You are about to audit the wrong layer. Everyone tests the AI model. Almost no one tests the data it runs on. LeanData 2026: 82% say clean data before AI. Only 26% can enforce it. A perfect model on unowned data just fails faster. phronetos.com/diagnostic

45% of marketing leaders say their AI agents already failed them. The model isn't the problem. 82% know clean data must come before AI. Only 26% can enforce it (LeanData, 2026). Your agent runs through that gap at machine speed. Buy the model last.

Your next customer may not be human. On June 23–25, leading CXOs, AI builders, VCs, and analysts will explore what this means for GTM. Free/virtual: hardskill.exchange/summit/ag… @briansolis @chiefmartec @jonmiller @Carles_Reina @AmandaKahlow @nbogaty @medinism @leoboulton @douglandis @GainsightHQ @TTC_Sandler_PHL @Vivun_Inc @LeanData

【保存版】 Anthropicが自社の営業組織を30日でAI化した話、記憶設計の観点で読むとかなり面白い😳 ここがポイント👇 x.com/jasonlk/status/2057197… Anthropicがやったこと： ・Clay / LeanData / Salesforce / Gong / Ironclad / Slack の6つのツールをClaudeで繋ぐ ・全ツールから文脈を引き出す "morning brief" Skillを構築 ・担当者は毎朝「今日の文脈」を持った状態で動き始める 新ツールは1つも買っていない。 既存スタックにClaudeを通しただけ。 結果、2026年の新規エンタープライズ契約の54%がセルフサーブ経由になった。 複数ツールに分散した情報をClaudeが毎朝束ねる仕組みを作ると、AIは「今日の文脈を知っている参謀」として動き始める。 Anthropicがやったのはこれを自社の営業組織で実装したということで、個人のObsidian Vault設計にそのまま応用できる話だ。 保存して、自分のVaultで「分散した情報を毎日束ねる仕組み」があるかを点検してみてほしい。

> Anthropic — 既存スタックの「間」をClaudeで補う設計 Vercelが「自分たちで作る」アプローチを取るのに対し Anthropicは、既存スタック（Clay・LeanData・Salesforce・Gong・Ironclad・Slack）は捨てず そのうえでClaudeを既存ツール間に接合させ、 一連のエージェント体験を構築させている

5 Things Anthropic Did To Reboot Their GTM Motion in 2026: 1/ Launched enterprise self-serve MVP in January, production in February. Built the funnel with Intercom Fin guiding buyers through real enterprise plans with real ACV and terms of service. 54% of new enterprise logos in 2026 came through this funnel. 2/ Threaded Claude through their existing 6-tool stack instead of replacing anything Clay for enrichment. LeanData for routing. Salesforce as system of record. Gong for call coaching. Ironclad for contracts. Slack for coordination. Claude became the connective tissue between them. 3/ Made Slack the front door for every support function Deal desk, legal, RevOps, billing, compliance. Slack ticket in, Claude triages, Jira ticket out. Resolves inline if it matches precedent. Escalates with full context if it doesn’t. 4/ Codified their best reps as 5 Skills every new hire gets day one Morning brief, call prep, customer follow-up, competitive intel, create-an-asset. AEs summon them with a / shortcut. Replaces the 6-week onboarding curve with a sales plug-in. 5/ Killed quotas Switched to “shadow targets” because model intelligence drives adoption faster than any quota cycle can keep up with. Kelly Loftus, Head of Startup Sales: “It’s really hard to predict what is happening. The adoption is fast.”

10 things to steal from Anthropic’s AI-native sales playbook, per Eleanor Dorfman at SaaSt 2026: 1/ Anthropic just hit $30B in annualized revenue with ~5,000 employees. Google needed 32,000 to reach $30B. Salesforce needed 79,000. The most efficient B2B company ever built. 2/ They run on the same stack you do. Salesforce. Gong. Slack. Ironclad. Clay. LeanData. They didn’t replace anything. They threaded Claude through the seams. 3/ 18 quota-carrying enterprise AEs serving 300,000 business customers. 16,667 customers per rep. 500 now spend $1M annually, up from ~12 two years ago. 4/ 54% of new enterprise logos in 2026 came through self-serve. Real ACV. Real terms of service. No AE-led journey. Intercom Fin guides the buyer end-to-end. 5/ They killed the PLG-vs-SLG orthodoxy in January. Enterprise self-serve isn’t a consolation prize for buyers who don’t deserve a human. It’s where most logos come from now. 6/ Slack became the front door for every support function. Ticket in, Claude triages, Jira ticket out. Deal desk, legal, RevOps, billing all run through one entry point. 7/ Codified the best reps as 5 Skills every new hire gets on day 1: morning brief, call prep, customer follow-up, competitive intel, create-an-asset. No more 6-week onboarding curve. 8/ ICONIQ 2026: high AI adopters now generate 2x net new revenue per GTM FTE. The biggest gap isn’t in Sales ( 20%). It’s in Post-Sales ( 83%). AI CSMs are the most underleveraged role. 9/ SDRs are already at 71% daily AI adoption. RevOps jumped from 34% to 54% in one year. Median company is planning 0% RevOps headcount growth in 2026. 10/ Anthropic doesn’t even use quotas anymore. “We have shadow targets. Adoption is driven by model intelligence, which you cannot predict.” If the leading AI lab can’t tie revenue to seat capacity, your customers can’t either. The B2B sales stack didn’t get disrupted. It got compressed.

「AIエージェント導入、社内で何度議論しても結論が出ない」 「PoCは動くけど本番でスケールしない」 「米国の事例を見るたびに焦るけど、何をどの順序でやればいいのか分からない」 この日本企業のAI戦略担当者が抱える根本的な不安に対し、この投稿では、「ようやく本物のエージェント時代が始まった年」として現地で観測した米国GTM最前線をまとめた決定的なレポが記載されています。 中心メッセージはSaaStr CEO Jason Lemkin氏のキーノートに凝縮されています。 > If you build the best agent... maybe we will have agent parity in 36 months, maybe even in 24 months. Today there is not agentic parity... The agent performance is so disparate that the best agents are just gonna win over the next 12 months. 24〜36ヶ月後にはAgent Parity（エージェント実装精度の横並び）が必ず来る。 だから今後12ヶ月で勝負を決めろ。 2025年のSaaStrが"とにかく動け"という空気感だったのに対し、2026年は「なぜSpeedが必要か、何を取りに行くべきか」が具体戦略として語られるようになった——これが最大の変化です。 現地で衝撃を受けた3つの具体的事例が紹介されています。 第一に、Vercel — SDRを10名から1名に削減。 Jeanne DeWitt Grosser COO主導のGTM Engineeringチームが構築したリード資格判定エージェントは、年$5,000のインフラ エンジニア1人の20%工数で10人分の業務を24/7で運用。 コスト効率32倍。 GTMエンジニア×データサイエンティスト×ベストパフォーマーの「Tripod model」がベストプラクティスをエージェントにエンコードする標準型です。 第二に、Anthropic — 既存6コアツールの「間をClaudeで縫う」。 Clay/LeanData/Salesforce/Gong/Ironclad/Slackを捨てず、Claudeを既存ツール間に接合させる戦略で、新規エンタープライズロゴの54%を人間営業を通さずself-serveで獲得。 「It isn't a new stack — it's being intentional about your existing stack」。 第三に、Databricks Unity Catalog Business SemanticsのGA。 VercelのJeanne氏の言葉「The agents you build will only be as good as the data underneath them」が示すように、AIエージェントの品質はその下のデータ品質を超えない。 セマンティックレイヤー（business semantic layer）を一箇所に置けるか否かが、AI駆動GTMの見えない大黒柱になります。 日本企業の経営層・事業責任者が今すぐ握るべき3つの含意があります。 第一に、「いつAIを導入するか」ではなく「2027年末までにカテゴリ第一想起を取れるか」で戦略を組み直すこと。 Monacoはステルス解除3ヶ月でシリーズB $50M SaaStr会場上空に飛行船という極端なSpeed戦略を実行。 Agent Parityが来る前の12ヶ月で「カテゴリリーダー認知」「業務深部への入り込み」「実例によるデータフライホイール起点」の3つを押さえた企業に需要が集中します。 第二に、「AIで人を減らす」ではなく「Atlassian型のジュニア厚く・シニア厚く・ミドル薄く」で組織を再設計すること。 AI導入提案で「ミドル削減」を強調するのは逆効果。 ジュニアのAI実験速度（シニアより18-30%高い）とシニアの「AI slopを見抜く力」を相互学習させる組織が勝ちます。 第三に、シリーズA基準が「PMF 健全な粗利率」に上がった現実を直視すること。 AIスタートアップは推論コスト赤字でseed 2/3/4を重ねている。 投資家は「Speed（年4倍）」と「Unit Economics（粗利）」の両方を見ています。 toB AIプロダクトの単価設計・推論コスト最適化が、これからは投資家評価の中核です。

SPONSORED: Aligning Go-to-Market Execution with Strategy to Better Address Complex Buyer Journeys report from @LeanData s.hbr.org/4dsqC9o

Expertise AI now integrates with @LeanData. This allows revenue teams to route conversations and leads using their existing LeanData logic while capturing richer intent and context from the website. Learn more about how Expertise AI works with LeanData: expertise.ai/integrations/le…

We’re live at @Dreamforce 2025🚀 Meet our Informa TechTarget team at Booth 514 and join us tonight for our exclusive happy hour with LeanData and OpFocus! We can't wait to see you tonight: 📍 The Treasury @ 200 Bush Street ⏰ 5:30 PM Enjoy craft cocktails, smart conversations, and great connections among the industry’s best. Register here: bit.ly/3Wss0Pl #Dreamforce2025 #DF25

Your GTM isn't a mess - it's a symphony. We've partnered with the masters of orchestration, @LeanData and @fullcast_com to help you conduct a masterpiece. Join us at Revolt to design flawless GTM workflows and align your entire revenue operation. Link in bio! 🎶

All revenue that is not performance marketing revenue is brand revenue. Anything that's not directly from performance marketing ads or SEO should get counted as brand traffic. We know brand works, there's a myriad of studies: - 86 % already have a Day-1 list of vendors at the very start of the journey, 92 % ultimately buy from that Day-1 list (Google × Bain) - 90 % of deals are won by vendors that were in the buyer’s initial consideration set (Corporate Visions 2025) - Brand awareness increases performance marketing conversion rates up to 2.86x (Tracksuite) - Brand size is a 20x multiplier of advertising profitability/ROI (Paul Dyson, Drivers of Advertising Profitability 2023) - Inbound deals close about 25 % better than outbound (LeanData Salesforce) - Inbound converts 1.7× higher and closes 28 days faster (HockeyStack Labs) ... but it gets shat on by executives when doing ROI math, looking for 30-to-60-day returns. ROI works when the money spent and the return happen at clear, defined moments. Brand marketing doesn’t behave that way. Yes, you should absolutely track share of search (for the 5% in market). Mid-sized and large brands need to run quarterly brand tracking surveys to measure awareness/preference/perception. But neither of those will tell you how much money brand made you -- which is what the CFO and CEO want to know. And this is why brand marketing investments get cut, resulting in poor pipeline in the future. Hence: all revenue that is not performance marketing revenue is brand revenue. It isn’t perfect science, but attributing every dollar that doesn’t come from performance clicks to ‘brand’ gets you 80 % of the truth with 20 % of the effort. Good enough for strategic decisions, and far more actionable than a multi-touch waterfall nobody trusts. Treating every dollar that isn't direct-response as brand revenue captures about 85 % of reality and gives execs a simple, repeatable gauge of brand ROI.

#البيانات_الذكية #LeanData هي منهجية حديثة في #البيانات. تهدف إلى الحصول على أقصى قيمة إدارية من البيانات بأعلى كفاءة ممكنة وتقليل الهدر. بدأت قصتها بممارسات تطبقها منظمة أكيومن على دراسات قياس الأثر، وحولتها بتوفيق الله في هذا الكتاب إلى منهجية متكاملة يمكن تطبيقها في مختلف القطاعات. أتممت بفضل الله تأليفه بعد رحلة من التعلم والعمل دامت آلاف الساعات مع عشرات المؤسسات، أضعه الآن بين يدكم ليحقق قفزة في استفادتكم من البيانات، جزيل الشكر والتقدير للجنة التحكيم الذين ساهموا معي في إيصال هذا العلم إلى العالم العربي: cutt.ly/LrqO6H57

25 top marketing softwares by category (no particular order) Here are my recommendations: 1. Google Analytics - Web Analytics 2. WordPress - CMS 3. Unbounce - landing pages 4. Sprout Social, Inc. - Social Media 5. Ahrefs - SEO 6. Drift - Conversational Marketing/Chatbot 7. Clearbit or ZoomInfo - Data Enrichment 8. Marketo, an Adobe Company, HubSpot or Mailchimp 9. Salesforce - CRM 10. Outreach - Sales Automation 11. Gong - Call Intelligence 12. Tableau Software - business intelligence 13. LeanData, Inc. - lead management 14. Segment – customer data infrastructure 15. Hotjar - Heatmapping 16. Intellimize - Web A/B testing 17. Sendoso - Direct Mail Automation 18. Chili Piper - booking tool 19. Clari - Revenue Ops platform 20. Asana or Airtable - Project Management 21. Canva - design tool 22. Zapier - integration tool 23. SurveyMonkey - surveys 24. Google Ads - Ad tech 25. Facebook Ads/LinkedIn Ads - Social Ads What would you add or remove? PS. You don't need all of these tools to be successful. #marketing

3/ Register for free: bit.ly/4c0neOr cc: @LeanData @SapphireVC #OpsStars24 #MarketingOps #SalesOps #RevOps #SalesAI #PipelineGeneration #AISDRs

We’re excited to sponsor the 9th annual OpsStars Conference in San Francisco on 9/18 and we can't wait to see you there 👋 LeanData #OpsStars #MarketingOps #SalesOps #RevOps

The #1 question at @ycombinator retreat was “How do we crack Sales?” I’ve compiled a list of best practices in Sales & RevOps for technical founders incl. comps of different SaaS tools to close more deals 💸💸: Note: your stack will vary based on 1. revenue maturity 2. main revenue motion (plg, sales-led, etc.) 3. revenue model (usage based, enterprise contracts, etc.) 💼 Small startup (<10 people): attio (crm), notion (track tasks/docs), apollo (email/cold call outbound), gmass (marketing campaigns), warmly (inbound tracker), posthog (user analytics), new digital worker startups like artisan, topo, and aisdr 📈 Preparing to Scale: 💥 CRM: Hubspot: great for individual items, per seat, or platform fee biz model, doesn’t scale well after $10M ARR, reporting is bad Salesforce: good for usage-based pricing, best to use as system of record and system of work b/c when decoupled, one is always trying to catch up to other so it’s harder to make business decisions ✍️ Personalized Outbound: Clay: gained popularity recently, scrapes websites and uses ai to create mass personalization Unify: contains email solution too Apollo: vertical integration of zoominfo gong clari 🧑‍🧑‍🧒‍🧒 Community Management: Common Room 🙋‍♀️ Sourcing: ZoomInfo 💰Revenue Intelligence: Gong Clari 🤝 Intent tracking: Segment: real-time insights into customer data Koala 📝 Meeting Notes: Fathom.video: great zoom meeting replay Read.ai: good summaries Fireflies.ai Otter.ai 🗒️Inbound form filling / lead-to-account matching: Default: most robust Calendly Chilipepper LeanData: complex to use RevenueHero 📧 Email automation: Superhuman Loops 👩‍💻 SEO: Daydream 👣 User tracking: Amplitude: detailed analytics Mixpanel: user engagement and retention with event-based tracking and segmentation FullStory: Specializes in session replay and visualizing the user experience to improve digital experiences Posthog: self-hosted option

Founded in 1977, Oracle quickly became a global leader in database software and technology. Today the company employs 159,000 people, many of which go on to become successful tech founders. Oracle alumni have founded 892 companies founded and $42 billion raised so far. Today, we highlight some of the top founders & startups (more in the full article at the link in the comments): 📌 1. FourKites, Inc. Founder: @mathewmje Oracle Role: Principal Consultant 📌 2. CAST AI Founder: Laurent Gil, Leon Kuperman Oracle Role: Group Architect, Vice President 📌 3. SalesHood Founder: @elaycohen Oracle Role: CRM Product Director 📌 4. 11Sight Founder: @AleksGollu Oracle Role: Software Engineer 📌 5. ecomedes Founder: Hung Vo, @kegan2050 Oracle Role: Vice President, Senior Director Global Sales Consulting 📌 6. Xignite Founder: @stephdubois Oracle Role: Product Manager 📌 7. MATRIXX Software Founder: Dave Labuda, @JenniferMatrixx Oracle Role: SVP, Communications Business Unit, Director, Product Solutions 📌 8. B GARAGE Founder: Aiden Kim Oracle Role: Senior Software Engineer 📌 9. Workato Founder: @vijaytella Oracle Role: Chief Strategy Officer, Fusion Middleware 📌 10. LeanData Founder: Kevin Cheung Oracle Role: Member of Technical Staff If there's anyone we've missed, tag them below. 👇 ❗Quick plug: Are you an Oracle Mafia member interested in bringing your community together to invest in innovative ventures (and enjoy potential profits and other perks along the way)? Or perhaps you're part of another dynamic group that could be a fantastic source of startup investments? 😉 Then sign up to our waitlist. getpin.xyz/ #startups #techmafia #oracle