The tech goes live in days. The training that makes it work takes 60 focused days. Most companies skip the training, then wonder why it failed. SaaStr breaks down the actual timeline: foundation work in weeks 1-2, optimization in weeks 3-4, ongoing maintenance after day 60.
Canva acquired Melbourne adtech startup Doohly for $30M, adding digital out-of-home advertising to its design platform. ...
Sales LeadershipTeresa Anania, former SVP Customer Experience at Sophos (now CCO at Verint), breaks down how the cybersecurity firm mana...
Cauldron Ferm closed $13.25M led by Main Sequence Ventures to scale hyper-fermentation tech in regional NSW. The 2022-founded biotech runs a 30,000-litre facility in Orange but hasn't disclosed sales team size, structure, or hiring plans. Worth noting for biotech sales professionals: no CRO, VP Sales, or revenue numbers public despite $19.5M total raised.
Kim Teo's hospitality tech merger absorbed heavy integration costs in year one, with losses that had skeptics calling it. The company is now profitable, processing $2 billion annually across 6,000+ venues. Here is what it took to survive the messy middle.
New Zealand agtech Halter closed a $314.4 million Series E led by Founders Fund, nearly tripling its valuation to $2.9 billion in under 12 months. The company, which makes GPS-enabled cattle collars, now employs over 300 people across NZ, Australia, and the US, with expansion into the UK and Ireland planned.
# SaaStr runs 30 AI agents. 25 vendors pitched them this week. One got deployed. The difference: that vendor deployed the agent in five minutes instead of booking a demo. Jason Lemkin's team at SaaStr operates with three humans and 30+ AI agents. Their capacity for new tool evaluations is zero until after their May event. When five leading AI agent vendors reached out this week (plus 20 more via LinkedIn), the answer was uniform: talk in June. Except one vendor replied: "Give us five minutes. We will deploy it for you right now." They made time for that one. It is live. The other four are on the June list, if SaaStr has not found another solution by then. ## Deployment is the sale The winning vendor understood what most AI sales teams miss: Forward Deployed Engineers matter before the contract, not after. Every AI agent SaaStr runs successfully had dedicated FDE time. Every one. Palantir invented this model in the early 2010s because government agencies could not get to production without an engineer in the room handling messy data and specific workflows. Most AI vendors today use FDEs post-sale. The ones winning use them pre-sale. Marc Benioff told Lemkin on 20VC that even at $40B ARR, his biggest wish is getting AI agents deployed before contracts sign. Not pricing. Not product. Deployment. Salesforce did exactly that with SaaStr. They assigned FDE resources to configure Agentforce before the deal closed. Results: 1,000 ghosted sponsorship leads from SaaStr Annual, zero prior follow-up, 72% open rate after Agentforce deployment, 10%+ response rate, deals closing from six-month-old dead contacts. Salesforce is now SaaStr's AI agent hub because they deployed first and let results make the argument. ## Why this matters for sales teams SaaStr is not skeptical of AI agents. They run 30, generate over $1M in revenue from them, and spend $500k yearly on AI tools versus $10k on Salesforce. The technology works. The constraint is capacity. Every new agent takes minimum 30 days to production: data integrations, routing logic, edge cases, ongoing management. When a vendor says "we would love to get you set up" and the next step is a kickoff call, the honest answer is: not right now. The mental load is too high. When a vendor says "we will handle it" and actually does, the calculus changes completely. The deployment gap disappears. Value shows up immediately. Nothing goes on the list because it is already running. ## What this means for AI vendors The FDE model scales better than it used to. That is the part traditional software vendors have not internalized. Deployment before signature is not a services business. It is what sales looks like for AI agents in 2026. Vendors likely pitching SaaStr include Relevance AI, Beam AI, Ruh AI, Salesforce Agentforce, Zapier AI Agents, and Microsoft Copilot Agents. Most target enterprise customers (finance, healthcare, retail) with global integrations. ANZ-specific presence is minimal across leading vendors. The deployment rate Lemkin describes (1 in 25 pitches) tracks with broader AI agent adoption challenges: implementation complexity, integration friction, and capacity constraints hit even teams already running dozens of agents successfully. Worth noting: SaaStr spends 50x more on AI tools than their CRM. That ratio tells you where budget is moving for sales ops teams evaluating 2026 stack decisions.
## How Sophos Built CS Ops for 600k Customers Teresa Anania (now CCO at Verint, formerly SVP Customer Experience at Sophos) built customer success into a revenue engine at scale. Sophos protects 600,000 organisations globally, runs over $1B in ARR, and operates 24/7 CS ops because cyber threats do not wait for business hours. The threat landscape shifted. AI accelerated attack speed and sophistication. Attackers now move in 3 to 4 hours, logging in rather than breaking in. Sophos structured CS to respond before customers know there is a problem. By the time a support ticket arrives, you have already failed your customer. ## The Attribution Model Anania ties CS touchpoints directly to retention and expansion. No vanity metrics. She tracks which CS activities drive renewals, upsells, and churn prevention. Dynamic segmentation assigns coverage based on risk, spend, and growth potential, not just ACV hard lines. For early-stage companies without perfect data: start at the end of the renewal cycle. Automate what you can measure. Crawl, walk, run. ## Structure and Scale Sophos uses a two-by-two matrix: customer risk versus revenue potential. High-touch CSMs for enterprise accounts showing growth signals. Digital-led motions for stable mid-market. The customer should never feel your org chart. Anania hires for "humble confidence", a specific combination of expertise without ego. Her 5-to-1 scorecard evaluates how CS earns trust over time. Inner and outer feedback loops turn NPS data into cross-functional action, not just a CS slide. ## ANZ Context Australia ranks among top countries for Sophos adoption. The company maintains ANZ presence with global 24/7 operations supporting the region. No specific ANZ headcount disclosed, but rapid MDR expansion (37% customer growth in 2024, 26,000+ MDR customers globally) suggests scaling in customer-facing ops. Sophos holds #1 rankings in G2's 2026 reports for Endpoint Protection, XDR, MDR, and Firewall across enterprise, mid-market, and SMB segments. Privately held following management buyout. Competing in a cybersecurity market projected to hit $267.7B by 2026. ## What This Means Retention is an all-company play. CS attribution models tie activity to revenue. Dynamic segmentation beats rigid ACV lines. If you are building CS at scale: measure what moves the number, automate the repeatable, and structure coverage around customer outcomes, not your reporting lines.
AI SDR deployment takes 60 days of real work, not the 3 days vendors quote you. The tech is live fast. The training that makes it perform like your best rep takes 60 days of focused effort. Most companies skip the training. That is why most AI SDR deployments fail. ## Week 1-2: Foundation work (2-3 hours daily) Pull 50+ real conversations from your best BDR. Not scripts. Actual conversations, exact tone, real objection handling. Feed the AI your product knowledge: customer data, past conversations, why anyone should care. Read every message the AI sends. Every one. Flag anything robotic or off-brand immediately. Most teams stop reading after day three. That is where it goes wrong. ## Week 3-4: Optimisation (1-2 hours daily) One variable at a time. Subject lines, CTAs, send timing, opening lines. Not all at once. The bar: is this response better than what your best rep would say? Not better than a mediocre rep. Better than your best one. Track which approaches get replies. The data will tell you things your instincts will not. ## Month 2+: Maintenance (30-60 minutes daily) By now the AI is performing. Your job shifts to catching edge cases, refreshing the knowledge base as your product changes, tightening guardrails based on real conversations. This is not set-it-and-forget-it. It is lighter-touch, but still real attention. ## Why most deployments fail 90% of companies skip the training work. They deploy, wait two weeks, see mediocre results, conclude AI SDRs do not work. They are wrong about the conclusion. They are right that it did not work. It did not work because they did not train it. Best-performing deployments share one thing: the team invested heavily in the first 60 days alongside the vendor. The vendors who actually help show up for 80% of that heavy lifting. They do not just hand you a login and a tutorial video. ## The actual timeline - Days 1-7: Technical deployment, data ingestion, initial config. Live quickly. - Days 8-30: Foundation training. Daily, intensive, non-negotiable. - Days 31-60: Optimisation. A/B testing, voice refinement, performance analysis. - Day 61+: Ongoing maintenance. Lighter lift, but still requires attention. Total time to a well-trained, high-performing AI SDR: 60 days if you do the work. Six months of frustration and a vendor switch if you don't. ## ANZ context This timeline matters more in ANZ markets where AI SDR adoption is tracking 6-12 months behind US deployments. Local teams asking about AI SDR ROI need to factor in the real 60-day ramp, not the 3-day vendor pitch. That changes the cost comparison versus hiring another human SDR on $80k base. The tools are not magic. The training is the product. *Source: SaaStr, Jason Lemkin*
## Rumin8 raises $4.3m, expands to NZ: agtech hiring watch Perth-based Rumin8 closed US$3 million ($4.3m AUD) from New Zealand investor AgriZeroNZ to expand its livestock methane reduction business across the Tasman. The startup develops feed additives that cut cattle emissions while claiming to boost production and farm profitability. Founded in 2021, Rumin8 started with seaweed-based solutions but pivoted to what it calls "nature-inspired pharmaceutical ingredients." The company aims to decarbonise 100 million cattle by 2030. Big goal, now entering final commercial trials. ### The funding context This follows a $17m seed round in 2023 that brought in Bill Gates via Breakthrough Energy Ventures and Twiggy Forrest through Harvest Road Group. Other backers include Aware Super Sentient WA Growth Fund and Prelude Ventures. Total funding not disclosed, but the company is clearly raising to scale. ### What this means for sales No sales team hiring announced yet, but worth tracking. NZ expansion usually means local market entry: think regional AEs, partnerships, potentially field sales given the agtech vertical. Dairy is New Zealand's largest export, so the addressable market justifies boots on the ground. Agtech sales cycles run long (12-18 months is common for farm inputs), and closing farmers requires product validation and local relationships. If Rumin8 follows the playbook, expect NZ-based commercial roles once trials wrap. ### Agtech hiring patterns Recently funded agtech startups typically hire sales 6-12 months post-raise, after product-market fit validation. Comp in agtech lags pure SaaS (enterprise AE OTE in agtech sits around $140k-160k vs $180k+ in tech), but territory sizes can be massive in ANZ given farm distribution. Competitors in the livestock emissions space include ASX-listed Sea Forest and CSIRO spinout FutureFeed. Rumin8's pharma-ingredient angle differentiates, but it is still selling into conservative farming budgets. CEO David Messina mentioned aligning with commercial partners in target markets. Translation: channel strategy likely, which could mean partner account management roles rather than direct field sales initially. No public data on current headcount or sales org structure. Watch for NZ commercial lead appointments in Q2-Q3 2026 if trials progress.
## ACS cuts executives two weeks into new CEO transition Dr Prins Ralston wasted no time. Two weeks into his role as CEO of the Australian Computer Society, he cut multiple executive positions. "A number of executive roles are being made redundant," Ralston told staff in a Tuesday email. "These are realignment decisions, driven by the need for a leaner and more appropriately focused organisation, not a reflection of the individuals involved." The ACS management committee approved the executive restructure on Monday. An all-staff meeting followed Wednesday. Ralston is the fourth ACS CEO in six years. He replaced Josh Griggs, who left suddenly after 18 months in March 2026. Griggs ran his own leadership purge during his tenure, shutting Melbourne's Bay City Labs and Brisbane's River City Labs in favour of a virtual offering. ### What the restructure looks like Operations director Betsy Gregg now reports directly to Ralston, overseeing Strategic Initiative Executives and their boards. Member Products and Services is being established as a new function under Enzo Cocotti, reporting to the CEO. Shared Services, led by CFO Wynand de Wet, now includes Sydney's Harbour City Labs, though ACS did not confirm whether that facility will remain open. ### More cuts coming "I want to be honest with you: this is the beginning of a transition, not the end of it," Ralston told staff. "There will be further decisions ahead as we shape ACS for the future as external factors such as the 26/27 Federal budget is announced." Ralston outlined priorities: member focus, operational efficiency, and growth in AI and cyber security. ACS recently received a $1.9 million federal government grant to co-design a voluntary national Cyber Security Professionalisation Scheme. ### What this means New CEOs often restructure in the first 90 days. What is notable here is the speed and the acknowledgement that more cuts are coming. Ralston signalled budget pressures and a need to streamline before growing. For sales professionals considering tech association roles or membership org sales positions, this is a reminder: non-profit does not mean stable. CEO transitions often mean executive churn, territory changes, and quota resets. ACS did not respond to questions about total headcount impact or specifics on which executive roles were cut.
## The Numbers Halter raised $314.4 million Series E led by Founders Fund, valuing the NZ agtech at $2.9 billion. That is 3x their Series D valuation from June 2025, when they hit $1 billion on a $100 million raise. The company now has 1 million solar-powered GPS collars deployed across 2,000+ cattle farms in New Zealand, Australia, and the US. ## What This Means for Sales Teams Series E at this scale typically signals aggressive go-to-market expansion. Halter already employs 300+ people and operates on a subscription model: monthly fees per cow per collar. They expanded into the US in 2024 and are targeting UK, Ireland, and South America next. For context: Halter reported $17.5 million revenue with 600,000+ collars across 1,000+ customers as of 2024. The math suggests they are scaling fast, which means territory expansion and quota changes for existing reps. ## The Funding Stack Founders Fund led, with participation from Blackbird Ventures (Australia), DCVC, Bond, Bessemer, and others. Rocket Lab founder Peter Beck is an investor and board member. Andrew Fraser serves as President. ## Market Context Halter won NZ's Deloitte Fast 50 as the country's fastest-growing company in 2024. The company was founded in 2016 by Craig Piggott, who left Rocket Lab to build tech he saw his family's Waikato dairy farm needed. The product: virtual fencing via collar that uses audio cues and vibrations to herd cattle, controlled via smartphone app. US farmers have built nearly 100,000 kilometres of virtual fencing since Halter's 2024 launch there. That adoption rate matters if you are tracking agtech sales cycles and enterprise deployment timelines. ## What We Are Watching Geographic expansion plans, particularly UK and Ireland rollout timing. Sales team buildout in new territories. Comp structures for AEs selling into agriculture, which historically has different sales cycles than SaaS. Whether the subscription model scales as they move from early adopters to mainstream dairy operations. Worth noting: agtech sales often require longer educational cycles and hands-on demonstrations. If they are hiring into new markets, expect field-heavy roles with territory ownership.
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