The Wire

Real-time updates from ANZ tech sales

about 2 months ago
News

AI SDR deployment takes 2 weeks minimum, says SaaStr founder

## The Setup Tax No One Mentions Jason Lemkin is running AI SDRs at SaaStr. His take: budget 2 weeks minimum for deployment, regardless of what the demo promised. The delay is not vendor slowness. Email warming takes 2 to 3 weeks if you are using dedicated IPs or domains. That is infrastructure reality, not implementation friction. Then comes the actual work: copy testing, subject line optimisation, time-of-day experiments, and segment-specific messaging. That is another 2 weeks before the agent is even live. Lemkin's team checks their agents daily. Not all day, but every day. Think of it like a 15-minute one-on-one with a rep, compressed. The "set and forget" pitch does not match deployment reality. ## Integration Overhead Once the agent is running, the questions compound. Does it flow back into Salesforce? Does it live in a silo? Do you add an inbound agent next? What about customer success? Even Monaco, which Lemkin describes as genuinely good at keeping pipeline current, took a week and a half to set up. That was their fastest deployment. The pattern holds across the market. Industry guides now cite 2 to 4 weeks for simpler setups, 4 to 6 weeks when you factor in knowledge-base prep, QA, and pilot testing. Warming alone consistently eats 2 to 3 weeks. ## Channel Preference: Chat Still Wins SaaStr runs multimodal agents: chat, voice, and video. After nearly a year of data from Amelia AI and Digital Jason on Delphi (2.75 million conversations), the result is clear. Most people still choose chat. Not voice. Not video. Chat. Lemkin saw it on a live call. The person on the other end pulled up SaaStr.ai mid-conversation, saw Amelia AI, and asked if that was him. It was the AI version. They chose to interact via chat, even though video was available. Some users prefer video because they do not want to type. A handful of attendees at SaaStr's London event said they had talked to Amelia AI before showing up. That is the value: 24/7 availability that no human can match. ## What This Means for Sales Teams Two takeaways if you are deploying AI SDRs: **The ramp is real.** Vendors who claim instant deployment will leave you troubleshooting in week three. Budget the time. Plan for it. **Build optionality.** Do not force users into one channel because that is what you built first. Let them pick: chat, voice, or video. Most will still choose chat. The AI SDR category is crowded. Tools like Autobound, Nooks, Landbase, and Monday's AI SDR offerings all compete in this space, alongside broader sales platforms adding AI prospecting. Lemkin's advice: pick a leading tool, budget the time, train it properly, and assign a strong human to manage it. That is where success comes from, not the demo. The market has moved past "launch in minutes" claims. The real work is deliverability, data hygiene, and human oversight. That work takes 2 weeks minimum, and pretending otherwise costs you 3 weeks of troubleshooting instead.

SaaStr
about 2 months ago
News

Lerer Hippeau VC: we fund crazy founders, not good companies

Ben Lerer runs Lerer Hippeau, a New York early-stage VC with nine funds and $1.5B AUM. His filter for founders: crazy beats good. "We don't fund good companies," Lerer told GTMnow. "Every dollar put into a sensible, durable business is a dollar taken away from a company chasing the power law." The logic: early-stage VC returns come from outliers, not incremental wins. A founder building a solid $50M ARR SaaS business does not move the needle on a venture fund. Lerer Hippeau wants founders whose best case is a multi-fund returner, which means filtering for risk appetite, not operational excellence. Lerer also argues he should be the worst investor at his own firm. "If I'm still the rainmaking investor at 55, the firm failed at building a team that outlasts me." The goal is to hire better investors, then build the structure for them to win deals. On investment committee process, conviction beats consensus. Deals get done when someone pounds the table, even if the rest of the team tries to talk them out of it. No groupthread votes. No comfortable middle ground. Lerer started in media, building Thrillist before it merged into Group Nine. That operator background gave him founder empathy and a network that translated into venture, with early bets on Warby Parker and Casper. He says the biggest process failure was passing on Peloton, which revealed gaps in how the firm evaluated hardware-enabled consumer plays. Current debate at the firm: AI-native 19-year-olds versus second-time founders with domain expertise. Lerer says the answer is rarely a silver bullet. Both profiles can work, depending on the market and the moat. No ANZ portfolio presence or regional expansion noted. Lerer Hippeau remains New York-focused, though the firm's thesis on founder selection and power law returns applies across geographies. Worth noting: this is a VC talking about picking founders, not a playbook for sales teams. The comp transparency and hiring specifics we usually track do not apply here. Still, the conviction-over-consensus model and the bias toward outlier outcomes mirror how top sales orgs think about territory allocation and quota design. Safe pipeline does not build a category.

Sales Hacker
about 2 months ago
News

OpenAI files for IPO: your AI stack now depends on a public company

OpenAI filed confidentially for an IPO on June 8, 2026. The company said timing is undecided and "it may be a while," but the move puts public market discipline on a company that reportedly burns through $10 billion annually on infrastructure while operating in the red. For sales teams: if you are using ChatGPT, integrated OpenAI models, or tools built on their API, your tech stack now has a landlord answering to Wall Street. That changes the risk profile. ## The numbers OpenAI raised $6.6 billion in October 2024 at $157 billion valuation, $40 billion in April 2025 at $300 billion, and $122 billion in early 2026 at $852 billion. The IPO is not about raising capital. It is about creating liquidity, optionability, and public currency for M&A. Microsoft owns 27%, the OpenAI Foundation owns 26%, employees and other investors hold the rest. That cap table complexity matters when quarterly earnings start. ## What this means for your AI strategy Vendor lock-in risk just became public company risk. Questions worth asking: - What happens to API pricing when OpenAI needs to show margin expansion? - If your SDR workflows depend on ChatGPT integrations, what is your fallback? - How much of your sales ops stack now routes through a single vendor under earnings pressure? OpenAI competing directly with Anthropic, Microsoft, Google, Amazon, and Nvidia. Anthropic also started its IPO process last week. The AI model layer is consolidating fast, and the companies providing it are all racing toward profitability under public scrutiny. ## The sales angle ChatGPT launched in November 2022 and became the fastest-growing consumer app in history. Public sources do not show a named CRO or ANZ headcount, but the company is working with Goldman Sachs and Morgan Stanley on the listing. For ANZ sales teams building on OpenAI: you are building on infrastructure controlled by a company that has not yet proven it can turn revenue into profit at scale. That is fine if you have a Plan B. If you do not, this IPO filing is your reminder to build one. Uncapped commission on your AI strategy assumes 100% vendor uptime and stable pricing. Historical data on public company pivots says otherwise.

SmartCompany
about 2 months ago
News

SaaStr AI: Six Verticals Agreed the AI Is Now Commodity, Data Is Moat

## The Takeaway Six closing sessions at SaaStr AI 2026 (12,500+ attendees, San Mateo) covered commerce, revenue ops, payroll compliance, and fintech. None sold the same product. All reached the same conclusion: the AI became commodity, data and guardrails are the moat. ## What That Means for Sales If you are selling vertical SaaS with AI features, your prospects already assume you have the AI. They are buying the proprietary data layer, the compliance framework, and the workflow that does not break when a rep enters bad data. That changes the discovery questions and the demo structure. Shoplazza (commerce platform, 650,000 merchants) rebuilt their entire stack AI-first rather than bolt features onto the old product. Their CRO Adam Modsley said everyone has the same tools now: Lovable, Claude, Vercel. Having the tools does not make you successful, the data does. They warned that usage-based billing is not optional anymore. One founder's AI token deal ran out in month four, got the real bill, and realized they were losing money on every customer. Nue (Salesforce-native CPQ-to-billing) demoed three quote variations in seconds, a task that normally costs a rep two hours. The AI is deterministic: same inputs, same output every time. Guardrails live in the pricing engine, not the prompt. Ask for a 76% discount and it caps at 55%. Quote-to-cash has to be end to end, down to showing the customer their exact first invoice at quote time. Papaya Global (payroll compliance, 160 countries) built Papaya 1 so clients stop asking ChatGPT a German termination question at 2am and acting on a confident wrong answer that can cost $250,000. They gave the same Brazilian employment contract to Claude and ChatGPT. Both were confident, both gave different answers, neither got it fully right. They built 22 compliance rules one at a time, added a second AI to check the first, and shipped a kill switch: if accuracy drops below threshold in any country, they turn that country off. The agent worked in four weeks, earning enough trust to put the company's name on it took four months. Reevo (revenue ops) automated the 70 to 80 percent of a seller's day that goes to admin: research, prep, notes, follow-ups, CRM. The deal-progression agent reads the CRM, emails, and call transcripts, cites the evidence (an unanswered "I need to run this by finance" comment), and drafts the follow-up. Automate the admin, not the relationship. ## The Pattern Across all six sessions: lead with the outcome, not the model. Build guardrails before features. Turn every failure into a rule. Meet users where they already work. The data is the moat. For sales teams, that means the pitch is shifting from "we have AI" to "our AI is trained on your vertical's data and will not recommend a discount structure that violates your comp plan." Generic AI gets you generic results. Vertical data and deterministic workflows are what close the deal now.

SaaStr
about 2 months ago
News

Startmate lands $8M to back women founders, typical deal $120k at $1.5M valuation

Startmate has secured an $8 million commitment from the Minderoo Foundation to expand capital access for women founders in the ANZ startup ecosystem. The Australia-based accelerator typically invests $120,000 into early-stage companies at a $1.5 million post-money valuation for first-time fundraisers. Its portfolio now spans more than $1 billion across all continents, positioning it as one of the better-known seed platforms in the region. The new capital will support Startmate's existing momentum: 52% of founders raise $1 million to $4 million directly after completing the accelerator program. The platform's Forever Fund has already written 19 follow-on checks ranging from $25,000 to $375,000, indicating increasing ability to support alumni through subsequent rounds. ## The market reality Female-founded startups receive just 2% of venture capital funding in Australia, despite research showing companies established by women achieve higher returns on investment. Worth noting: the data and the money remain misaligned. Remy Tucker's experience tracks with this. Her company On The House, which installs free feminine hygiene product dispensers funded by advertising, completed Startmate's program and subsequently raised a $1.7 million seed round. The company now operates 55 machines across Sydney, Melbourne, Brisbane and the Gold Coast with a team of five. Tucker started the business after working as a student midwife and noticing recurring period inequity. "Women were leaving the hospital asking if they could take products with them," she said. The solution: billboard advertising in bathrooms funding free hygiene products. ## What this means Startmate operates as a community-driven seed fund and accelerator focused on network access, mentorship and early capital rather than a traditional sales motion. The platform does not list a sales organisation, CRO, or VP Sales in public sources, which is consistent with it being a venture platform rather than a software company. The $8 million commitment will likely deepen Startmate's visibility in diversity-focused venture investing and expand its ability to write follow-on checks for women-led companies. The accelerator model remains the same: early capital, strong network access, and a track record of helping founders close their next round.

SmartCompany
about 2 months ago
News

Four ANZ startups raised $87M: quantum, fintech, AI hiring implications

## The Numbers Four Australian startups closed $87.3M this week: - **Silicon Quantum Computing (SQC):** $40M from the National Reconstruction Fund - **Dentroid, Earlytrade, ReSmart:** $47.3M combined (individual amounts not disclosed) SQC's raise brings federal government investment to $60M in three months, with $40M equity giving them roughly one-third ownership. ## What It Means for Sales Teams Deep tech and quantum computing typically hire engineers and scientists first, sales roles later. SQC is building quantum chip manufacturing capability, not a SaaS go-to-market motion. Expect technical pre-sales and partnerships roles before field AEs. For context: Australian startups raised $5.1B across 390 deals in 2025, the third-largest year on record. AI, fintech, biotech and climate tech drove most capital. That suggests buyers are still writing cheques, but sales cycles remain long for infrastructure plays. ## Broader ANZ Funding Context Australian startups raised $4B across 414 deals in 2024. Half the capital came from eight deals above $100M. The market still concentrates capital in scale-up winners (SafetyCulture, Deputy, InDebted) while supporting high volumes of smaller rounds. For sales professionals: large funding rounds at mature companies usually mean quota expansion and territory splits. Early rounds at deep tech startups mean long sales cycles and technical selling. Know the difference before you take the call from the recruiter. ## The Sales Hiring Reality Quantum computing, dental AI, trade finance and recycling tech are not hiring SDR pods. These are 12-month enterprise sales cycles with technical buying committees. If you are an AE looking for fast ramp and monthly quota, these are not your plays. Watch for follow-on rounds at B2B SaaS companies in the cohort. That is where the AE, SDR and CSM hiring happens. These four? Probably adding one enterprise AE each, maybe a partnerships lead. Not a sales floor build-out. ## Bottom Line Healthy funding week for ANZ, but most of it went to categories that hire technical talent before sales talent. If you are tracking which raises lead to go-to-market hiring, focus on B2B SaaS and fintech follow-ons, not quantum computing seed rounds.

SmartCompany
about 2 months ago
News

Minderoo Foundation backs Startmate with $8m over four years

## Minderoo Foundation backs Startmate with $8m over four years Andrew and Nicola Forrest's Minderoo Foundation is backing Australian accelerator Startmate with $8 million over four years, structured as $2 million annually. The funding targets women founders. Minderoo, with an endowment around $7.6 billion after the Forrests donated $5 billion in Fortescue shares, is operating as a strategic investor rather than traditional VC. This fits their pattern of funding ecosystem-building initiatives in ANZ. ### The Startmate model Startmate runs two accelerator cohorts per year. Standard investment: $120,000 for 8% equity. Their backing of companies with at least one female co-founder sits at 43%, nearly double the industry average of 24%. Last year, 51% of Startmate's accelerator capital went to women-led startups (defined as at least one female co-founder with meaningful equity). Another 33% went to all-women founding teams. Applications from women-led startups have grown from 100 (20% of total) in 2019 to nearly 600 (43% of total) in 2025. ### Why this matters Minderoo CEO John Hartman: "Research shows female founders are consistently underfunded and operating with fewer resources globally. That hasn't changed, despite strong performance from women-led teams and clear evidence they deliver results, often outperforming their male peers." For sales professionals watching ANZ startup ecosystem funding: this is institutional capital backing pipeline infrastructure, not individual deal flow. Startmate portfolio companies become future hiring opportunities, particularly for early-stage sales hires. Startmate CEO Phoebe Pincus says the partnership will build on existing momentum. Worth noting: the accelerator model here is founder-focused, not a large enterprise sales motion. The downstream implication is more startups scaling, which means more AE and SDR roles opening up across the portfolio over the next 12-24 months. No specific hiring plans announced yet, but accelerators at this funding level typically expand operations teams, including outreach and portfolio support roles.

Startup Daily
2 months ago
News

Shopify hits $13B revenue at age 20, growing 34%

## The Numbers Shopify turned 20 and shipped its strongest quarter since the pandemic surge. Q1 revenue hit $3.17B, up 34% year over year. GMV crossed $100B in a single quarter for the first time, up 35%. Free cash flow margin held at 15%. Most software companies decelerate at this scale. Shopify accelerated. Growth rate improved from 27% a year ago to 34% now, at a $13B+ run rate. That does not happen by accident. ## The Revenue Mix Shifted Subscriptions (the monthly merchant plans) grew 21% to $750M. That is 24% of total revenue. Merchant solutions, mostly payments and lending, grew 39% and now makes up 76% of revenue. Shopify makes roughly 3x more when merchants succeed than it does selling them software. The subscription is the wedge. The business is taking a cut of $100B+ in commerce flowing through the platform. Shopify Payments alone processed $67B in GMV, up 41%, handling 67% of all platform volume. Look only at MRR and you would think this was a 16% grower. MRR hit $212M, up 16%. Total revenue grew 34%, more than double the MRR growth rate. The gap is success-based revenue: payments, Shop Pay, Capital, the revenue that scales with merchant volume rather than merchant count. ## Why This Matters for B2B Sales Shopify figured out a decade ago what many SaaS companies are learning now: the highest-growth revenue is usage-based and success-based, not seat-based. The model where you grow when your customer grows is the one compounding fastest. For go-to-market teams, this is the playbook. Land with subscription, expand with usage. Nearly 90% of Q1 revenue came from merchants who have been on the platform more than a year. That is expansion revenue, not new logo hunting. Shopify's commercial motion is platform-led, not classic enterprise field sales. Merchant success, partner ecosystem, and payment take-rates drive growth. That structure scales differently than a traditional SaaS sales org, but the numbers show it works at $13B. The company was founded in 2004 by Tobi Lütke, Daniel Weinand, and Scott Lake after building an online snowboard shop. Twenty years later, it is still accelerating. Durable does not have to mean slow.

SaaStr
2 months ago
News

Earlytrade raises $14.2M, US revenue up 7x since 2024 launch

**Earlytrade closed $14.2 million** led by S3 Ventures and Brick & Mortar Ventures. The construction fintech, founded in Sydney in 2018, runs a payments marketplace for contractors and subcontractors. The round brings total funding to $35.5 million. Previous raises: $12.5 million Series A in September 2022, $8.4 million seed in 2019. ## US revenue up 7x Earlytrade launched in the US in 2024. Since then, US revenue grew sevenfold, the company says. They now claim 211,000 subcontractors on the platform and have processed over US$3 billion in early payments globally. The fresh capital goes toward US expansion and building agentic AI into the payments workflow. Worth noting: no detail yet on what "agentic AI" actually means in practice or how it changes the product. ## What this means for hiring Earlytrade has not announced headcount plans tied to this raise. Construction fintech sits in an active funding segment: competitors like Trayd (payroll/workforce software) and Grand (AI trade credit) have raised capital in the past 18 months. That usually signals commercial hiring, but Earlytrade has not confirmed numbers, roles, or locations. For context, a $14.2 million round at this stage typically funds 8 to 12 commercial hires over 12 to 18 months, split between AEs, SDRs, and customer success. No confirmation yet on ANZ versus US hiring split. ## Open questions Earlytrade has not disclosed: current ARR, team size, sales leadership, or whether the US expansion means closing ANZ roles or keeping dual operations. Founders Guy Saxelby and Piers Symons remain at the company. For sales professionals watching construction tech: the category is getting capital, but comp data and hiring specifics remain sparse. If you are tracking construction fintech opportunities, this is one to monitor for role postings over the next quarter.

SmartCompany
2 months ago
News

Why B2B vendors pay $1 per AI call while customers pay $20/month

## The Margin Squeeze Nobody Talks About Here is the problem: when your B2B product does something genuinely complex with AI, you might be paying $1.00 or more per API call. Your customer can do roughly the same thing in Claude for a fraction of a cent, amortised over their $20/month subscription. SaaStr CEO Jason Lemkin laid out the actual numbers this week. A simple chatbot reply on Haiku costs about $0.004. Fine. But a moderately complex document analysis (20,000 input tokens, 2,000 output on Sonnet) runs $0.09 per call. A sophisticated 100-page analysis hits $0.375. Run that on Opus 4.6, the model that actually impresses a CFO, and you are at $0.625 per call. Add extended thinking and you regularly clear $1.00. Meanwhile, a Claude Pro subscriber at $20/month can run hundreds of those same complex analyses per day. Rough math: 10 complex document analyses per day is 300 per month at $20 flat, or about $0.067 per analysis. You just paid $0.375 to $1.25 for the same call. ## What This Means for Enterprise Software To build a profitable business, a $1.00 API call needs to become a $3 to $5 per-query charge once you factor in infrastructure, engineering, support, and margin. Or it gets buried in a monthly subscription where you are quietly hoping users do not run complex queries too often. Neither option feels great when your customer's other browser tab is open to claude.ai. SaaStr runs 12+ internal and external AI apps. Most use under $200/month total in API tokens. But two of their most complex apps cost $0.30 to $1.00 per usage. For a startup with high ACV and low margin sensitivity, that works. For a B2B leader at $100M+ ARR with thousands of customers running queries at volume, the math gets uncomfortable fast. ## Why AI Features Feel Thin The market pressure runs one direction: toward using cheaper models and simpler workflows. That is why so many AI features in enterprise software feel mediocre compared to what you can do in Claude directly. It is not that engineering teams are bad. It is that the cost of making features genuinely great does not fit the pricing model they have already committed to. McKinsey notes that B2B sales leaders are using AI for opportunity identification and value-based pricing, but competitive advantage depends on using data and AI to improve decision-making, not just adding AI features. The bottlenecks are leadership alignment, data quality, and organisational change, not model access. For sales leaders evaluating AI tools: ask what model is running under the hood, what the token usage looks like for your use case, and whether the vendor is paying $0.004 or $1.00 per call. That will tell you whether you are getting genuinely sophisticated AI or a thin wrapper that will feel outdated in six months.

SaaStr
2 months ago
News

AI vendors grow without big sales teams: Anthropic lands 54% of enterprise logos self-serve

# Sales is the caboose at AI leaders, not the engine Anthropic landed 54% of new enterprise logos through self-serve in 2025. They built the motion as an MVP in January, shipped it in February, and it was already closing more than half of enterprise deals. The sales team is real. It matters. But it is catching demand the product generated, not manufacturing pipeline. When growth runs at 300% to 500%, reps process a firehose instead of filling an empty funnel. That is the new reality at frontier AI vendors. OpenAI, Anthropic, and the other AI platform companies all have sales teams. No one is saying the function is dead. But the math changed. Before AI, great execution could take a B2B company from 80% growth to 120% growth. That gap mattered. The best sales org was often the category winner. Now the spread is 500% versus 15%. And when the gap is that wide, the sales team is not creating it. The demand environment is. If you are growing 500%, you are in the right category at the right time. If you are at 15%, no comp plan fixes that. ICONIQ's 2026 GTM benchmarks show high AI adopters generating $640k of net new revenue per GTM head versus $370k for everyone else, a 73% gap. In post-sales it was wider: $1.1m versus $600k per head. That is not a story about better reps. It is a story about which side of the AI demand line a company sits on. ## What this means for sales teams Sales still matters in both worlds. At 500% growth you need a team that can scale fast enough to capture demand without breaking. At 15% you need discipline to defend the base and win every contested deal. Both are hard. But in neither case is sales setting the trajectory. The trajectory was set before the reps picked up the phone. That changes hiring priorities, team structure, and what quota attainment actually measures. AI vendors are building around product velocity and self-serve adoption first, enterprise sales motion second. Columbia's GTM analysis says firms are shifting toward GTM engineers, AI agents, and leaner lead-generation functions. Challenger's research shows AI is improving forecast accuracy, lead scoring, pipeline analysis, and coaching, but the human seller is focusing on complex deals and retention, not top-of-funnel volume. For sales professionals, the split is clear: you are either working harder than ever to process 10x demand, or you are in slow-growth territory where every deal is contested. The middle is gone. And that means the skills that matter, the roles that exist, and the comp structures that make sense are all changing. Sales is not dead. It is just not the engine anymore. At least not at the companies growing fastest.

SaaStr
2 months ago
News

Labor considers startup CGT carve-out after founder backlash on tax changes

The federal government is considering a carve-out for startups from its capital gains tax reforms, according to the Sydney Morning Herald. Treasurer Jim Chalmers is examining options that would let qualifying startups keep the existing 50% CGT discount instead of moving to the proposed inflation-indexed model. The shift comes after sustained backlash from founders, investors, and venture capital groups who argued the changes would materially increase tax on exits and deter investment in the sector. ## What's changing Labor's budget proposal would replace the 50% capital gains tax discount with cost-based indexation for assets held longer than 12 months, starting 1 July 2027. The plan includes a minimum 30% tax on real gains. Some existing small-business CGT concessions would remain. ## The pushback ABC reported the government was caught off guard by the response from startup founders and small business owners. Industry Minister Tim Ayres did not rule out future changes, saying the treasurer was in talks with the startup community. Financial Review coverage also noted growing unrest on the Labor backbench about exempting startup investment, suggesting the issue has become politically sensitive inside the party. ## The design challenge Ministers are still working through how any startup concession would be structured. The core challenge: defining what qualifies as an innovative startup for tax purposes without creating exploitable loopholes. Options reportedly include using existing eligibility frameworks from startup incentive programs and employee share scheme concessions as templates. ## Why it matters For sales professionals at startups or considering startup roles, this matters for equity compensation. CGT treatment directly affects the after-tax value of share options on exit. If your startup sells and you have vested options, the tax bill on that gain could change significantly depending on how this policy lands. The debate also signals broader market uncertainty for the ANZ startup sector. Founders are watching comp structures and exit planning closely. VCs are reassessing risk models. That uncertainty flows through to hiring plans and OTE structures for sales teams. No timeline yet on when Treasury will land on a final design or whether the carve-out will actually ship.

SmartCompany
2 months ago
News

Australia Post lifts parcel prices 4.95%, small businesses passing costs through

Australia Post is raising parcel delivery prices by an average 4.95% from July 1, forcing small businesses to pass shipping costs through to customers. MyPost Business rates, MyPost Business Pickup, and retail parcel services will all increase. Contract customers, typically businesses shipping hundreds to thousands of parcels monthly, will see rates rise 4.25%. The government-owned business cited global fuel market disruptions and Middle East tensions as drivers behind the annual price review. Australia Post operates 4,118 outlets nationally and is wholly owned by the Australian Government. **Market context matters here.** Australia Post acquired last-mile delivery platform Rendr in April 2026, aiming to expand same-day delivery coverage to 90% of Australia's population. The company has made at least three acquisitions recently, including an earlier investment in Shiperoo in March 2025. Translation: they are defending parcel market share against private logistics providers while also needing to maintain margins. Small retailers are not happy. Gold Coast baby goods shop Tiny Trader posted on Instagram that it has historically absorbed nearly a third of shipping costs under flat-rate postage. "Until now, we've absorbed a large portion of shipping costs ourselves," the business wrote, signalling that practice is ending. **Why this matters for sales teams:** If you are selling to retailers or ecommerce businesses, shipping cost inflation is now a real line item pressure. Customer acquisition costs stay flat or rise, but so do fulfilment costs. That squeezes margins and makes budget conversations harder. Worth flagging in discovery if logistics spend is material to your prospect's P&L. For logistics software or fulfilment tech sellers, this is fuel. Australia Post's push into same-day delivery through acquisition suggests the market is moving toward speed and flexibility, not just cost. If your product helps businesses optimise carrier mix or automate shipping decisions, this pricing change is a conversation starter. Australia Post is Melbourne-headquartered and self-funded, operating under both commercial and community service obligations. The tension between those two mandates shows up in pricing decisions like this one.

SmartCompany
2 months ago
News

AI-forward GTM teams run 43% leaner, double revenue per rep: ICONIQ data

# AI-forward GTM teams run 43% leaner, double revenue per rep: ICONIQ data ICONIQ Growth's January 2026 State of Go-to-Market report surveyed 150+ B2B GTM executives and combined it with portfolio operating data. The headline: companies embedding AI across revenue functions are running significantly leaner teams while generating roughly double the net new revenue per FTE. ## The headcount gap is structural At $10M to $25M ARR, AI-forward companies run about 20 GTM FTEs. Lower-adoption peers at the same revenue run 35. That is a 43% difference. The gap holds up market. At $25M to $100M it is roughly 45 FTEs versus 65. At $100M to $250M it is 125 versus 165. At $250M to $500M it is 275 versus 350. Median GTM headcount growth at $100M+ companies is 9% in 2026 versus 25 to 40% five years ago. The shift is not just tooling: revenue orgs are being redesigned around AI, hiring more builders (engineers who understand revenue workflows) rather than adding more operators. ## Pipeline is now sales-sourced Sales-sourced pipeline makes up 62% of total pipeline. Marketing-sourced sits at 19%. If your forecast assumes marketing fills most of the top of the funnel, that assumption no longer matches the data. ## Conversion is the problem, not volume Demo-to-close rates have fallen 5 to 10 points. Sales cycles have lengthened. Buyers are still entering the funnel at similar rates. The decline is in closing. The driver is buyer caution: in a fast-changing market, choosing the wrong vendor is costly, so buyers are evaluating longer and harder. More leads will not fix a conversion problem. Invest in the close: ROI cases, proof-of-value, faster time to result. ## POC converts at 50%, up 14 points YoY Conversion from POC or free trial now runs around 50%, roughly double the SQL-to-close rate. Most companies still run POCs informally, without success criteria, a timeline, or an owner. Make the POC a defined stage with measurable success criteria. ## Comp is shifting toward durable revenue Net New Recurring Revenue as a component of AE comp rose from 25% of companies in 2025 to 33% in 2026, an 8-point move and the largest single-year change ICONIQ tracked. Net Dollar Retention as an AE comp metric rose another 5 points. Median NRR now sits in the 108% to 110% range, while the top quartile holds above 123%. If a durable, expanding account pays a rep the same as a deal that churns in a year, the comp plan is misaligned with where the value is. The leaner teams also attain quota at higher rates: 67% of ramped AEs hit quota at AI-forward companies versus 59% elsewhere. Source: ICONIQ State of Go-to-Market 2026, January 2026 survey of 150+ B2B GTM executives.

SaaStr
2 months ago
News

AI agents bypass Marketo, Outreach, Salesloft: why automation tools face existential risk

## The Tools Agents Don't Need SaaStr ran an experiment: ask Claude, OpenAI, and Gemini which APIs work best for agentic workflows. Stripe topped the list. No surprise there. What caught attention: when asked about marketing automation and sales engagement, all three models said the same thing. Marketo, Outreach, and Salesloft have no use in an agent-driven workflow. The reasoning: an agent crafts and sends better emails itself. It does not need a sequence builder, a template library, or a cadence tool. These platforms exist because humans cannot manually send thousands of personalized emails or track hundreds of follow-ups. Agents have no such constraint. They generate each message in real time, pull context from the CRM, and execute the cadence natively. The entire productivity layer disappears. ## What This Means for Sales Stacks SaaStr's own numbers show the shift. Salesforce spend went from $12k to $22k annually. Seats dropped from 10 to 2 plus one agent. Token consumption is up because agents run constantly. Meanwhile, the Marketo equivalent got cut entirely. Their AI VP of Marketing writes campaigns, segments audiences, sends emails, and measures results without touching a marketing automation platform. The pattern extends across categories: **Marketing automation:** Marketo, HubSpot enterprise, Eloqua. Built to let marketers template communications at scale. Agents generate each email fresh with full context. **Sales engagement:** Outreach, Salesloft. Built to run sequences because SDRs cannot track 400 cadences manually. Agents run cadences natively and generate each touch based on actual prospect behavior. **Conversation intelligence:** Gong, Chorus. Built to extract insights from call transcripts for humans to act on. Agents ingest transcripts directly and act without a dashboard layer. **Project management:** Atlassian (Jira, Confluence), Monday, Asana. Built for human coordination. Agents have memory and context windows. They do not need Kanban boards or wikis. Atlassian, the $4.4 billion Sydney-headquartered company, sits in an interesting position. Its tools are built for human coordination in software development and IT service management. Strong market position, but fundamentally designed around biological constraints agents do not have. ## The API-Native Advantage The reason some platforms work for agents while others do not comes down to architecture. Stripe exposes clean APIs with structured data and predictable workflows. Legacy B2B tools like Marketo, Outreach, and Atlassian were built around human-driven processes: configuration, manual handoffs, UI-centric usage. That makes them less agent-ready. Agents favor API-native workflows over platforms that require a human to click through screens. When the product itself is the workaround for human limitations, agents bypass the product entirely. ## The Ratio That Matters Gartner data shows vendor consolidation taking 30-50% of new AI spend. The first cuts: tools that exist purely as productivity layers for humans. Even if agents only handle 30% of these workflows by end of 2026, that is 30% of the customer base with no native need for the product category. This is not about agents using the same tools faster. This is about entire categories becoming redundant because the constraint they solved no longer exists. The sales engagement platform was a workaround for humans who could not personalize at scale. The agent does not need the workaround. ## ANZ Context For Australian sales teams evaluating AI tools: watch what gets consolidated first. Marketing automation and sales engagement platforms are high-risk renewal categories. The comp model for SDRs and AEs may shift as outbound volume becomes less about human touches and more about agent-generated quality. Atlassian remains the standout ANZ company in this conversation. Founded in Sydney, major global enterprise footprint, but the core products are still built around human coordination. The question for any ANZ tech employer in the collaboration or productivity space: does your product exist because humans have constraints, or because the problem itself requires human judgment? The agents have an answer. Some categories stay. Some become features inside broader AI systems. Some just get cut.

SaaStr
2 months ago
News

Startup Year axed: $15M program drew eight students, spent $80k

## Program cut after massive miss on targets The federal government's Startup Year program is dead. Eight students signed up. The budget was $15.4 million over four years, designed to support 2,000 loans per year. Total funding released: $80,000. Department of Education officials confirmed the numbers at Senate Estimates on Friday. The program was discontinued in May's federal budget. ## What the program promised Startup Year offered HELP-style loans for students and recent graduates joining university-run accelerator programs. Participants could access up to two loans of $11,800 each, repayable through the tax system like HECS debt. Labor first floated the idea in 2016, revived it in Anthony Albanese's 2021 budget reply, then allocated $15.4M after forming government in 2022. Years of consultation and legislative changes followed. The gap between plan (2,000 loans per year) and reality (eight total) suggests the problem was not awareness or legislation. Universities were supposed to deliver accredited accelerator programs. Either they did not build them, students did not want them, or both. ## Why this matters for sales hiring Startup accelerators are a common talent pipeline for early-stage companies building SDR and AE teams. When accelerators do not launch or attract participants, that pipeline stays dry. The university angle matters too. Campus recruiting and graduate programs are standard plays for building sales teams in ANZ tech. If university-backed startup programs cannot get traction, companies relying on that channel need other sourcing strategies. Worth noting: $15M is not massive funding by startup standards, but it is real budget. The 0.4% uptake rate (eight participants versus 2,000 target) is a data point for anyone building programs that assume students will trade future tax liability for current opportunity. No word yet on whether the eight participants who did sign up will keep their funding or face clawback.

SmartCompany
2 months ago
News

Nine writes off $49M Pedestrian investment, hands it to Vinyl for nothing

## The Numbers Nine Entertainment exited Pedestrian Group for nominal consideration. Total investment: $49 million across two acquisitions (60% stake for $9.3M in 2015, remaining 40% for $39.3M in 2018). Peak valuation: $100 million. Current valuation: effectively zero. Vinyl Group (ASX:VNL) is acquiring 100% of the youth media brand with no cash, debt, scrip, or ongoing royalties. Nine's ASX filing confirms the transaction followed unsolicited buyer enquiries, not a planned divestment. ## What Happened Pedestrian, founded in 2005, became part of Nine's digital media strategy during the traditional media pivot to online audiences. The business expanded through licensing deals (Business Insider, Lifehacker, Kotaku, Gizmodo, Vice, Refinery 29) and launched Pedestrian Television on 9Now as a youth-focused VOD channel. The cracks showed in 2022 when Business Insider's licence ended. A pivot to web3 content (The Chainsaw) failed as crypto imploded. By mid-2024, CEO Matt Rowley departed alongside multiple redundancies. Licensing deals for Lifehacker, Kotaku, Gizmodo, Vice, and Refinery 29 ended. Only PopSugar remained. Nine, which has collapsed from a $4 billion valuation to $1.18 billion in seven years, is offloading assets across the board: Domain sold, ACM regional print divested, radio stations and regional TV network also gone. ## Why It Matters This is a textbook case study in failed digital media investment. Nine bet $49 million on youth audience growth and digital advertising revenue. The hypothesis: build reach, monetise through programmatic and branded content deals. The reality: licensing costs, restructuring cycles, and a shrinking digital ad market. For sales teams in media or publishing, the lesson is clear: audience does not always equal revenue. Pedestrian had brand recognition and traffic, but could not convert that into sustainable margins. The web3 pivot showed desperation, not strategy. Vinyl is picking up a known brand for nothing, which either means they see capital-efficient upside in the audience, or they are betting on cost-cutting and cross-platform synergies with their existing publishing portfolio. Either way, Nine walked away from the entire investment rather than continue funding losses. Pedestrian co-founder Chris Wirasinha now runs adtech startup Linkby, which raised a $23M Series B in 2024. He got out early.

Startup Daily
2 months ago
News

Goterra enters administration after failing to raise growth capital

## Goterra enters administration after failing to raise growth capital Canberra-based ag-tech startup Goterra has entered voluntary administration after failing to secure the investment needed to scale operations. Teneo's Daniel Walley and Martin Ford were appointed administrators on Wednesday. The company is pursuing a going concern sale. ### The business model Founded in 2016 by former sheep farmer Olympia Yarger, Goterra uses modular, container-based systems housing black soldier fly larvae to process food waste on-site. The output: insect protein and soil conditioner. Customers include farms, restaurants, hotels, supermarkets, hospitals, and local councils across Australia. The pitch was decentralised waste processing with lower emissions and costs than landfill. The company raised an $8 million Series A co-led by Grok Ventures (Mike Cannon-Brookes' VC fund) and Tenacious Ventures. ### What went wrong In a statement to SmartCompany, a Goterra representative said the company has "working technology, contracted customers, and operating licences that are genuinely difficult to replicate." "This was not a product failure or a market failure," they said. "We ran out of runway while pursuing the investment we needed to scale." Worth noting: the gap between contracted customers and securing growth capital. That suggests the business was selling but could not close the funding needed to expand fast enough. ### What it means For commercial teams in climate-tech and ag-tech: contracted customers do not guarantee your next round. Goterra had technology, licences, and revenue. Still entered administration. Administrators are looking for a buyer to keep the business operating. If they find one, this becomes an acqui-hire story. If not, the contracted customers and operating licences get unwound. No public information on current sales team size or commercial leadership. The job was likely operations-heavy given the on-site processing model.

SmartCompany
2 months ago
News

Aurasell CEO: His old GTM stack cost $3M, 22 tools, 11 ops people

## The Stack Audit No One Wants to Run Jason Eubanks, CEO of Aurasell, skipped the AI vision slides at SaaStr AI 2026. He showed his old GTM stack from Harness instead: 22 products, $3M per year in software fees, 11 ops people to keep it standing. Those 11 were not driving revenue. They were stitching integrations, patching workflows, reconciling data across silos. Reps worked inside 10 to 12 products daily. They spent 24 to 30% of their time actually selling. The rest went to context switching, manual research, prep, follow-up, internal busywork. You are paying quota-carrying salaries for that. Eubanks calls it Project X-Ray: the audit he ran mid-COVID when his board asked him to cut burn. The finding that stuck was tool sprawl killing productivity, not headcount. ## Why Bolting Agents Onto Legacy Tools Fails Every niche tool brings its own database. That silo might sync with your CRM at the field level, but the context stays trapped. Conversations, activities, signals: all siloed. Agents need that context to act intelligently. Without it, they guess. Legacy vendors bolting agents onto fragmented data get what Eubanks calls "agentic thrash": low-quality automation, agents stepping over each other, costs going up. Aurasell's play: one unified data layer first, then agents. Structured and unstructured data in one place. 900M contacts, 85M accounts, auto-enriched. Conversational context across every channel feeding one graph, not a dozen silos. Automation layer on top, some agents prebuilt, others you build in natural language. The deployment is smart: run it as your AI-native CRM and migrate off legacy tools, or lay it on top of Salesforce or HubSpot with bidirectional sync. Rip and replace is optional. ## The Proof: $2.7M Closed in 41 Days Aurasell showed a new rep's first 41 days, ending in a $2.7M closed deal. Day one: territory already built and prioritized by ICP. No spreadsheets, no other tools. AI columns ran custom research at scale. Which accounts hired a new CRO this year? One prompt, pulled from reputable sources. Contacts pulled and ranked by propensity to engage, auto-enriched with email and phone. Sequences built by prompt, unique messages for every account and persona off the custom research. Cold call blocks surfaced with context attached: recent events, discovery questions, talk tracks. The company raised $30M seed from N47, Menlo Ventures, and Unusual Ventures. Co-founded by Eubanks and CTO Srinivas Bandi, both with prior runs at VMware, Twilio, Nutanix, Meraki, and Harness. The platform has logged 41 million agent runs. No ANZ office or local traction visible yet. Offices in San Francisco Bay Area, Bangalore, and London. ## What It Means for Sales Ops Stack consolidation is not new talk. What is different: Eubanks is not pitching a better dashboard. He is pitching one data layer that makes agents useful instead of adding more noise to a fragmented stack. The math is simple. If your reps are selling 25% of the time and working inside 10 tools daily, you have an ops problem masquerading as a headcount problem. The question is whether collapsing the stack into one AI-native platform actually works at scale, or if you are just trading 22 vendors for one very expensive vendor with a better pitch deck. Worth watching: does this play as consolidation theatre, or do the agent runs translate into quota attainment? The $30M seed says investors think the latter. The proof will be in customer retention and expansion, not demo walkthroughs.

SaaStr
2 months ago
News

Anthropic, OpenAI hiring sales faster than engineering: 20% of roles are GTM

## The numbers tell the story Anthroptic and OpenAI are hiring sales roles faster than any other function. At both companies, roughly 20% of open positions are in go-to-market: account executives, solutions engineers, partnerships, revenue operations. This is not a vanity hire. Anthropic's ARR sits at $47 billion, up from $9 billion six months ago. Enterprise customers account for 80% of that revenue. More than 1,000 businesses now spend over $1 million annually with Anthropic, double the count from two months earlier. OpenAI is planning to nearly double headcount this year, from 4,500 to 8,000 employees. Enterprise account executives are among the most aggressively recruited roles. ## Self-serve hits a ceiling The driver is deal size. A $1 million annual contract does not close through a checkout page. It closes through an AE who can navigate a multi-stakeholder buying committee, a solutions architect who maps the model to the customer's technical stack, and a CSM protecting the renewal. Anthroptic recently posted a Head of GTM Systems role. The job description says the company is scaling toward "multi-billion dollar revenue organisation" and needs systems for CRM, CPQ, finance, billing, order management, and revenue recognition. That is enterprise sales infrastructure, not startup motion. Other openings include GTM Strategy & Operations roles for Startups and Industry/EMEA segments. The company is hiring sales ops and planning, not just quota-carrying reps. ## What this means for sales professionals Three role types are prominent: **Forward-deployed engineers and solutions architects:** Technical sellers who embed in customer environments and ship integrations. Not pitch-deck AEs who present and leave. **Enterprise account executives:** Multi-stakeholder deal runners. The companies building the most sophisticated AI products in the world still need humans to close enterprise logos. **Revenue operations:** CRM admins, sales ops, systems architects. The back-office that makes a high-velocity sales org function. Anthroptic filed confidentially for a U.S. IPO on 1 June, days after a $65 billion round pushed valuation to $965 billion. A company that still leads with AI safety is walking into public markets on the back of an enterprise sales engine it has been building for months. Comp data for these roles is not public yet. Worth watching: if Anthropic and OpenAI are competing for the same enterprise AE talent as Salesforce, Google Cloud, and AWS, they will need to match or beat those OTE packages. That will set a new baseline for AI startup sales comp.

Sales Hacker
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