirement. The workflow automation company went from 10% to 97% daily AI usage across 800 employees in under two years. CEO Wade Foster credits a single decision: stopping work in March 2023 for a week-long hackathon after GPT-4 launched. AI adoption jumped from 10% to 50% in five days. They ran quarterly hackathons after that. The marketing team alone shipped 57 AI projects. Now they hire for it. ### The four-level rubric Zapier assesses candidates on a scale: Unacceptable, Acceptable, Adaptive, Transformative. **Unacceptable:** Cannot articulate basic AI use cases or demonstrate baseline fluency. **Acceptable:** Uses AI for standard tasks. Email drafts, research summaries, basic automation. **Adaptive:** Builds workflows, chains prompts, understands when AI is the right tool versus when it is not. **Transformative:** Redesigns processes around AI capabilities. Builds agent workflows. Identifies business problems AI can solve that humans missed. Most sales orgs are still hiring at Acceptable. Zapier wants Adaptive minimum. ### What this means for sales teams If you are hiring AEs or SDRs in 2026 and not testing AI fluency, you are behind. The question is not whether your team uses AI. It is whether they use it well enough to 10x their output. Zapier runs 800+ AI agents now. More agents than employees. Their support team handles 50% of tickets with AI. Foster uses a personal "advisory council" of AI sub-agents for major decisions. That productivity gap shows up in quota attainment. Teams that adopted AI early are closing faster, researching deeper, and personalising at scale. Teams that did not are still manually building prospect lists. ### The assessment question In interviews, Zapier asks: "Walk me through how you would use AI to solve [specific sales problem]." They listen for workflow thinking, not just tool names. Can you chain prompts? Do you know when to hand off to a human? Can you build a repeatable process? If your interview process does not include an AI assessment, add one. If your onboarding does not include AI training, fix that. If your sales leaders are not using AI daily, that is your biggest bottleneck. The comp gap between AI-fluent reps and non-fluent reps is widening. Zapier just made it a hiring requirement. Expect more companies to follow.

Sales Hacker
6 days ago
News

Canva buys Simtheory, Ortto: AI pivot targets enterprise sales teams

## Canva buys Simtheory, Ortto: AI pivot targets enterprise sales teams Canva acquired Sydney startups Simtheory and Ortto on April 8, its fifth and sixth acquisitions in 10 months. The deals mark a clear shift: the $4 billion design platform is building an AI-powered work platform targeting enterprise teams. Simtheory builds custom AI assistants for enterprise and government. Teams can deploy agents that integrate with OpenAI, Anthropic, and Google models, automating CRM updates, document creation, and email management. For sales teams, this means AI agents that can actually touch your stack: update Salesforce, draft follow-ups, pull pipeline reports. Ortto handles marketing automation: unified customer data, campaign deployment, metric tracking. The platform serves 11,000 customers across 190 countries. That customer base matters. Canva now has a foothold in marketing ops at scale, territory adjacent to sales enablement. COO Cliff Obrecht called founders Chris and Mike Sharkey, who built both companies, "exactly the kind of founders we love partnering with." The Sharkey brothers sold Stayz for $225 million in 2013. They know how to build and exit. Canva did not disclose deal terms. No comp details, no team size, no integration timeline. ### What this means for sales teams Canva is not just adding features. The company is assembling infrastructure for end-to-end B2B workflows: design, automation, AI agents, customer data. If you are selling into marketing or revenue ops, watch this space. Canva is building a platform play that touches prospect research, content creation, campaign execution, and CRM integration. The AI agent angle matters more than the design tools. Enterprise sales teams need automation that connects systems, not just pretty decks. Simtheory gives Canva that capability. Ortto's 11,000 customers represent potential cross-sell territory. Marketing automation users need sales enablement tools. That is not speculation, that is pipeline math. ### ANZ context Both acquisitions are Sydney-founded, keeping talent and IP in the ANZ market. Canva maintains its Sydney headquarters and continues aggressive M&A: MagicBrief, MangoAI, Doohly ($30 million in March), now Simtheory and Ortto. The company hit $4 billion ARR by end of 2025, still private, still expanding. For ANZ sales professionals, this is local product development at scale. Enterprise AI tools built in Sydney, deployed globally, competing with Adobe and emerging workflow platforms. No details yet on how Canva plans to staff the new capabilities or what this means for go-to-market teams. If historical patterns hold, acquisitions lead to hiring. Watch for AE and solutions engineer roles as Canva pushes deeper into enterprise.

SmartCompany
6 days ago
News

90-day cashflow crunch hitting ANZ SMEs: what sales teams need to know

# 90-day cashflow crunch hitting ANZ SMEs: what sales teams need to know Australian SMEs are walking into a cashflow pinch, and if you sell to them, your pipeline is about to feel it. ## The numbers 80% of Australian SMEs have experienced cashflow impacts in the last 12 months. The average SME burns through 4.2 months of negative cashflow annually. Payment terms have stretched to 55 days average, despite most invoices being written at 30. Now add fuel price lag (four to eight weeks to flow through supply chains), payday super changes (requiring $124k additional working capital for average SME), and consumer confidence at levels that correlate with delayed purchasing decisions. That is three things hitting at once. Ninety days is not much time when that happens. ## What this means for your deals Customers are not cancelling. They are delaying. Shopping harder on price. Deferring anything deferrable. If you are selling into SME, expect: - Deal cycles extending 30-60 days beyond historical norms - More stakeholders in approval chains - Heavier scrutiny on payment terms and ROI timelines - Requests for quarterly payment plans instead of annual upfront Growth often makes this worse, not better. Larger clients demand 30-60 day terms versus 7-14 days from smaller accounts. Revenue goes up, cash position goes down. ## Impact on quota and comp If your customers are experiencing cashflow pressure, expect: - Slower collections affecting company cashflow, potentially delaying commission payments - Territory adjustments as companies reprioritise enterprise over SMB - Quota relief discussions if SME segment materially underperforms For sales managers building 30-60-90 day plans: factor in extended close timelines. Historical win rates may not hold if purchasing decisions are being delayed by finance teams, not rejected by champions. ## What to watch 85% of SMEs are actively managing cashflow through expense reduction, finding new revenue streams, or raising prices. 27% of business owners have dipped into personal savings or forgone salary in the last year. If your champion starts talking about budget reviews, approval freezes, or CFO involvement where it did not exist before, that is the signal. The deal is not dead, but the timeline just changed. For AEs and sales managers forecasting Q2 and Q3: model for longer cycles. For commission forecasting, factor in collection delays if your comp is tied to cash received rather than booking. The cashflow crunch is not theoretical. It is already showing up in payment terms and approval chains. ## Bottom line Cashflow crunches do not kill deals. They delay them. Adjust your forecast, extend your pipeline coverage, and have the conversation with finance about what happens if collections slow down. The businesses that see this coming will adjust. The ones that do not will miss quota and blame the market.

SmartCompany
6 days ago
News

Meta's Muse Spark targets commerce: AI shopping hits social feeds

Meta shipped Muse Spark overnight, the first model from its superintelligence team. The play here is straightforward: commerce at scale across its entire app ecosystem. The model powers Meta AI, rolling out across Instagram, Facebook, WhatsApp and Messenger. Meta calls it "purpose-built for Meta's products", which is corporate speak for: this AI is optimised for keeping you inside our apps and buying things. ## What This Means for Sales Teams If you are running paid social or lead gen on Meta properties, the targeting and discovery mechanics are about to shift. AI-driven shopping feeds mean: - **Discovery changes**: Product recommendations get smarter. Your ad targeting needs to keep pace. - **Lead gen formats evolve**: Meta's AI can now handle more complex customer queries in-feed, potentially shortening the path from scroll to conversion. - **Attribution gets messier**: When AI surfaces your product organically versus paid placement, tracking gets complicated. For B2B teams using Meta lead ads (still one of the better performing channels for top-of-funnel), watch how AI-assisted discovery affects cost per lead and quality. Early indicators suggest AI-surfaced leads convert differently than traditional ad-driven ones. ## The Commerce Focus Meta abandoned its metaverse spend and is now betting hard on AI commerce. The company is explicit: Muse Spark is "tied to commerce and discovery inside its ecosystem." Translation: Meta wants to own the entire shopping journey, from discovery to checkout, without you leaving their apps. For sales teams, this means your product needs to be discoverable by Meta's AI, not just their ad algorithm. ## ANZ Context Meta has not disclosed ANZ-specific rollout timing or regional sales team expansion tied to Muse Spark. Worth noting: Australian e-commerce brands have historically seen strong performance on Instagram Shopping. If AI discovery improves conversion rates, expect Meta to staff up local commerce partnerships. Bottom line: Meta is repositioning AI as a shopping tool, not a search tool. If your go-to-market relies on Meta properties, your targeting strategy needs to account for AI-driven discovery, not just paid placement.

SmartCompany
7 days ago
News

SaaStr CRO: Ditch Your CRM, Follow the AI Agents Instead

## The CRM Question Just Changed A CRO at a leading AI company is hiring 250 sellers this year and asked Jason Lemkin at SaaStr which CRM to use. His answer: follow the agents. For years, the advice was simple. Use Salesforce because your VP Sales will want it. Then HubSpot came up, native marketing integration included, and by 2022 it was neck and neck with Salesforce in the startup world. SaaStr itself had Salesforce as shelfware, paying for it but barely using it. Then SaaStr went all-in on AI agents. Now Salesforce is the most important software they run. ## What 20+ AI Agents Actually Looks Like SaaStr plugged 20+ agents into Salesforce as the central hub. Here is what that stack does: - **Artisan** runs three AI SDR campaigns: ticket sales, sponsorship outreach, VIP reactivation. 15,000+ messages, 5-7% response rates. - **Monaco** handles a fourth outbound campaign, booking meetings with top AI execs from day one. - **Qualified** powers inbound AI on saastr.com. 700k+ sessions. $1M+ in closed sponsorship revenue. In one month, 71% of closed-won sponsorship deals came from AI-qualified leads. Historic average: 29-34%. - **Agentforce** handles warm lead win-backs. After SaaStr Annual, Lemkin found 1,000 people who filled out "interested in sponsoring" forms and got zero human follow-up. Agentforce got a 72% open rate and 10%+ response rate on contacts considered dead. For context: cold email averages 2-4% open rates. - **Momentum** auto-transcribes every sales call, pushes structured data into Salesforce. Reps never manually update CRM. - **Attention** layers on call intelligence, auto-populates Salesforce fields. Plus 4-5 specialised agents for email campaigns, de-anonymisation, event coordination, sponsor management. All connected to Salesforce as the data layer. Salesforce acquired Qualified. Salesforce acquired Momentum. They built Agentforce with 2,000 people. The thesis: the CRM that becomes the hub for AI agents wins. ## What This Means for Sales Orgs Lemkin is budgeting $500k for 21 AI agents in 2026. Compare that to $10k on Salesforce CRM. SaaStr is running AI-heavy teams with 6-10% response rates and 130+ booked meetings while shrinking human sales roles. The CRM decision is no longer about features or marketing integration. It is about which platform your agents can plug into without breaking. If you are hiring 250 sellers this year, ask which CRM supports the agents you need, not which one your VP Sales used at their last company. SaaStr's AI events are running at 132% growth year-over-year. AI spend is up to $2.52 trillion globally, up 44% YoY. The market is moving to agent-native sales stacks. Emerging options like Lightfield, Monaco, and Aurasell are positioning as next-gen AI agent CRMs, though public details on funding, headcount, or ANZ presence remain scarce. The playbook: follow the agents. Pick the CRM that supports them. Everything else is shelfware waiting to happen.

SaaStr
7 days ago
News

Firmus locks $725m raise at $8bn valuation, ASX IPO incoming

## The Numbers Firmus Technologies is raising US$505 million ($725 million) at an $8 billion valuation, led by New York AI investor Coatue with Nvidia participating. The round is subject to closing conditions. This comes weeks after a $100 million raise at $6 billion valuation. Total capital raised: over $16 billion across equity and debt, including a $10 billion debt facility from Blackstone. The company plans an ASX IPO later this year. This is reportedly the final private raise, though an additional $3 billion raise has been floated as part of the listing. For context: that would exceed Guzman y Gomez's 2024 IPO market cap. ## What They Actually Do Firmus builds AI data centers. Not cloud hosting, actual infrastructure: purpose-built facilities designed to train and run AI models on Nvidia chip architectures. Founded in Sydney in 2019 by Oliver Curtis, Tim Rosenfield, and Jonathan Levee, the company started in bitcoin mining before pivoting to AI infrastructure. Now Singapore-based, they are deploying thousands of GPUs across construction sites in Tasmania, Melbourne, Canberra, Sydney, and Perth. The flagship campus is in Launceston. Project Southgate, their national expansion plan, targets 1.6-1.8 gigawatts of capacity by 2028 with a $73 billion price tag. ## The Sales Angle Firmus serves hyperscale and AI-native customers globally. They joined Nvidia's DGX Cloud Lepton program in June 2025, letting developers rent infrastructure from their data center network. No public data on headcount, sales team size, or revenue. The company has not disclosed staffing plans around the IPO. ## What It Means Australia landing one of the country's largest-ever private debt deals signals serious institutional confidence in AI infrastructure plays. The IPO will test whether public markets share that conviction. For enterprise sales teams: if your prospects are building or scaling AI capabilities, they need compute. Firmus is betting Australia becomes a regional hub for that capacity.

Startup Daily
7 days ago
News

Anthropic hits $30B run-rate, passes OpenAI while spending 75% less on training

## The Numbers Anthropic: $30 billion annualised run-rate as of April 2026. OpenAI: $24 billion ($2B monthly, confirmed by the company). A year ago, Anthropic was at $1 billion ARR and OpenAI was at $6 billion. The company that most people outside B2B circles could not name two years ago just passed the company that invented the consumer AI category. Worth noting: Anthropic has roughly 5% of ChatGPT's consumer user base. Consumer scale and revenue scale are not the same thing. ## How They Got There No viral consumer app. No 900 million weekly users. Enterprise API contracts, cloud provider deals (Google Cloud, AWS), and developer adoption. Eight of the Fortune 10 are now Claude customers. Over 500 companies spend more than $1 million annually. Anthropic captured 73% of enterprise AI spend among businesses buying AI tools for the first time, according to Ramp customer data. That split was 50/50 ten weeks prior. Claude Code launched May 2025. By February 2026: $2.5 billion ARR. The product now authors 4% of all public GitHub commits. That figure has doubled in the past month. A product that did not exist 11 months ago is generating more revenue than most public SaaS companies ever will. ## Growth Rates Without Precedent Anthropic went from $1 billion ARR in December 2024 to $30 billion in April 2026. That is $14B to $30B in roughly eight weeks. Meritech reviewed IPO trajectories of over 200 public software companies and never saw a growth rate like this. Salesforce took about 20 years to reach $30 billion in annual revenue. Anthropic did it in under three years. OpenAI's trajectory: $2 billion ARR in 2023, $6 billion in 2024, $20 billion by end of 2025, $24 billion run-rate now. That is 3x per year, sustained, at scale where 3x means adding billions every quarter. ## What This Means for Sales Teams Enterprise is the engine. OpenAI confirmed enterprise now makes up over 40% of revenue, up from 30% last year, on track to reach parity with consumer by end of 2026. APIs process more than 15 billion tokens per minute. Nine million paying business users as of February. The company that started consumer-first is rapidly becoming enterprise-first. The company that was enterprise-first from day one is pulling ahead on run-rate as a result. The B2B motion gets you to durable, high-ACV revenue that compounds. Coding tools are the category. Claude Code and OpenAI's Codex are both tracking developer adoption rates that most SaaS companies never see. The AI coding category went from zero to multi-billion dollar market in under a year. If your sales team is not tracking how prospects are using AI coding tools, that is a gap. ## The Burn Neither company is profitable. OpenAI is burning approximately $17 billion in cash this year, projecting a $14 billion loss for 2026. The company has committed over $1 trillion to infrastructure and does not project positive free cash flow until 2029. Anthropic has raised over $18 billion in funding. The revenue is real, but so is the cost structure. The investors backing both companies (SoftBank, Amazon, Nvidia, Google, a16z, Lightspeed, ICONIQ) are making a specific bet: compute costs fall per unit of intelligence, revenue compounds faster than burn, and whoever owns the AI infrastructure layer owns the next decade of enterprise spend. Both companies are reportedly targeting public market debuts in 2026.

SaaStr
7 days ago
News

How Databricks sells across 30 industries without building vertical products

## The Framework Databricks sells a $4.8 billion run-rate data platform to CDOs, CTOs, and CIOs across 30+ industries. They do not build vertical products. They build what they call imperatives: the intersection of customer priorities, industry trends, and product capabilities. Most B2B teams stop at personas and ICP. Databricks goes further. Personas tell you who buys. ICP tells you which accounts fit. Neither tells you what the buyer is actually held accountable for this quarter. ## How It Works in Practice Take retail. Databricks maps three imperatives: - Personalisation and monetisation of customer experience - Employee productivity improvement - Supply chain optimisation Each imperative breaks down to business priorities (the OKRs the exec owns), use cases (specific product applications), and proof (customer references with metrics). Sales gets a one-page placemat: here is what retail CIOs care about, here is how our platform maps to it, here is the data. The product stays horizontal. What changes is the conversation entry point. You start from their world (tariffs, regulation, industry consolidation) then connect back to your capabilities. As Madelyn Mullen, Sr. Industry Solutions Manager at Databricks, put it: you are not fitting square pegs into round holes. You are starting from their problems. ## What This Means for Sales Teams If you are selling a horizontal platform into multiple industries, stop asking product to build vertical editions. Start mapping imperatives: 1. What are buyers in this vertical actually accountable for? 2. What industry trends are moving their market right now? 3. Where does your product deliver differentiated value against those priorities? The overlap is where deals happen. One caveat: SMB and enterprise imperatives are different. An SMB construction company and a global construction enterprise have different strategic priorities. You cannot use the same conversation framework across segments. ## The Comp Angle Databricks is hiring industry solutions managers and industry marketing managers to run this motion. These are not AE roles. They sit between product marketing and sales: building the frameworks, mapping the imperatives, enabling the field. Worth noting for sellers looking to move into solutions or enablement roles at platform companies. The company closed a $4+ billion Series L at $134 billion valuation in December 2024, up 34% from their August round. That kind of growth funds GTM expansion. Expect more hiring in industry-specific enablement roles over the next 12 months.

SaaStr
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