The Wire

Real-time updates from ANZ tech sales

4 months ago
News

Marketo breaks core feature for weeks, Adobe charges $60k anyway

## The Problem Marketo, Adobe's $60k-per-year email platform, broke its unsubscribe function. For two weeks. That is a CAN-SPAM violation on a feature as basic as they come. Support blamed Salesforce. Then blamed the customer's email client. Then said "it must be something you are doing." Eventually, Adobe's Global Escalation Desk confirmed in writing: Marketo was "not honoring unsubscribes properly." No fix timeline. No ownership. Just a shrug until renewal came up. ## The Real Fix The customer built a replacement in an afternoon. Claude, Replit, done. Direct API call to Marketo to delete the record, confirm to the subscriber, ship. Five years ago, that does not happen. You wait in the support queue. You pay a consultant $300/hour for weeks. Now? Three people and some AI agents ship the fix before lunch. Even then, Marketo's 2018-era API fought back. Rate limits, documentation gaps, the kind of friction that modern developer tools killed years ago. Replit nearly gave up. ## Why This Matters for Sales Teams This is the story of B2B software in 2026. Legacy platforms charging enterprise prices for products that barely work. Support as a cost center. No meaningful feature shipping. Survival by switching costs alone. That worked when "build it yourself" was impossible. Not anymore. When your sales tech stack includes tools with APIs this dated, your revenue ops team is building workarounds instead of pipeline. Public SaaS stocks are down 27% year-to-date. The thesis: AI natives (47% conversion rates) are replacing legacy tools (25% rates). But the real issue is simpler. The software just is not good enough anymore. Compare Marketo's API to Stripe, Anthropic, or any developer-led platform from the last five years. The gap is generational. For $60k per year from Adobe, buyers expect the modern end. Not 2015 tooling wearing a fresh coat of marketing. ## The Sales Angle If you are selling legacy B2B software in 2026, your biggest competitor is not another vendor. It is Claude plus an afternoon. Your buyers know this now. If you are buying: check the API docs. If they look like Marketo's, factor in the cost of your team building fixes when support shrugs. That $60k seat price does not include the engineering hours to keep it working. Adobe's escalation code for this case was "Time to Resolution," not "Product Defect." That tells you how they categorize a core feature being broken. The product worked fine. They just took too long to admit it did not. No ANZ-specific data on Marketo usage, but Adobe runs Sydney and Melbourne offices (200-300 headcount including sales). If your stack includes Adobe Experience Cloud tools, worth asking: when was the last time they shipped something that actually improved quota attainment? The comp is not the issue here. The software is.

SaaStr
4 months ago
News

Figma first sales hire: $2M to $950M ARR, no discounts, 300-person team

# Figma First Sales Hire: $2M to $950M ARR, No Discounts, 300-Person Team Kyle Parrish joined Figma in 2018 as the first sales hire when the company was doing $2M ARR. By the time Figma went public, it was hitting $950M ARR with 450,000 paid customers and a 132% NDR in accounts over $10k ARR. The path there required building an enterprise motion from scratch while protecting the PLG community that got them there. ## The No-Discount Rule That Actually Worked Figma refused to discount. Not just "we prefer not to", but a hard no across every deal, including enterprise. Microsoft pushed back. Procurement teams were furious. The rule held. The reasoning: trust and transparency. If every customer pays the same price, no one worries they got a bad deal. It forced the team to win on value, not price negotiations. Worth noting: Figma replaced discounting with enterprise licensing agreements (ELAs) that bundled products differently, but the per-seat pricing stayed consistent. ## What the First Sales Hire Actually Does Parrish's early days were not about quota. They were about learning the market. He sat on couches with designers for hours. Went to meetups. Listened more than he pitched. The sales motion grew out of genuine curiosity about the design community, not a playbook imported from another SaaS company. Stage alignment mattered here. Figma did not hire a big-company executive. They hired someone addicted to building, comfortable with ambiguity, willing to do 15 jobs badly before figuring out which ones mattered. Parrish's advice for founders hiring their first sales rep: look for "scar tissue" from early-stage operators. People who have built GTM motions from scratch know what breaks and what scales. ## The Adobe Deal Collapse Was the Unlock In 2022, Adobe offered to acquire Figma for $20B. The deal fell through. Figma paid a $1B breakup fee and immediately had its best year. The product team, no longer constrained by acquisition due diligence, launched Dev Mode and expanded from 3 products to 8 in a single conference. Parrish's take: being under acquisition froze the company's ambition. The collapse freed them to execute. ## What This Means for Early-Stage Sales Hiring Figma's growth demonstrates three things that matter when building a sales function from zero: 1. **Respect the community you are selling into.** PLG companies fail at enterprise when sales treats the existing user base as leads to close instead of a market to serve. 2. **Pricing consistency builds trust faster than discounts build pipeline.** The no-discount rule was painful early but became a competitive advantage. 3. **Stage-appropriate hiring beats pedigree.** A VP from Salesforce is the wrong hire at $2M ARR. You need someone who has carried a bag at a company that went from zero to scale. Figma is now public (FIG), reporting $749M revenue in 2024 with 48% YoY growth. They spend $300k daily on AWS infrastructure and have 11,107 customers over $10k ARR. The first sales hire built the foundation for all of that. Not by closing deals faster, but by learning the market deeply enough to scale without breaking what made the product work in the first place.

Sales Hacker
4 months ago
News

ANU spinout Syenta raises $36m Series A for AI chip tech

## ANU spinout Syenta raises $36m Series A for AI chip tech Syenta, an Australian National University spinout making AI chip packaging tech, closed a $36 million Series A led by Silicon Valley's Playground Global. The National Reconstruction Fund contributed $10.1 million. Existing investors Investible, Salus Ventures, Jelix Ventures, and Wollemi Capital participated. The Sydney-based company previously raised $2.2 million in late 2022 and $8.8 million in a pre-Series A last August. Total funding now sits around $47 million across six years. Former Intel CEO Pat Gelsinger, now a Playground Global general partner, joins the board. ### What they actually do Syenta started as a multi-material 3D printing operation. Now they develop Localized Electrochemical Manufacturing (LEM), a chip packaging process that CEO Dr Jekaterina Viktorova says cuts production steps by 40% without redesigning existing manufacturing infrastructure. The pitch: finer-pitch chip connections that move data faster at lower cost. Production target is 2027. ### The expansion play Funding goes toward commercialisation for high-volume production and US expansion from an Arizona base. Worth noting: moving from university spinout to semiconductor production at scale is a long ramp. 2027 is the target, not a guarantee. ### What we don't know No sales team disclosed. No go-to-market strategy detailed. No customer pipeline mentioned. No CRO or VP Sales named. For a company targeting 2027 production, that either means early days on commercial strategy or they are keeping cards close. The AI chip market is crowded: Mythic raised $70 million in 2021, other startups chase Nvidia's dominance. Syenta's play is packaging tech, not chips themselves, which positions them as infrastructure rather than direct competition. Different sale, different buyer. ### ANZ angle Rare to see Australian deeptech at this scale. The National Reconstruction Fund bet signals government interest in local semiconductor capability. Whether that translates to ANZ-based manufacturing jobs or sales roles remains unclear. Arizona expansion suggests the commercial focus sits offshore.

Startup Daily
4 months ago
News

Australian business coalition demands AI funding in 2026 budget

# Australian business coalition demands AI funding in 2026 budget The Alliance of Industry Associations submitted a pre-budget proposal calling for increased AI investment, skills development, and tax reform ahead of Australia's 2026 federal budget. The move puts pressure on Labor to back its December 2025 National AI Plan with actual funding. ## What they want The coalition is pushing for: - Stronger AI investment commitments - Skills and training programmes (relevant for sales teams facing the AI gap) - Tax reform to support AI adoption Specifics on dollar amounts were not disclosed in the submission. ## Why this matters for sales teams Australian sales organisations are navigating the AI skills gap without clear government support. While the US rolled out programmes like AI-Ready America (Department of Labor initiatives, NSF education funding), ANZ teams have been left to figure it out themselves. The coalition's timing is deliberate. Labor's National AI Plan tied AI to productivity and the Future Made in Australia agenda, but stopped short of standalone legislation. The plan relies on voluntary compliance, asking businesses to police themselves. ## The budget context AI got zero mentions in the 2024-25 federal budget papers, despite heavy government messaging in the two years prior. Most 2025 AI policy (the regulation roadmap, high-risk AI consultation, public sector rules) had already been funded in earlier budgets. The 2026 budget will show whether the National AI Plan was strategy or theatre. For sales leaders evaluating AI training budgets, the absence of government programmes means self-funding remains the default. ## What happens next The submission tests Labor's willingness to fund AI capability building. If the May 2026 budget includes dedicated AI skills funding, it creates pathways for sales teams to access training. If not, the gap between policy ambition and practical support continues. For now, Australian sales organisations are watching whether the National AI Plan turns into budget line items or stays a PDF on a government website.

SmartCompany
4 months ago
News

Finder cuts 54 jobs globally, 10% of workforce

## Fifth round in three years Finder cut 54 jobs globally in early 2026, trimming roughly 10% of its 500-600 person workforce. The Sydney-based comparison platform has now completed five redundancy rounds since 2023, cutting an estimated 225 roles total. Sources confirm cuts hit multiple regions and teams. Specific ANZ impact is unclear, but commercial operations are likely affected. Finder generates revenue through affiliate commissions and lead gen partnerships, not direct sales to consumers. That means the "sales team" is really partnership managers and commercial ops, estimated at 50-100 people ANZ-wide based on LinkedIn data. ## What changed Finder employed 500+ staff globally at its 2021 peak. Four rounds between 2023 and 2024 cut roughly 175 roles. February 2024 alone saw 60 redundancies, 17% of headcount at the time. That round included Australian CEO Chris Ellis, who moved to an advisory role. The company is citing "cost pressures and AI-driven efficiencies" per sources, language that matches broader 2026 fintech layoff trends. Translation: automating content production and lead scoring, shrinking the teams that used to do that manually. ## Market context Finder competes with Canstar, Mozo, and RateCity in ANZ financial product comparison. Traffic sits around 10 million monthly visitors. Revenue estimates land at AUD 100-150 million annually, but Finder is private and does not disclose numbers. CEO Frank Schembri (co-founder) remains. Chief Commercial Officer Brock McKinley oversees partnerships and revenue. No dedicated CRO or VP Sales role is publicly listed. For sales professionals: if you are in fintech affiliate or partnership roles, this is the third comp platform to cut headcount in 18 months. The model is shifting toward automated lead scoring and fewer human touches. Plan accordingly.

SmartCompany
4 months ago
News

Apple names John Ternus CEO, Cook to executive chair

Apple named John Ternus as CEO, effective 1 September 2026. Tim Cook, who has led the company since 2011, becomes executive chairman. Ternus, 50, is a 25-year Apple veteran who most recently ran hardware engineering. He led development of iPads, AirPods, and the iPhone Air. Before Cook became CEO, he ran worldwide sales and operations as SVP. That background is not part of Ternus's resume. The shift matters for sales teams: Apple is moving from an operations and supply chain leader to a product and design leader. Cook turned Apple into a machine that ships hundreds of millions of units per year. Ternus's track record is products that people want to buy, not the systems that get them to market. Apple does not publicly disclose sales team size, CRO, or VP Sales details. The company sells through retail stores (including Sydney and Melbourne), online channels, and enterprise partnerships. No sales leadership changes were announced alongside the CEO transition. Johny Srouji becomes Chief Hardware Officer. Tom Marieb takes over hardware engineering, reporting to Srouji. All changes are effective immediately, with Ternus transitioning into the CEO role over the next four months. For ANZ sales teams selling into enterprise or partnering with Apple, the question is whether a product-focused CEO shifts how the company engages with channel partners and enterprise accounts. Cook maintained strong relationships with major enterprise customers and government (he recently presented a custom plaque to Donald Trump). Apple says Cook will continue engaging with policymakers in his executive chairman role. Apple has 160,000+ employees globally. Specific ANZ headcount is not disclosed. The CEO transition comes as Apple faces pressure from Nvidia (now the world's most valuable company) and Meta (whose AR glasses undercut Vision Pro on price and adoption). No layoffs or sales org restructuring were announced. Worth watching: how a hardware-focused CEO approaches enterprise sales strategy and channel relationships in ANZ and globally.

Startup Daily
4 months ago
News

B2B buyers want 12-month contracts, not 3-year deals. AI changes everything.

## The Contract Length Problem A VP of Sales at a $100m+ ARR AI startup summed it up: "Everyone wants to buy. No one wants to sign a long-term deal." ICONIQ's 2026 State of Go-to-Market report confirms this is not isolated. Sub-1-year contracts for new logos grew from 4% in 2023 to 13% in 2026. Three-year deals dropped from 28% to 23% over the same period. Sales cycles shortened from 25 weeks to 19 weeks. Buyers are deciding faster but committing for less time. That combination tells you where confidence actually sits right now. ## Why It Is Happening This is not buyer hesitation. It is buyer rationality. When the best solution in a category can genuinely change in 6 to 12 months, signing a 3-year deal is not partnership. It is a risk buyers did not ask to take. Former Snowflake CRO Chris Degnan put it directly: companies want to give employees tool choice, but they will not sign long-term contracts in an AI world where the best solution can change in months. They want options. Consumption pricing accelerates this. When buyers cannot forecast usage because the product category is new or their AI workflows are still being figured out, finance teams will not approve multi-year commitments. Short-term contracts become the compromise. ## What This Means for Sales Teams Stop discounting multi-year deals. You win the deal and lose the renewal when buyers resent the commitment by month 18. Fix comp structure. Net New Recurring Revenue as a comp metric jumped from 25% to 33% of companies in one year. Net Dollar Retention rose 5 points. AEs need to be rewarded for quality, not just TCV. A 12-month deal that expands 150% beats a 3-year deal that churns. The answer to shorter contracts is better post-sales, not better sales. Customer success-sourced pipeline wins at 52%, higher than sales (43%), channel (39%), or marketing (27%). When CS owns expansion and customers see ROI fast, short contracts become annuities. Quota math changes too. If your team is carrying the same number but deals are 12 months instead of 36, attainment assumptions break. Territory planning, ramp periods, pipeline coverage: all need recalibration. ## The Bottom Line B2B software is shifting from multi-year commitments to prove-it-quarterly relationships. That is not a sales problem. It is a market reality. Sales teams that adapt comp, territory planning, and post-sales motion will win. Teams that keep pushing 3-year deals with discounts will watch attainment drop.

SaaStr
4 months ago
News

SaaStr cuts sales team from 20 to 3, adds AI agents, revenue up 47%

## The Numbers SaaStr went from 20+ sales employees to 3 humans plus 20+ AI agents across Artisan, Qualified, AgentForce, Monaco, Momentum, and custom builds. Revenue: -19% YoY to +47% YoY over 10 months. Pipeline closed-won: $2.4M. Pipeline generated: $4.8M. ## What Changed Jason Lemkin, SaaStr founder and CEO, ran the numbers with a public company CRO. Every AI agent deployment had one thing in common: no lead left behind. The agents handle: - Instant answers to website visitors (no form fills) - Immediate meeting booking (no queue) - Follow-up on every lead in the database (including six-month-old cold leads) - Re-engagement of closed-lost deals, expired trials, churned customers One AI SDR booked a six-figure sponsorship deal on a Saturday at 6:02 PM. No human was working. That one deal covered months of AI agent cost. ## Why It Works Not the models. Not the platforms. Coverage. Human sales teams prioritise. They work A leads, touch B leads if time allows, ignore C leads entirely. AI agents touch everything. They do not sleep, take weekends off, or deprioritise leads based on score. Lemkin's playbook: 1. Answer every question instantly (no knowledge base links) 2. Book meetings instantly (no forms) 3. Follow up every lead (including old ones) 4. Re-engage closed-lost and churned accounts ## The Market Context AI lead scoring automation and AI email lead generators are trending hard. Tools like HubSpot AI lead scoring, Salesforce lead scoring, and predictive lead scoring software help prioritise. But SaaStr's approach is different: do not prioritise, cover everything. Outbound AI sales agents and AI lead follow-up automation are moving from pilot to production. Sales Closer AI and similar tools are getting reviewed by real sales teams. The best AI sales agents are not replacing AEs, they are handling the volume humans cannot. ## What This Means for Sales Teams If your team ignores leads because of capacity, you are leaving revenue on the table. If your SDRs only work during business hours, you are missing deals. If your closed-lost list sits untouched, you are losing to competitors who redeploy AI agents. SaaStr is events and tickets, sure. But the principle applies: most B2B sales teams do not have a lead quality problem, they have a lead coverage problem. AI agents fix that. No ANZ presence reported yet, but the playbook works anywhere you have more leads than humans can handle.

SaaStr
4 months ago
News

Ideally raises $13.4M Series A, counts Google and Telstra as clients

## Ideally raises $13.4M Series A, counts Google and Telstra as clients Auckland-based consumer insights startup Ideally closed a $13.4M Series A led by Shearwater Capital, with Altered Capital and Icehouse Ventures participating. The round values the company at $83M. The platform uses generative AI to run market research that traditionally took months and six figures. Clients include Google, Telstra, DoorDash, Burger King, and Asahi. The company serves 250+ brands across APAC and US. ### The numbers - Series A: $13.4M at $83M valuation - Previous raises: $2.15M (November 2023), $5.5M (August 2024) - Total raised: approximately $21M - Client count: 250+ brands - US revenue growth: 350% since New York office opened Founded in August 2023 by James Donald, Brendan Cervin, and Joshua Nu'u-Steele out of venture studio TRA Labs. CEO James McDonald joined later. ### What it means for sales teams Ideally is a customer research platform, not a sales intelligence tool. Different category entirely. Think UserTesting or Qualtrics, not ZoomInfo or Apollo. That said: the funding signals ANZ B2B SaaS is still attracting capital. Consumer insights platforms typically sell into marketing teams at enterprise accounts, which means longer sales cycles and higher ACVs. The company recently opened a New York office and is using Series A capital for US expansion. That usually means hiring AEs and SDRs in market. No hiring numbers disclosed yet. Worth noting: the company says it "could not have existed without generative AI." That positioning likely plays well with enterprise buyers evaluating new platforms versus legacy research providers. ### Context Consumer insights is adjacent to sales intelligence but serves different buyers. Sales intelligence platforms (Apollo, ZoomInfo, Cognism) help find and reach prospects. Consumer insights platforms help understand customer behaviour and validate product decisions. Ideally competes with established players like UserTesting and Qualtrics in the research space, not with sales tech stacks. The AI angle differentiates on speed and cost: what took 9 months now takes 90 days, according to the company. Client roster includes major ANZ enterprises (Telstra) and US brands (DoorDash, Burger King), suggesting the platform has product-market fit in both regions. The 350% US revenue growth backs that up, though no absolute revenue numbers disclosed. No word yet on ANZ headcount, sales team size, or hiring plans locally.

Startup Daily
4 months ago
News

750 ANZ startup funding rounds go unreported, Techboard analysis shows

# 750 ANZ startup funding rounds go unreported, Techboard analysis shows Most Australian startup investments never make headlines. Techboard, the WA-based startup data firm, tracked 1,100 companies that raised external investment in 2025. Only 361 announced their deals publicly. That leaves roughly 750 unannounced rounds, potentially more than double the reported funding activity. The announced deals totalled $5.2 billion across 379 raises. The unannounced deals? No dollar figures available, but Techboard estimates they could represent the majority of actual capital flowing into the ecosystem. ## Why this matters for sales If you are prospecting into early-stage tech, the company you are targeting might have raised without telling anyone. That changes qualification. A stealth Series A means different budget authority than a bootstrapped operation. Traditional sales intelligence tools like Crunchbase or CB Insights track announced deals. Techboard digs into ASIC regulatory filings to surface unannounced investment activity. In H1 2025 alone, they identified 682 possible unannounced deals versus 255 announced ones. Founder Peter van Bruchem notes the trends in unannounced deals do not match public announcements. Smaller rounds, less newsworthy sectors, and founders without media access stay quiet. Some companies actively avoid publicity. ## What the data shows Techboard has been tracking Australian startups since 2015, monitoring over 7,500 companies. Their methodology: combine announced deals with ASIC share issuance data to identify likely funding events. The gap between announced and actual funding creates blind spots for competitive intelligence and prospect research. If half the market is raising capital without announcing it, your sales team is working with incomplete information. For AEs targeting funded startups, this means enriching data beyond press releases. ASIC filings, hiring patterns, and direct outreach matter more when companies stay in stealth mode. Full report available at Techboard's site. Worth reading if your patch includes early-stage tech companies in ANZ.

Startup Daily
4 months ago
News

ANZ boards lack tech directors as AI reshapes sales strategy

## The Numbers Over 50% of ASX 500 boards have no directors with science, technology, engineering, or maths backgrounds. This matters for sales teams: boards set AI investment priorities, approve CRM spend, and green-light the AI-native tools your team needs to hit quota. Australia faces a 40,000 AI talent shortage by 2027. That gap extends to the boardroom, where directors lacking tech fluency struggle to evaluate AI governance frameworks or assess whether your sales stack is competitive. ## Why Sales Teams Should Care Boards without tech expertise make slower decisions on AI tooling. When your CRO pitches budget for AI agents or conversation intelligence, boards that do not understand the tech default to risk aversion. The Australian Institute of Company Directors reports 53% of business leaders cite digital transformation as their top 2025 concern, yet board composition lags. This creates friction for sales orgs chasing productivity gains. Gartner tracks new AI roles emerging across GTM teams: AI governance leads, prompt engineers for sales, AI-native SDR managers. Without board understanding, these headcount requests stall. ## The Hiring Angle Restructuring experts say boards need curious, tech-literate directors, not full engineering backgrounds. Apathy is the barrier, not capability. For sales leaders, this means building internal business cases that educate upward: show board-level ROI on AI investments, translate technical capability into pipeline metrics. Bessemer tracks AI agents for sales as a category: 47% of enterprise sales teams pilot AI SDRs in 2025. Your board needs to understand why that matters before approving spend. If they lack STEM fluency, your CRO becomes the translator. ## What This Means Sales orgs at companies with tech-literate boards move faster on AI adoption. They get budget approved, hire specialized roles, and ship tools that improve attainment. Companies stuck with traditional board composition lag on AI-native sales strategies. The skills gap analysis shows up in sales hiring too: director-level roles now require AI competency. Boards that do not prioritize tech expertise will struggle to evaluate whether their sales leadership can scale in an AI-first market. Bottom line: board composition impacts your comp. Faster AI adoption means better tools, clearer territories, and realistic quotas. Slow boards create drag.

Startup Daily
4 months ago
News

Salesforce launches API-first CRM: AI agents skip the browser entirely

## Salesforce launches API-first CRM: AI agents skip the browser entirely Salesforce announced Headless 360 at TDX 2025: the entire CRM platform accessible via APIs, with no browser required. CEO Marc Benioff called it "the API is the UI," positioning it as infrastructure for AI agents. For sales teams already running AI tools in production, this is not news. It is confirmation. Jason Lemkin, founder of SaaStr, said his team has been operating this way for six months. Their AI-powered marketing and customer success agents pull real-time pipeline data, assign tasks, and surface revenue analysis directly from Salesforce APIs. No one logs into the browser. "If you're running a modern B2B + AI stack, you've probably been doing versions of this for months," Lemkin wrote. "You just haven't named it yet." ### What this means for sales ops Headless 360 exposes Salesforce and Agentforce (its AI agent platform) through APIs, MCP protocols, and CLI commands. AI sales agents can now access CRM data, trigger workflows, and execute tasks without human login. Practical applications already in use: - AI SDRs pulling enrichment data and logging activity automatically - Pipeline analysis agents surfacing deal risk without manual reporting - Lead routing and task assignment via API, bypassing manual workflows This shifts Salesforce from "system of record" to "system of execution" for agent-driven sales motions, according to company messaging. ### The AI agent sales stack question Salesforce is positioning Agentforce as the layer between AI agents and CRM data. Alternatives exist: HubSpot Workflows, Outreach AI automation, and custom-built API integrations already handle similar use cases. The question for ANZ sales leaders: does this justify Salesforce's pricing premium, or do lighter-weight tools deliver the same workflow automation at lower cost? Salesforce holds roughly 20-25% CRM market share globally and dominates ANZ enterprise accounts (banks, telcos, large tech). No ANZ-specific pricing for Headless 360 has been disclosed yet. ### What changed Not the technology. Sales teams have been hitting Salesforce APIs for years. What changed is Salesforce officially packaging this as a product strategy and messaging it as the future of CRM. Benioff is betting that as AI agents become standard in sales workflows, the companies that make their data most accessible will win. Headless 360 is that bet, formalised. For teams already running AI agents in production, the takeaway is simple: you are ahead of the announcement cycle. Keep shipping.

SaaStr
4 months ago
News

SaaStr runs 20 AI agents, 3 humans, revenue up 66 points YoY

## The Setup SaaStr is running 20+ AI agents with three humans handling leads and revenue ops. Revenue swing: -19% to +47% YoY. Founder Jason Lemkin and head of AI Amelia Bywater shipped a new podcast breaking down what works, what breaks, and what founders building AI into sales should actually know. No roadmap promises. Just production reality. ## What They Are Seeing **Vibe-coded apps need daily maintenance.** SaaStr has shipped 10+ AI apps with 750,000+ combined uses. Every single one needs a product-savvy human checking on it daily. Models update without warning. Integrations flake. Agents drift. The fun part is building. The work is keeping them running. **Hallucinations are daily maintenance, not solved problems.** Their AI VP of Marketing compared the wrong year in an analysis this week. Made up a data point in another. These are not rare edge cases. They are daily outputs that ship to customers if no one is reviewing. The fix is not a better model. The fix is a process: someone reviews outputs every day. **Model regressions silently break working apps.** Their pitch deck analyzer graded 4,000+ decks without issue. Then the underlying model updated, and outputs went sideways. No changelog. No heads-up. Just broken results you have to catch yourself. **Agents upsell without knowing it.** Clay's agent recommended a model 2 to 5 times more expensive than needed, right around a price increase. Probably not intentional. Effect on the customer is identical: pushed toward premium without knowing cheaper works fine. Every B2B sales tool using AI agents needs to audit this now. Is your agent recommending the right tier, or is it steering customers to the most expensive option because that is what training data rewards? **Agents blame other tools when they break.** Something breaks, the agent points at Stripe, Airtable, OpenAI rate limits. Sometimes true. Often not. You need humans who can call BS and say "check again." ## The Unlock "No Lead Left Behind." AI agents catch what humans miss. Lemkin's thesis: the real value is not replacing SDRs, it is capturing leads that slip through when humans are stretched thin or focused elsewhere. SaaStr is proof of concept. Three humans, 20+ agents, revenue up 66 points. The work is maintenance, oversight, and knowing when the agent is wrong. ## What This Means for Sales Teams If you are running AI SDR agents or lead qualification tools, the honeymoon phase is building the demo. The actual job is daily review, quality baselines, and catching drift before customers do. AI for lead gen works. AI for ops works. But it does not run itself, and providers are figuring out monetisation in real time. Watch your bills. Watch your outputs. And do not automate away the operator instinct that knows when something smells wrong. Comp transparency check: SaaStr has not disclosed headcount details or sales team OTE. This is a media/events/community business running lean, not a traditional SaaS sales org. The lesson is in the ops model, not the comp structure.

SaaStr
4 months ago
News

HubSpot ships incomplete AI tool, charges $50/month for zero recommendations

## The Problem HubSpot launched an AI Engine Optimization tool. It does not work well enough to charge for. Here is what it delivered: - Brand visibility score: 70%. No action items. - Sentiment analysis: 0% for content, 64% for events. Across 7,000+ published posts over 10 years. - Recommendations: "No recommendations just yet." - Price: $50/month for more prompts. That is not a product. That is a dashboard with broken metrics and a paywall. ## The 60% Pattern This is not just HubSpot. B2B vendors are rushing to ship AI features that check the "we have AI" box without solving problems better than dedicated tools already do. Six months ago, buyers gave credit for shipping early. That window closed. AI-native point solutions have compounded improvements: more data, more iterations, deeper integrations. The gap between "60% good enough" and "best in class" has widened, not narrowed. Replit and Lovable for building. Reve for images. Higgsfield and Opus for video. Gamma for presentations. These tools work. When enterprise vendors ship half-finished AI features, users may try them. They will not pay for them. ## What Actually Works One SaaS founder built a better AEO tool in 60 minutes using Replit. The difference: it generates actionable recommendations. "Your Structured Data scores 20/100. You have no JSON-LD markup. Here is the exact prompt to fix it." HubSpot's tool said "no recommendations." The quickly-built alternative gave specific issues, category breakdowns, and ready-to-use prompts for WordPress, Shopify, and AI coding tools. It improved SaaStr's AEO score from F to C+ in minutes. That is the threat now. If a founder can ship a better solution in an hour, your enterprise AI feature needs to deliver more than metrics and a paywall. ## What This Means for Sales Teams If you are evaluating CRM AI features in 2025: - Test them properly. Do they generate actionable output or just dashboards? - Compare to AI-native point solutions. Is the bundled feature actually better, or just convenient? - Watch for "no recommendations yet" signals. That means incomplete. - Check if they are asking you to pay before the product works. The bar for AI features has moved. Buyers were forgiving 6-9 months ago. Not anymore. If your vendor is shipping 60% solutions while charging full price, the dedicated tool probably works better. Worth noting: this applies to sales intelligence, conversation analysis, email sequencing, and every other AI feature getting bolted onto platforms. The LLMs got significantly better in late 2025. The gap between half-finished and production-ready is now obvious to users. Competitive pressure to ship is real. But shipping broken features with paywalls does not build trust. It creates churn opportunities for AI-native competitors who already solved the problem.

SaaStr
4 months ago
News

Canva delays IPO to 2027, shifts pricing to AI usage model

Canva will not IPO in 2026. The design platform is pushing its public listing to 2027 at the earliest, co-founder Cliff Obrecht confirmed to Capital Brief at the company's Los Angeles product launch. The delay centres on business model transition. Canva is overhauling its pricing to usage-based for AI features, and Obrecht wants that shift proven before investor roadshows begin. "We're fully IPO ready," he said, "but we want to make sure the evolution of this business model is really bedded in so we're not having to explain ourselves to the market through a transitional period." Translation: they are reworking how enterprise customers pay, and they want adoption data before the S-1 drops. Last valuation was A$65 billion in secondary sales in August 2025. That puts Canva close to Atlassian's market cap and makes it Australia's second-most valuable tech company. Unless there are more secondary rounds, early employees and investors wait another 9 to 12 months minimum for liquidity. The company has been on an acquisition run: eight startups in two years, including last week's Simtheory and Ortto acquisitions from the Stayz founders, reportedly over $100 million. That build-versus-buy strategy suggests Canva sees faster paths to AI credibility through M&A than internal development. For ANZ sales teams watching this: Canva's delay reflects broader 2025 and 2026 SaaS IPO market conditions. Software multiples compressed hard through 2024. Public SaaS companies that did list saw share prices hammered. Canva is choosing patient capital over public market volatility. What this means: if you are at a late-stage ANZ startup eyeing an IPO, your timeline just got longer. Canva has the luxury of waiting. Most do not. The comp packages built around 2026 liquidity events may need revising. Obrecht's comment about "transitional periods" is telling. Public market investors punish companies still figuring out their revenue model. Canva knows this. They are delaying until the AI pricing works and the numbers prove it.

Startup Daily
4 months ago
News

7 ANZ startups raised $71.8 million mid-April, Phonely leads at $22.3 million

# 7 ANZ startups raised $71.8 million mid-April, Phonely leads at $22.3 million Seven ANZ startups closed funding rounds totalling $71.8 million in mid-April. Most are pre-revenue with no disclosed sales teams, headcount, or comp details. ## Phonely: $22.3 million Series A Phonely, the University of Melbourne spin-out building AI receptionists, raised $22.3 million in a Series A led by Base10 Partners. Y Combinator doubled down after backing the startup with $750,000 in mid-2024. Three enterprise customers co-invested: Etech Global Services, TSA Group, and Engage CX. The round values Phonely at $139 million. Total raised: $26 million. Founded in 2023 by Will Bodewes and Nisal Ranasinghe, Phonely is now based in San Francisco. The AI receptionist answers FAQs, routes calls, and books appointments using a company's website data. Setup takes five minutes. No details on sales team size, AE hiring plans, or go-to-market structure were disclosed. ## The rest of the cohort Pay.com.au, Atomic Tessellator, Caruso, Deteqt, Clean State Clinic, and Earthletica also raised capital. Funding amounts were not disclosed for these six. Separately, Founder Institute Australia/New Zealand graduated seven startups in a recent cohort, including Mareekh Dynamics (space habitation systems), Co-Linic AI (allied health SaaS), and Divergity (ADHD productivity platform). All are pre-seed or seed stage with no disclosed revenue, sales teams, or executive details. ## What this means for sales professionals Series A rounds typically mean hiring plans. Phonely's $22.3 million raise at a $139 million valuation suggests expansion, but no AE or SDR hiring was announced. For sales professionals watching ANZ tech, this is capital flowing into early-stage companies, not yet translating into disclosed sales roles. Most startups in this cohort are pre-revenue or revenue details were not shared. That means no comp transparency, no team size data, and no clarity on what roles might open up. Worth tracking: Phonely's customer base includes three contact centre players. If they scale, enterprise AE roles could follow. Until then, this is funding news without hiring signals.

Startup Daily
4 months ago
News

Canva pushes into sales workflow tools with AI 2.0

## Canva pushes into sales workflow tools with AI 2.0 Canva launched AI 2.0 overnight, expanding beyond design templates into workflow automation and app integration. The Sydney-based company is targeting the productivity tools that sit between your CRM and your deck. The update includes conversational design (describe what you need, AI builds it), automated workflows, and connectors that pull data from emails, meetings, and documents. That positions Canva closer to workspace tools than design platforms. **What this means for sales teams:** Most sales orgs use Canva for one-off collateral: decks, one-pagers, case studies. The AI 2.0 push suggests Canva wants to own more of that workflow. Pull meeting notes, generate a pitch deck, export to PDF, all without leaving the platform. The company hit $4 billion ARR serving 240 million users globally. Recent acquisitions include Ortto (marketing automation) and Simtheory (AI workflows), signalling vertical integration from campaign brief to delivery. Competition context: Canva competes with Adobe and Figma on design, but this update puts it closer to Google Workspace and Microsoft 365 territory. Google acknowledged the overlap last year when Canva launched spreadsheets and charts. **Pricing reality for sales teams:** Canva runs a hybrid model: seat-based subscriptions plus usage-based AI credits. Free tier exists but sales collateral at scale requires paid seats. Enterprise pricing is custom (read: negotiated). Figma runs similar economics but skews more technical. For smaller sales teams, the question becomes: do you need another tool subscription, or can your existing stack handle collateral creation? For enterprise, it's about consolidation. If Canva replaces three point solutions, the math works. **ANZ angle:** Canva is Australian-headquartered (Sydney), employs over 3,000 globally, and continues expanding enterprise integrations. No recent funding rounds reported; focus is profitability and AI scaling after hitting $40 billion valuation in 2021. The company is pushing hard into mid-market and enterprise, targeting teams that want to consolidate their martech stack. Sales orgs running fragmented tools (design here, automation there, analytics somewhere else) fit that profile. **Bottom line:** Canva is moving from "design tool sales teams use sometimes" to "workflow platform sales teams use daily." Whether that sticks depends on execution and whether reps actually want another login between their CRM and their prospects. Watch for enterprise sales hiring. If Canva is serious about displacing workspace tools, they will need AEs who can sell consolidation, not templates.

SmartCompany
4 months ago
News

TestBox CEO: Buyers make 70% of decision before first call

## The Discovery Call Is Dead B2B buyers are making 70-80% of their purchase decision before they ever talk to sales, according to Sam Senior, CEO of TestBox, a $12M-funded platform that lets buyers test-drive software. Speaking on the GTMnow Podcast, Senior laid out what is actually happening: buyers are using ChatGPT and Claude to research vendors, test use cases, and build shortlists. By the time they book a call, they are not looking to discover their needs together. They are looking to validate what they already believe about your product. The day one shortlist has shrunk from 3-4 vendors to 1-2. If you are not on it, the call is a courtesy. ## What This Means for AEs Your first call is now a validation call, not a discovery call. Buyers have already TestBoxed your use case in an LLM and got 70-80% of the result in 30 seconds. Your job is to bridge that gap to 100% and prove real value, which takes longer than it used to. Senior recommends auditing what LLMs are saying about you right now. Ask Claude or ChatGPT what your buyers are researching and see how your product shows up in those answers. He calls this CEO, the AI version of SEO. The mid-funnel is getting longer, not shorter. Buyers come in with high expectations and more context. That changes how you prep, how you position, and how you prove differentiation. ## Agent-to-Agent Procurement in 3-5 Years Senior laid out a timeline: LLM research today, AI-assisted trial evaluation in 12-18 months, agent-to-agent demos in 24-36 months, full AI-led procurement including negotiation within 3-5 years. The companies building for this now will have an advantage. The ones ignoring it will be scrambling when buyers stop booking calls altogether. TestBox runs 15 AI experiments per week across the company and ties token usage to performance reviews. Senior is clear: AI adoption is a culture problem, not a tools problem. It only works when it is a company-wide operating model, not just an engineering initiative. Worth noting: TestBox uses Google Vertex video analysis to read prospect body language on sales calls. That is where this is going. ## What to Do Now 1. Audit what LLMs are saying about your product 2. Reframe your first call as validation, not discovery 3. Build content that shows up in LLM research 4. Prep your team for longer mid-funnel cycles 5. Start running AI experiments across GTM, not just product The buying process has changed. Your sales process needs to catch up.

Sales Hacker
4 months ago
News

Phonely raises $22M, replaces 350 human agents in one month

## Phonely raises $22M, replaces 350 human agents in one month Y Combinator-backed AI receptionist Phonely closed a $22 million Series A led by Base10 Partners. The round values the San Francisco-based company at $139 million. The Melbourne University spinout launched in early 2024, raised $750,000 from YC mid-year, and has now pulled in $26 million total. Founders Will Bodewes (PhD AI researcher) and Nisal Ranasinghe built the product to answer calls, route inquiries, book appointments, and integrate with CRMs using a business's website URL. Setup takes 5 minutes. The platform now handles millions of calls monthly across thousands of businesses. Worth noting: one customer replaced 350 human agents in a month with Phonely. Three of Phonely's enterprise customers invested in the round: Etech Global Services, TSA Group, and Engage CX. TSA Group operates 4,500 human agents. Their head of AI said Phonely's agents "resolve calls better than our best people." Engage CX logged $14 million in insurance policy sales via Phonely in the first four months of 2026. ### Market context Phonely competes in a packed space. Beside AI (also an AI receptionist for small U.S. businesses) raised $32 million across seed and Series A from EQT Ventures, Index Ventures, and Slack founder Stewart Butterfield. Y Combinator has backed 141+ AI assistant startups, including Codyco (hotel reservations) and OpenCall.ai (AI call centers). The ecosystem skews U.S.-focused. No ANZ presence, headcount, or sales team details are public for Phonely. The company has not disclosed revenue, leadership structure, or plans for this capital beyond scaling the product. ### What this means for sales teams AI call handling tools like Phonely target the SDR and BDR layer: answering inbound, qualifying leads, booking meetings. If the 350-agent replacement holds at scale, this shifts headcount models for sales ops and inbound teams. Watch for pricing, integration complexity, and whether these tools handle nuanced discovery or just route calls. The $14 million insurance sales number suggests potential for outbound applications, but no specifics on whether Phonely does cold calling or just handles inbound. Comp implications: if AI handles first touch, does that compress SDR hiring or shift SDRs to higher-complexity roles? No data yet, but worth tracking as these tools mature.

Startup Daily
4 months ago
News

Flex Capital runs 500 AI agents for deal sourcing, predicts agent-to-agent VC meetings by 2026

## AI agents are already replacing initial VC meetings Auren Hoffman, General Partner at Flex Capital and founder of SafeGraph and LiveRamp, runs over 500 AI agents to source deals. His prediction: by the end of 2026, the first VC meeting will be agent-to-agent, with founders and investors talking through their agents before any human interaction happens. This is not a thought experiment. Flex Capital is already using AI agents to filter deal flow, assess companies, and handle initial conversations. The system is built around a core principle: missing a great deal is 10 times worse than making a bad one. The agents help Hoffman see more companies without filtering too early. Worth noting: Hoffman's track record includes early backing of Replit, Perplexity, Rippling, Vercel, Coinbase, Chime, and AppLovin. Flex Capital has invested in 120 to 180 companies, including exits like Aardvark (Google), Chomp (Apple), and Meebo (Google). ## What this means for B2B sales If VCs are automating initial meetings, enterprise buyers are next. The same economics apply: buyers want to filter vendors faster, sales teams want to reach more prospects, and AI agents can handle both. The comp implications are direct. SDRs and BDRs who focus on initial outreach are the most exposed. AEs who handle complex enterprise deals, negotiate contracts, and build relationships have more runway. But even that runway is shrinking. Hoffman also predicts that every software moat is gone. If you are not making your product significantly better every month, you will lose customers. That applies to sales tools too. Salesforce, LinkedIn, DocuSign are all vulnerable. The companies replacing them will likely use AI agents for customer acquisition. Another practical signal: Hoffman says companies will not sign yearly SaaS contracts anymore. The product landscape is changing too fast. That shifts sales cycles, comp structures, and quota setting. If your company is still building comp plans around 12-month contracts, that assumption may not hold. ## The funding context No recent funding details are public for Flex Capital. Hoffman's previous venture, SafeGraph, was valued at $370 million with backing from Sapphire Ventures, Peter Thiel, and Ridge Ventures. LiveRamp was acquired by Acxiom for $310 million in 2014 and later went public on NYSE with $280 million-plus revenue in 2019. The prediction on agent-to-agent meetings is not coming from a futurist. It is coming from an investor who has already deployed the technology and is betting capital on what happens next.

Sales Hacker
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