Podcasts about saas b2b

En este episodio de SaaStulia, nos juntamos con Ignacio Arriaga (Acumbamail) y Miguel Sanz (Estudio Bisiesto) para charlar sobre los grandes retos y cambios que está viviendo el mundo del SaaS:

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Come Lanciare una App: TabUi, l'App che sta rivoluzionando il turismo locale con la realtà aumentata!In questo nuovo episodio del Marketing Garage, Gianluca Testa incontra Giorgio Proglio, imprenditore visionario e creatore di TabUi, l'app che valorizza il patrimonio culturale dei piccoli comuni italiani con l'uso intelligente della realtà aumentata ✨.======Questa intervista è offerta da BeBoom, la piattaforma SaaS B2B che aiuta le aziende a fidelizzare i clienti e far crescere le vendite. Compila il form per avere maggiori informazioni: https://app.beboom.io/it/tryMe.php=====

#265 Non-SaaS Marketing | In this episode, Matt sits down with Sandra Rand, a fractional head of marketing who works with early-stage, non-SaaS B2B companies. She's led marketing for PE-backed, self-funded, and services-based businesses, where big budgets and SaaS-style playbooks aren't the norm. She's also building the Non-SaaS Marketers subgroup inside Exit Five to support others facing the same challenges.Matt and Sandra cover:How non-SaaS teams drive growth without demos, PLG, or huge lead volumeWhy events, word of mouth, and referrals often outperform funnels in these orgsTactical ideas for gifting, partnerships, and pipeline-building on a lean budgetWhether you work in SaaS or not, you'll walk away with creative, scrappy strategies to build trust and drive results in B2B.Timestamps(00:00) - – Intro (03:04) - – Why Exit Five launched the Non-SaaS group (08:24) - – What makes non-SaaS marketing different (11:44) - – Budgets, sales cycles, and team structure (16:34) - – Why brand and trust matter more (18:44) - – Events > funnels in non-SaaS (28:40) - – How to build brand on a budget (34:10) - – Word-of-mouth and referral tactics (38:50) - – Gifting and relationship-driven growth (44:50) - – Scrappy, creative plays that actually work (50:20) - – What's next for the Non-SaaS community Send guest pitches and ideas to hi@exitfive.comJoin the Exit Five Newsletter here: https://www.exitfive.com/newsletterCheck out the Exit Five job board: https://jobs.exitfive.com/Become an Exit Five member: https://community.exitfive.com/checkout/exit-five-membership***Today's episode is brought to you by Zuddl.We're halfway through 2025, and one thing's clear: events continue to be one of the highest performing marketing channels. Niche meetups, conferences, curated dinners, networking - you name it. Everyone's leaning in.Events are a core part of our playbook this year at Exit Five. So far, we've hosted two virtual sessions each month, one large virtual event, one in-person meetup, and we're deep in the weeds planning our Drive conference coming back to Vermont this September.Zuddl helps us run a smarter event strategy - from driving registrations, managing invites, automating comms, reminders, analytics, tracking. Their Salesforce integration also makes it simple to report on pipeline and revenue from events without pulling in ops.On top of that, the differentiator with Zuddl is how their team is insanely good at supporting us. They always go above and beyond for us - and that's how we've been able to keep the momentum going with 12+ events already this year, with plenty more to come.If events are part of your marketing strategy, you need to look at Zuddl to see how companies like Zillow, CrowdStrike, and Iterable are using the top event platform for Business events in 2025. Head over to zuddl.com/exitfive to learn more. 

En este episodio, conversé con Diego Morales, fundador de Rocket Revenue y referente en crecimiento para startups B2B en Latinoamérica. Hablamos de todo lo que un SaaS necesita para escalar: desde encontrar el product market fit, hasta generar awareness, construir pipeline y medir las métricas correctas.Diego compartió estrategias prácticas para founders que están comenzando, explicando cómo usar contenidos, performance marketing e influencers para crecer sin derrochar presupuesto.También explicó por qué las plataformas como Capterra y G2 son fundamentales para startups B2B, cómo funciona la expansión en clientes actuales, y qué indicadores financieros son clave para escalar con inteligencia.Cerramos el episodio con sus herramientas de marketing favoritas y una reflexión sobre cómo construir equipos de revenue que realmente funcionen.

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Pour l'épisode de cette semaine, je reçois Guilhem Bertholet, CEO et cofondateur d'Invox, une agence spécialisée dans le marketing B2B.Guilhem était déjà passé sur le podcast dans l'épisode #101 pour parler de content marketing. Cette fois-ci, on revient ensemble sur un sujet plus large : la demand generation, un concept encore émergent en France mais central dans les stratégies marketing des SaaS B2B.Dans cet épisode, Guilhem explique les différences entre content marketing et demand generation, pourquoi il est crucial d'éduquer ses prospects bien en amont de la décision d'achat, et comment structurer une stratégie pérenne : quels contenus produire, sur quels canaux, avec quels outils, et sur quels horizons de temps.On a aussi parlé de son retour d'expérience avec la vidéo, de la place de l'IA dans les stratégies marketing, et de Demand Generation, la conférence qu'il organise à Lyon le 1er juillet, dédiée à la demand generation B2B.Vous pouvez suivre Guilhem sur LinkedIn et découvrir la conférence sur demandgeneration.fr.Bonne écoute !Mentionnés pendant l'épisode :InvoxDemand GenerationSubmagicÉpisode #101 de SaaS Connection avec GuilhemPour soutenir SaaS Connection en 1 minute⏱ (et 2 secondes) :Abonnez-vous à SaaS Connection sur votre plateforme préférée pour ne rater aucun épisode

Invité : Gaspard Pastural, consultant en marketing spécialisé dans le positionnement et le messaging pour les entreprises SaaS B2BDans cet épisode, je m'entretiens avec Gaspard Pastural, consultant en marketing spécialisé dans le positionnement et le messaging pour les entreprises SaaS B2B. Gaspard expose son approche pour aider les startups et PME à clarifier leur message sur le marché, tout en mettant en avant les différences observées chez les entreprises francophones par rapport aux entreprises anglophones. Nous discutons des notions clés de positionnement et de messaging, des défis que rencontrent souvent les entreprises, ainsi que de l'importance d'une vision à long terme en marketing. Gaspard souligne la nécessité d'une structure web efficace et partage des conseils sur l'interaction avec les clients pour mieux comprendre leurs besoins. Il insiste également sur l'importance de cibler efficacement les segments de marché pour maximiser la valeur et établir un messaging percutant.Au menu de cette conversation entre Gaspard et Mony :0:04 Introduction0:57 Comprendre le Positionnement et le Messaging2:16 Problèmes Courants dans le B2B4:46 Vision à Long Terme en Marketing5:45 Importance des Interviews Clients12:46 Stratégies pour Améliorer le Positionnement15:27 Signes d'Alerte pour les Entreprises20:46 Optimisation du Site Web26:07 Campagnes d'Outbound et Contenu29:55 Priorisation des Cibles en Marketing32:17 Conclusion et Ressources de ContactRéférences :LinkedIn de Gaspard:https://www.linkedin.com/in/gaspardpastural/--⚡ Connecte-toi à Mony⁠ ⁠⁠⁠⁠ici⁠⁠⁠⁠⁠.Je suis Mony Chhim et je suis freelance LinkedIn Ads pour entreprises B2B (45+ clients accélérés)

Pour en savoir plus sur Hellodarwin : https://go.hellodarwin.com/hypercroissance?utm_source=helloDarwin&utm_medium=podcast&utm_campaign=grants-hypercroissanceComment Connect&Go a généré 1 milliard en transactions et atteint 10M$ en revenus SaaSDans cet épisode d'Hypercroissance, on reçoit Dominic Gagnon, président de Connect&Go, une scale-up montréalaise qui a su pivoter d'un modèle événementiel vers une plateforme SaaS B2B ultra-performante. En seulement 4 ans, l'entreprise a dépassé les 10M$ de revenus et traite maintenant près de 1 milliard de dollars en volume de transactions.On plonge dans : ✅ Le virage SaaS après la pandémie : stratégie, focus client, exécution✅ Les vraies raisons derrière la rentabilité repoussée à 2025✅ Pourquoi lever des fonds peut parfois nuire à la croissance✅ Comment l'intelligence artificielle est devenue un passage obligé dans les pitchs✅ Les défis de scaler une entreprise avec moins de 100 clients actifs✅ Ce que Dominic referait autrement… et ce qu'il refera encoreTu es entrepreneur, marketer ou fondateur d'une entreprise tech? Cet épisode est un concentré d'apprentissages sur la croissance SaaS, les réalités de marché en 2025 et les nouveaux modèles d'affaires.

Invité : Kamel Ben yacoub, CEO de l'agence GetUpLeadDans cet épisode, je reçois Kamel Ben yacoub, CEO de l'agence GetUpLead, spécialisée dans les LinkedIn Ads et Google Ads pour le secteur SaaS B2B. Nous explorons les dynamiques entre ces deux leviers publicitaires, en mettant en lumière comment déterminer leur pertinence selon les caractéristiques du marché et du public ciblé. Kamel aborde l'importance de la demande existante pour Google Ads et la flexibilité de LinkedIn, ainsi que les considérations clés pour maximiser l'efficacité des campagnes. La conversation se concentre également sur la synergie entre les deux plateformes et des conseils pratiques pour ceux qui ont des budgets limités, en insistant sur l'importance de capturer la demande tout en développant des audiences sur LinkedIn.Au menu de cette conversation entre Kamel et Mony :0:15 Introduction0:21 Présentation de Kamel1:32 Importance de LinkedIn et Google Ads3:24 Déterminer la pertinence des plateformes6:27 L'audience cible sur LinkedIn10:27 Le contenu et le cycle de vente14:21 Synergie entre les plateformes16:43 Approches différentes de Google et LinkedIn19:50 Retargeting efficace22:34 Erreurs fréquentes des utilisateurs29:43 Stratégies avec un petit budgetRéférences :LinkedIn de Kamel:https://www.linkedin.com/in/kamelbenSite web de l'agence:https://getuplead.com--⚡ Connecte-toi à Mony⁠ ⁠⁠⁠⁠ici⁠⁠⁠⁠⁠.Je suis Mony Chhim et je suis freelance LinkedIn Ads pour entreprises B2B (45+ clients accélérés)

Nouveau mois : nouvelle ronde de test Facebook Ads !Dans cette vidéo de Social Scaling, on vous présente 4 nouveaux tests à appliquer sur Facebook Ads pour de meilleurs résultats dans l'agence.Au programme : une offre ultra rentable inspirée du calendrier de l'Avent, une campagne Catalogue Ads en acquisition pour détecter les produits qui performent, des créatifs simples mais puissants pour vos lead magnets, et enfin une structure de test d'audience utilisée par un SaaS B2B à plus de 60 000 $ de budget.Chaque exemple est issu de campagnes réelles gérées par notre équipe, avec des résultats analysés à l'appui. Que vous soyez e-commerçant, infopreneur ou en B2B, ces optimisations vous donneront des idées concrètes à tester sur votre propre compte.Notre agence : https://experts.j7media.com/agence/

Pour l'épisode de cette semaine, je reçois Steven Fabre, le CEO et cofondateur de Liveblocks.Liveblocks, c'est une solution qui permet aux éditeurs de logiciels, et en particulier aux SaaS B2B, d'ajouter facilement des fonctionnalités de collaboration en temps réel et d'intelligence artificielle dans leurs produits. Cela inclut les commentaires, les notifications, la présence en temps réel ou encore les éditeurs de texte collaboratifs façon Google Docs ou Figma.Au cours de notre échange, Steven revient sur son parcours, son expérience chez InVision, et la genèse de Liveblocks, née d'un besoin rencontré en interne. On parle du positionnement produit, des briques proposées (présence, collaboration, copilote IA…), du modèle de pricing, de l'approche “best-of-suite”, mais aussi de la stratégie go-to-market et de la transition d'un produit destiné aux développeurs vers une cible plus produit et business.On évoque également sa démarche très proactive aux US : ses allers-retours réguliers à San Francisco, l'organisation de dîners avec clients et prospects, et les avantages d'être “au cœur du réacteur” tech mondial.Vous pouvez suivre Steven sur LinkedIn.Bonne écoute !Mentionnés pendant l'épisode :InVisionFigmaTipTapLexicalGuillaume Moubeche sur YouTubeLivre Positioning d'Al Ries et Jack TroutPour soutenir SaaS Connection en 1 minute⏱ (et 2 secondes) :Abonnez-vous à SaaS Connection sur votre plateforme préférée pour ne rater aucun épisode

In this weeks' Scale Your Sales Podcast episode, my guest is Jan Young.   Jan Young is the founder of JanYoungCX consultancy & coaching, StepUpXchange CS executive courses with private community & CxXchange community for CS professionals. She is an award-winning CS leader of 2 successfully exited startups. She brings her cross-disciplinary approach to SaaS B2B tech and Customer Led Growth. Jan is on a mission to transform CS Leaders into Business Leaders and align GTM teams.   In today's episode of Scale Your Sales podcast, Jan shares expertise in transforming customer success leadership and aligning go-to-market strategies for business growth. This discussion covers the critical role of CS leaders in market alignment, the impact of data integration and AI on revenue operations, and the importance of breaking down organizational silos. Jan provides insights on driving profitability in customer interactions and creating a seamless customer journey.   Welcome to Scale Your Sales Podcast, Jan Young.     Timestamps: 00:00 Aligning GTM for Customer Experience 05:16 Balancing Customer Value and Profitability 09:34 Fostering Success Through Collaboration 13:42 Shifting to Profitable, Efficient Growth 15:03 Rethinking Customer Engagement Strategies 18:42 Optimizing Customer Success Milestones 22:47 Earning Trust in Sales Delivery 26:51 Sales vs. Customer Success Gender Dynamics 28:52 CS Careers Foster Customer Relationships 31:27 Embracing AI for Business Efficiency 35:07 Adapting to Industry Transformation 38:00 Community and Courage     https://www.linkedin.com/in/jan-young-cx/ https://x.com/janyoungcx     Janice B Gordon is the award-winning Customer Growth Expert and Scale Your Sales Framework founder. She is by LinkedIn Sales 15 Innovating Sales Influencers to Follow 2021, the Top 50 Global Thought Leaders and Influencers on Customer Experience Nov 2020 and 150 Women B2B Thought Leaders You Should Follow in 2021. Janice helps companies worldwide to reimagine revenue growth thought customer experience and sales.   Book Janice to speak virtually at your next event: https://janicebgordon.com   LinkedIn: https://www.linkedin.com/janice-b-gordon/   Twitter: https://twitter.com/JaniceBGordon   Scale Your Sales Podcast: https://scaleyoursales.co.uk/podcast   More on the blog: https://scaleyoursales.co.uk/blog   Instagram: https://www.instagram.com/janicebgordon   Facebook: https://www.facebook.com/ScaleYourSales   And more! Visit our podcast website https://scaleyoursales.co.uk/podcast/ to watch or listen.

In this episode of Pathmonk Presents, we welcome Shiro Hatori, Director of Demand Generation at Concept3D.  Concept3D is a B2B SaaS company specializing in interactive maps, virtual tours, and online event calendars for higher education institutions. Shiro shares insights on how their solutions help marketing, communications, and enrollment teams improve efficiency and enhance user experiences for students and parents. He discusses the shift in their client acquisition strategy, the launch of his own podcast, and valuable tips for B2B marketers looking to leverage podcasting for content creation, networking, and account-based marketing.  Shiro also emphasizes the importance of ethical marketing and overcoming imposter syndrome in the industry.  

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Pricing and packaging can either bog down your go-to-market engine or fuel it to peak performance.This week's SaaS Backwards podcast features Dan Balcauski, Founder and Chief Pricing Officer at Product Tranquility, a consultancy that helps high-volume B2B SaaS CEOs define pricing and packaging for new products. In this episode, Dan discusses the critical role pricing plays in a SaaS business model and why leadership teams must view it as a dynamic lever, not a "set-it-and-forget-it" element. He dispels the common myth that success hinges solely on what you charge, emphasizing instead that who and how you charge are the real determinants of success.Breaking this down, Dan walks through the four key elements of SaaS packaging: price metric, price model, offer configurations, and price fences.Our conversation also explores how to conduct a pricing study, realigning pricing strategies, AI's role in pricing decisions, and the ever-debated topic: should pricing be displayed on the website?This episode offers actionable insights for SaaS leaders looking to harness pricing as a powerful tool for growth and market alignment.Key takeaways from this episode:The impact of pricing and packaging on revenue, profitability, and valuationWhy pricing is a critical lever for growth in SaaS businesses that shouldn't be overlookedSigns a new CMO or CRO should look for to determine if pricing needs attention at a prospective employerOther resources to check out:Interview with Vinay Bhagat, Founder and CEO of TrustRadius who publishes a yearly report about how B2B buyer behavior is changing.The Lead Gen Mistake I Guarantee You're Making – how to create content that better identifies intent from today's b2b buyer.And, if you want an outside look at your content with actionable advice, take advantage of our Content Audit. Valued at $20K in free consulting---Thanks for listening to the SaaS Backwards Podcast, brought to you by Austin Lawrence Group. We help SaaS firms reduce churn, accelerate sales, and generate demand. Learn more at AustinLawrence.com.---Is your messaging a sales ally or sneaky saboteur? Let us help with our free messaging audit.We'll look at your website's messaging, content, and conversion potential from the eyes of today's buyer and deliver a presentation with new combinations to more sales conversations and demos. And the best part? It's absolutely free. Get started today!

We are recording our next big recap episode and taking questions! Submit questions and messages on Speakpipe here for a chance to appear on the show!Also subscribe to our calendar for our Singapore, NeurIPS, and all upcoming meetups!In our first ever episode with Logan Kilpatrick we called out the two hottest LLM frameworks at the time: LangChain and Dust. We've had Harrison from LangChain on twice (as a guest and as a co-host), and we've now finally come full circle as Stanislas from Dust joined us in the studio.After stints at Oracle and Stripe, Stan had joined OpenAI to work on mathematical reasoning capabilities. He describes his time at OpenAI as "the PhD I always wanted to do" while acknowledging the challenges of research work: "You're digging into a field all day long for weeks and weeks, and you find something, you get super excited for 12 seconds. And at the 13 seconds, you're like, 'oh, yeah, that was obvious.' And you go back to digging." This experience, combined with early access to GPT-4's capabilities, shaped his decision to start Dust: "If we believe in AGI and if we believe the timelines might not be too long, it's actually the last train leaving the station to start a company. After that, it's going to be computers all the way down."The History of DustDust's journey can be broken down into three phases:* Developer Framework (2022): Initially positioned as a competitor to LangChain, Dust started as a developer tooling platform. While both were open source, their approaches differed – LangChain focused on broad community adoption and integration as a pure developer experience, while Dust emphasized UI-driven development and better observability that wasn't just `print` statements.* Browser Extension (Early 2023): The company pivoted to building XP1, a browser extension that could interact with web content. This experiment helped validate user interaction patterns with AI, even while using less capable models than GPT-4.* Enterprise Platform (Current): Today, Dust has evolved into an infrastructure platform for deploying AI agents within companies, with impressive metrics like 88% daily active users in some deployments.The Case for Being HorizontalThe big discussion for early stage companies today is whether or not to be horizontal or vertical. Since models are so good at general tasks, a lot of companies are building vertical products that take care of a workflow end-to-end in order to offer more value and becoming more of “Services as Software”. Dust on the other hand is a platform for the users to build their own experiences, which has had a few advantages:* Maximum Penetration: Dust reports 60-70% weekly active users across entire companies, demonstrating the potential reach of horizontal solutions rather than selling into a single team.* Emergent Use Cases: By allowing non-technical users to create agents, Dust enables use cases to emerge organically from actual business needs rather than prescribed solutions.* Infrastructure Value: The platform approach creates lasting value through maintained integrations and connections, similar to how Stripe's value lies in maintaining payment infrastructure. Rather than relying on third-party integration providers, Dust maintains its own connections to ensure proper handling of different data types and structures.The Vertical ChallengeHowever, this approach comes with trade-offs:* Harder Go-to-Market: As Stan talked about: "We spike at penetration... but it makes our go-to-market much harder. Vertical solutions have a go-to-market that is much easier because they're like, 'oh, I'm going to solve the lawyer stuff.'"* Complex Infrastructure: Building a horizontal platform requires maintaining numerous integrations and handling diverse data types appropriately – from structured Salesforce data to unstructured Notion pages. As you scale integrations, the cost of maintaining them also scales. * Product Surface Complexity: Creating an interface that's both powerful and accessible to non-technical users requires careful design decisions, down to avoiding technical terms like "system prompt" in favor of "instructions." The Future of AI PlatformsStan initially predicted we'd see the first billion-dollar single-person company in 2023 (a prediction later echoed by Sam Altman), but he's now more focused on a different milestone: billion-dollar companies with engineering teams of just 20 people, enabled by AI assistance.This vision aligns with Dust's horizontal platform approach – building the infrastructure that allows small teams to achieve outsized impact through AI augmentation. Rather than replacing entire job functions (the vertical approach), they're betting on augmenting existing workflows across organizations.Full YouTube EpisodeChapters* 00:00:00 Introductions* 00:04:33 Joining OpenAI from Paris* 00:09:54 Research evolution and compute allocation at OpenAI* 00:13:12 Working with Ilya Sutskever and OpenAI's vision* 00:15:51 Leaving OpenAI to start Dust* 00:18:15 Early focus on browser extension and WebGPT-like functionality* 00:20:20 Dust as the infrastructure for agents* 00:24:03 Challenges of building with early AI models* 00:28:17 LLMs and Workflow Automation* 00:35:28 Building dependency graphs of agents* 00:37:34 Simulating API endpoints* 00:40:41 State of AI models* 00:43:19 Running evals* 00:46:36 Challenges in building AI agents infra* 00:49:21 Buy vs. build decisions for infrastructure components* 00:51:02 Future of SaaS and AI's Impact on Software* 00:53:07 The single employee $1B company race* 00:56:32 Horizontal vs. vertical approaches to AI agentsTranscriptAlessio [00:00:00]: Hey everyone, welcome to the Latent Space podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co-host Swyx, founder of Smol.ai.Swyx [00:00:11]: Hey, and today we're in a studio with Stanislas, welcome.Stan [00:00:14]: Thank you very much for having me.Swyx [00:00:16]: Visiting from Paris.Stan [00:00:17]: Paris.Swyx [00:00:18]: And you have had a very distinguished career. It's very hard to summarize, but you went to college in both Ecopolytechnique and Stanford, and then you worked in a number of places, Oracle, Totems, Stripe, and then OpenAI pre-ChatGPT. We'll talk, we'll spend a little bit of time about that. About two years ago, you left OpenAI to start Dust. I think you were one of the first OpenAI alum founders.Stan [00:00:40]: Yeah, I think it was about at the same time as the Adept guys, so that first wave.Swyx [00:00:46]: Yeah, and people really loved our David episode. We love a few sort of OpenAI stories, you know, for back in the day, like we're talking about pre-recording. Probably the statute of limitations on some of those stories has expired, so you can talk a little bit more freely without them coming after you. But maybe we'll just talk about, like, what was your journey into AI? You know, you were at Stripe for almost five years, there are a lot of Stripe alums going into OpenAI. I think the Stripe culture has come into OpenAI quite a bit.Stan [00:01:11]: Yeah, so I think the buses of Stripe people really started flowing in, I guess, after ChatGPT. But, yeah, my journey into AI is a... I mean, Greg Brockman. Yeah, yeah. From Greg, of course. And Daniela, actually, back in the days, Daniela Amodei.Swyx [00:01:27]: Yes, she was COO, I mean, she is COO, yeah. She had a pretty high job at OpenAI at the time, yeah, for sure.Stan [00:01:34]: My journey started as anybody else, you're fascinated with computer science and you want to make them think, it's awesome, but it doesn't work. I mean, it was a long time ago, it was like maybe 16, so it was 25 years ago. Then the first big exposure to AI would be at Stanford, and I'm going to, like, disclose a whole lamb, because at the time it was a class taught by Andrew Ng, and there was no deep learning. It was half features for vision and a star algorithm. So it was fun. But it was the early days of deep learning. At the time, I think a few years after, it was the first project at Google. But you know, that cat face or the human face trained from many images. I went to, hesitated doing a PhD, more in systems, eventually decided to go into getting a job. Went at Oracle, started a company, did a gazillion mistakes, got acquired by Stripe, worked with Greg Buckman there. And at the end of Stripe, I started interesting myself in AI again, felt like it was the time, you had the Atari games, you had the self-driving craziness at the time. And I started exploring projects, it felt like the Atari games were incredible, but there were still games. And I was looking into exploring projects that would have an impact on the world. And so I decided to explore three things, self-driving cars, cybersecurity and AI, and math and AI. It's like I sing it by a decreasing order of impact on the world, I guess.Swyx [00:03:01]: Discovering new math would be very foundational.Stan [00:03:03]: It is extremely foundational, but it's not as direct as driving people around.Swyx [00:03:07]: Sorry, you're doing this at Stripe, you're like thinking about your next move.Stan [00:03:09]: No, it was at Stripe, kind of a bit of time where I started exploring. I did a bunch of work with friends on trying to get RC cars to drive autonomously. Almost started a company in France or Europe about self-driving trucks. We decided to not go for it because it was probably very operational. And I think the idea of the company, of the team wasn't there. And also I realized that if I wake up a day and because of a bug I wrote, I killed a family, it would be a bad experience. And so I just decided like, no, that's just too crazy. And then I explored cybersecurity with a friend. We're trying to apply transformers to cut fuzzing. So cut fuzzing, you have kind of an algorithm that goes really fast and tries to mutate the inputs of a library to find bugs. And we tried to apply a transformer to that and do reinforcement learning with the signal of how much you propagate within the binary. Didn't work at all because the transformers are so slow compared to evolutionary algorithms that it kind of didn't work. Then I started interested in math and AI and started working on SAT solving with AI. And at the same time, OpenAI was kind of starting the reasoning team that were tackling that project as well. I was in touch with Greg and eventually got in touch with Ilya and finally found my way to OpenAI. I don't know how much you want to dig into that. The way to find your way to OpenAI when you're in Paris was kind of an interesting adventure as well.Swyx [00:04:33]: Please. And I want to note, this was a two-month journey. You did all this in two months.Stan [00:04:38]: The search.Swyx [00:04:40]: Your search for your next thing, because you left in July 2019 and then you joined OpenAI in September.Stan [00:04:45]: I'm going to be ashamed to say that.Swyx [00:04:47]: You were searching before. I was searching before.Stan [00:04:49]: I mean, it's normal. No, the truth is that I moved back to Paris through Stripe and I just felt the hardship of being remote from your team nine hours away. And so it kind of freed a bit of time for me to start the exploration before. Sorry, Patrick. Sorry, John.Swyx [00:05:05]: Hopefully they're listening. So you joined OpenAI from Paris and from like, obviously you had worked with Greg, but notStan [00:05:13]: anyone else. No. Yeah. So I had worked with Greg, but not Ilya, but I had started chatting with Ilya and Ilya was kind of excited because he knew that I was a good engineer through Greg, I presume, but I was not a trained researcher, didn't do a PhD, never did research. And I started chatting and he was excited all the way to the point where he was like, hey, come pass interviews, it's going to be fun. I think he didn't care where I was, he just wanted to try working together. So I go to SF, go through the interview process, get an offer. And so I get Bob McGrew on the phone for the first time, he's like, hey, Stan, it's awesome. You've got an offer. When are you coming to SF? I'm like, hey, it's awesome. I'm not coming to the SF. I'm based in Paris and we just moved. He was like, hey, it's awesome. Well, you don't have an offer anymore. Oh, my God. No, it wasn't as hard as that. But that's basically the idea. And it took me like maybe a couple more time to keep chatting and they eventually decided to try a contractor set up. And that's how I kind of started working at OpenAI, officially as a contractor, but in practice really felt like being an employee.Swyx [00:06:14]: What did you work on?Stan [00:06:15]: So it was solely focused on math and AI. And in particular in the application, so the study of the larger grid models, mathematical reasoning capabilities, and in particular in the context of formal mathematics. The motivation was simple, transformers are very creative, but yet they do mistakes. Formal math systems are of the ability to verify a proof and the tactics they can use to solve problems are very mechanical, so you miss the creativity. And so the idea was to try to explore both together. You would get the creativity of the LLMs and the kind of verification capabilities of the formal system. A formal system, just to give a little bit of context, is a system in which a proof is a program and the formal system is a type system, a type system that is so evolved that you can verify the program. If the type checks, it means that the program is correct.Swyx [00:07:06]: Is the verification much faster than actually executing the program?Stan [00:07:12]: Verification is instantaneous, basically. So the truth is that what you code in involves tactics that may involve computation to search for solutions. So it's not instantaneous. You do have to do the computation to expand the tactics into the actual proof. The verification of the proof at the very low level is instantaneous.Swyx [00:07:32]: How quickly do you run into like, you know, halting problem PNP type things, like impossibilities where you're just like that?Stan [00:07:39]: I mean, you don't run into it at the time. It was really trying to solve very easy problems. So I think the... Can you give an example of easy? Yeah, so that's the mass benchmark that everybody knows today. The Dan Hendricks one. The Dan Hendricks one, yeah. And I think it was the low end part of the mass benchmark at the time, because that mass benchmark includes AMC problems, AMC 8, AMC 10, 12. So these are the easy ones. Then AIME problems, somewhat harder, and some IMO problems, like Crazy Arm.Swyx [00:08:07]: For our listeners, we covered this in our Benchmarks 101 episode. AMC is literally the grade of like high school, grade 8, grade 10, grade 12. So you can solve this. Just briefly to mention this, because I don't think we'll touch on this again. There's a bit of work with like Lean, and then with, you know, more recently with DeepMind doing like scoring like silver on the IMO. Any commentary on like how math has evolved from your early work to today?Stan [00:08:34]: I mean, that result is mind blowing. I mean, from my perspective, spent three years on that. At the same time, Guillaume Lampe in Paris, we were both in Paris, actually. He was at FAIR, was working on some problems. We were pushing the boundaries, and the goal was the IMO. And we cracked a few problems here and there. But the idea of getting a medal at an IMO was like just remote. So this is an impressive result. And we can, I think the DeepMind team just did a good job of scaling. I think there's nothing too magical in their approach, even if it hasn't been published. There's a Dan Silver talk from seven days ago where it goes a little bit into more details. It feels like there's nothing magical there. It's really applying reinforcement learning and scaling up the amount of data that can generate through autoformalization. So we can dig into what autoformalization means if you want.Alessio [00:09:26]: Let's talk about the tail end, maybe, of the OpenAI. So you joined, and you're like, I'm going to work on math and do all of these things. I saw on one of your blog posts, you mentioned you fine-tuned over 10,000 models at OpenAI using 10 million A100 hours. How did the research evolve from the GPD 2, and then getting closer to DaVinci 003? And then you left just before ChatGPD was released, but tell people a bit more about the research path that took you there.Stan [00:09:54]: I can give you my perspective of it. I think at OpenAI, there's always been a large chunk of the compute that was reserved to train the GPTs, which makes sense. So it was pre-entropic splits. Most of the compute was going to a product called Nest, which was basically GPT-3. And then you had a bunch of, let's say, remote, not core research teams that were trying to explore maybe more specific problems or maybe the algorithm part of it. The interesting part, I don't know if it was where your question was going, is that in those labs, you're managing researchers. So by definition, you shouldn't be managing them. But in that space, there's a managing tool that is great, which is compute allocation. Basically by managing the compute allocation, you can message the team of where you think the priority should go. And so it was really a question of, you were free as a researcher to work on whatever you wanted. But if it was not aligned with OpenAI mission, and that's fair, you wouldn't get the compute allocation. As it happens, solving math was very much aligned with the direction of OpenAI. And so I was lucky to generally get the compute I needed to make good progress.Swyx [00:11:06]: What do you need to show as incremental results to get funded for further results?Stan [00:11:12]: It's an imperfect process because there's a bit of a... If you're working on math and AI, obviously there's kind of a prior that it's going to be aligned with the company. So it's much easier than to go into something much more risky, much riskier, I guess. You have to show incremental progress, I guess. It's like you ask for a certain amount of compute and you deliver a few weeks after and you demonstrate that you have a progress. Progress might be a positive result. Progress might be a strong negative result. And a strong negative result is actually often much harder to get or much more interesting than a positive result. And then it generally goes into, as any organization, you would have people finding your project or any other project cool and fancy. And so you would have that kind of phase of growing up compute allocation for it all the way to a point. And then maybe you reach an apex and then maybe you go back mostly to zero and restart the process because you're going in a different direction or something else. That's how I felt. Explore, exploit. Yeah, exactly. Exactly. Exactly. It's a reinforcement learning approach.Swyx [00:12:14]: Classic PhD student search process.Alessio [00:12:17]: And you were reporting to Ilya, like the results you were kind of bringing back to him or like what's the structure? It's almost like when you're doing such cutting edge research, you need to report to somebody who is actually really smart to understand that the direction is right.Stan [00:12:29]: So we had a reasoning team, which was working on reasoning, obviously, and so math in general. And that team had a manager, but Ilya was extremely involved in the team as an advisor, I guess. Since he brought me in OpenAI, I was lucky to mostly during the first years to have kind of a direct access to him. He would really coach me as a trainee researcher, I guess, with good engineering skills. And Ilya, I think at OpenAI, he was the one showing the North Star, right? He was his job and I think he really enjoyed it and he did it super well, was going through the teams and saying, this is where we should be going and trying to, you know, flock the different teams together towards an objective.Swyx [00:13:12]: I would say like the public perception of him is that he was the strongest believer in scaling. Oh, yeah. Obviously, he has always pursued the compression thesis. You have worked with him personally, what does the public not know about how he works?Stan [00:13:26]: I think he's really focused on building the vision and communicating the vision within the company, which was extremely useful. I was personally surprised that he spent so much time, you know, working on communicating that vision and getting the teams to work together versus...Swyx [00:13:40]: To be specific, vision is AGI? Oh, yeah.Stan [00:13:42]: Vision is like, yeah, it's the belief in compression and scanning computes. I remember when I started working on the Reasoning team, the excitement was really about scaling the compute around Reasoning and that was really the belief we wanted to ingrain in the team. And that's what has been useful to the team and with the DeepMind results shows that it was the right approach with the success of GPT-4 and stuff shows that it was the right approach.Swyx [00:14:06]: Was it according to the neural scaling laws, the Kaplan paper that was published?Stan [00:14:12]: I think it was before that, because those ones came with GPT-3, basically at the time of GPT-3 being released or being ready internally. But before that, there really was a strong belief in scale. I think it was just the belief that the transformer was a generic enough architecture that you could learn anything. And that was just a question of scaling.Alessio [00:14:33]: Any other fun stories you want to tell? Sam Altman, Greg, you know, anything.Stan [00:14:37]: Weirdly, I didn't work that much with Greg when I was at OpenAI. He had always been mostly focused on training the GPTs and rightfully so. One thing about Sam Altman, he really impressed me because when I joined, he had joined not that long ago and it felt like he was kind of a very high level CEO. And I was mind blown by how deep he was able to go into the subjects within a year or something, all the way to a situation where when I was having lunch by year two, I was at OpenAI with him. He would just quite know deeply what I was doing. With no ML background. Yeah, with no ML background, but I didn't have any either, so I guess that explains why. But I think it's a question about, you don't necessarily need to understand the very technicalities of how things are done, but you need to understand what's the goal and what's being done and what are the recent results and all of that in you. And we could have kind of a very productive discussion. And that really impressed me, given the size at the time of OpenAI, which was not negligible.Swyx [00:15:44]: Yeah. I mean, you've been a, you were a founder before, you're a founder now, and you've seen Sam as a founder. How has he affected you as a founder?Stan [00:15:51]: I think having that capability of changing the scale of your attention in the company, because most of the time you operate at a very high level, but being able to go deep down and being in the known of what's happening on the ground is something that I feel is really enlightening. That's not a place in which I ever was as a founder, because first company, we went all the way to 10 people. Current company, there's 25 of us. So the high level, the sky and the ground are pretty much at the same place. No, you're being too humble.Swyx [00:16:21]: I mean, Stripe was also like a huge rocket ship.Stan [00:16:23]: Stripe, I was a founder. So I was, like at OpenAI, I was really happy being on the ground, pushing the machine, making it work. Yeah.Swyx [00:16:31]: Last OpenAI question. The Anthropic split you mentioned, you were around for that. Very dramatic. David also left around that time, you left. This year, we've also had a similar management shakeup, let's just call it. Can you compare what it was like going through that split during that time? And then like, does that have any similarities now? Like, are we going to see a new Anthropic emerge from these folks that just left?Stan [00:16:54]: That I really, really don't know. At the time, the split was pretty surprising because they had been trying GPT-3, it was a success. And to be completely transparent, I wasn't in the weeds of the splits. What I understood of it is that there was a disagreement of the commercialization of that technology. I think the focal point of that disagreement was the fact that we started working on the API and wanted to make those models available through an API. Is that really the core disagreement? I don't know.Swyx [00:17:25]: Was it safety?Stan [00:17:26]: Was it commercialization?Swyx [00:17:27]: Or did they just want to start a company?Stan [00:17:28]: Exactly. Exactly. That I don't know. But I think what I was surprised of is how quickly OpenAI recovered at the time. And I think it's just because we were mostly a research org and the mission was so clear that some divergence in some teams, some people leave, the mission is still there. We have the compute. We have a site. So it just keeps going.Swyx [00:17:50]: Very deep bench. Like just a lot of talent. Yeah.Alessio [00:17:53]: So that was the OpenAI part of the history. Exactly. So then you leave OpenAI in September 2022. And I would say in Silicon Valley, the two hottest companies at the time were you and Lanktrain. What was that start like and why did you decide to start with a more developer focused kind of like an AI engineer tool rather than going back into some more research and something else?Stan [00:18:15]: Yeah. First, I'm not a trained researcher. So going through OpenAI was really kind of the PhD I always wanted to do. But research is hard. You're digging into a field all day long for weeks and weeks and weeks, and you find something, you get super excited for 12 seconds. And at the 13 seconds, you're like, oh, yeah, that was obvious. And you go back to digging. I'm not a trained, like formally trained researcher, and it wasn't kind of a necessarily an ambition of me of creating, of having a research career. And I felt the hardness of it. I enjoyed a lot of like that a ton. But at the time, I decided that I wanted to go back to something more productive. And the other fun motivation was like, I mean, if we believe in AGI and if we believe the timelines might not be too long, it's actually the last train leaving the station to start a company. After that, it's going to be computers all the way down. And so that was kind of the true motivation for like trying to go there. So that's kind of the core motivation at the beginning of personally. And the motivation for starting a company was pretty simple. I had seen GPT-4 internally at the time, it was September 2022. So it was pre-GPT, but GPT-4 was ready since, I mean, I'd been ready for a few months internally. I was like, okay, that's obvious, the capabilities are there to create an insane amount of value to the world. And yet the deployment is not there yet. The revenue of OpenAI at the time were ridiculously small compared to what it is today. So the thesis was, there's probably a lot to be done at the product level to unlock the usage.Alessio [00:19:49]: Yeah. Let's talk a bit more about the form factor, maybe. I think one of the first successes you had was kind of like the WebGPT-like thing, like using the models to traverse the web and like summarize things. And the browser was really the interface. Why did you start with the browser? Like what was it important? And then you built XP1, which was kind of like the browser extension.Stan [00:20:09]: So the starting point at the time was, if you wanted to talk about LLMs, it was still a rather small community, a community of mostly researchers and to some extent, very early adopters, very early engineers. It was almost inconceivable to just build a product and go sell it to the enterprise, though at the time there was a few companies doing that. The one on marketing, I don't remember its name, Jasper. But so the natural first intention, the first, first, first intention was to go to the developers and try to create tooling for them to create product on top of those models. And so that's what Dust was originally. It was quite different than Lanchain, and Lanchain just beat the s**t out of us, which is great. It's a choice.Swyx [00:20:53]: You were cloud, in closed source. They were open source.Stan [00:20:56]: Yeah. So technically we were open source and we still are open source, but I think that doesn't really matter. I had the strong belief from my research time that you cannot create an LLM-based workflow on just one example. Basically, if you just have one example, you overfit. So as you develop your interaction, your orchestration around the LLM, you need a dozen examples. Obviously, if you're running a dozen examples on a multi-step workflow, you start paralyzing stuff. And if you do that in the console, you just have like a messy stream of tokens going out and it's very hard to observe what's going there. And so the idea was to go with an UI so that you could kind of introspect easily the output of each interaction with the model and dig into there through an UI, which is-Swyx [00:21:42]: Was that open source? I actually didn't come across it.Stan [00:21:44]: Oh yeah, it wasn't. I mean, Dust is entirely open source even today. We're not going for an open source-Swyx [00:21:48]: If it matters, I didn't know that.Stan [00:21:49]: No, no, no, no, no. The reason why is because we're not open source because we're not doing an open source strategy. It's not an open source go-to-market at all. We're open source because we can and it's fun.Swyx [00:21:59]: Open source is marketing. You have all the downsides of open source, which is like people can clone you.Stan [00:22:03]: But I think that downside is a big fallacy. Okay. Yes, anybody can clone Dust today, but the value of Dust is not the current state. The value of Dust is the number of eyeballs and hands of developers that are creating to it in the future. And so yes, anybody can clone it today, but that wouldn't change anything. There is some value in being open source. In a discussion with the security team, you can be extremely transparent and just show the code. When you have discussion with users and there's a bug or a feature missing, you can just point to the issue, show the pull request, show the, show the, exactly, oh, PR welcome. That doesn't happen that much, but you can show the progress if the person that you're chatting with is a little bit technical, they really enjoy seeing the pull request advancing and seeing all the way to deploy. And then the downsides are mostly around security. You never want to do security by obfuscation. But the truth is that your vector of attack is facilitated by you being open source. But at the same time, it's a good thing because if you're doing anything like a bug bountying or stuff like that, you just give much more tools to the bug bountiers so that their output is much better. So there's many, many, many trade-offs. I don't believe in the value of the code base per se. I think it's really the people that are on the code base that have the value and go to market and the product and all of those things that are around the code base. Obviously, that's not true for every code base. If you're working on a very secret kernel to accelerate the inference of LLMs, I would buy that you don't want to be open source. But for product stuff, I really think there's very little risk. Yeah.Alessio [00:23:39]: I signed up for XP1, I was looking, January 2023. I think at the time you were on DaVinci 003. Given that you had seen GPD 4, how did you feel having to push a product out that was using this model that was so inferior? And you're like, please, just use it today. I promise it's going to get better. Just overall, as a founder, how do you build something that maybe doesn't quite work with the model today, but you're just expecting the new model to be better?Stan [00:24:03]: Yeah, so actually, XP1 was even on a smaller one that was the post-GDPT release, small version, so it was... Ada, Babbage... No, no, no, not that far away. But it was the small version of GDPT, basically. I don't remember its name. Yes, you have a frustration there. But at the same time, I think XP1 was designed, was an experiment, but was designed as a way to be useful at the current capability of the model. If you just want to extract data from a LinkedIn page, that model was just fine. If you want to summarize an article on a newspaper, that model was just fine. And so it was really a question of trying to find a product that works with the current capability, knowing that you will always have tailwinds as models get better and faster and cheaper. So that was kind of a... There's a bit of a frustration because you know what's out there and you know that you don't have access to it yet. It's also interesting to try to find a product that works with the current capability.Alessio [00:24:55]: And we highlighted XP1 in our anatomy of autonomy post in April of last year, which was, you know, where are all the agents, right? So now we spent 30 minutes getting to what you're building now. So you basically had a developer framework, then you had a browser extension, then you had all these things, and then you kind of got to where Dust is today. So maybe just give people an overview of what Dust is today and the courtesies behind it. Yeah, of course.Stan [00:25:20]: So Dust, we really want to build the infrastructure so that companies can deploy agents within their teams. We are horizontal by nature because we strongly believe in the emergence of use cases from the people having access to creating an agent that don't need to be developers. They have to be thinkers. They have to be curious. But anybody can create an agent that will solve an operational thing that they're doing in their day-to-day job. And to make those agents useful, there's two focus, which is interesting. The first one is an infrastructure focus. You have to build the pipes so that the agent has access to the data. You have to build the pipes such that the agents can take action, can access the web, et cetera. So that's really an infrastructure play. Maintaining connections to Notion, Slack, GitHub, all of them is a lot of work. It is boring work, boring infrastructure work, but that's something that we know is extremely valuable in the same way that Stripe is extremely valuable because it maintains the pipes. And we have that dual focus because we're also building the product for people to use it. And there it's fascinating because everything started from the conversational interface, obviously, which is a great starting point. But we're only scratching the surface, right? I think we are at the pong level of LLM productization. And we haven't invented the C3. We haven't invented Counter-Strike. We haven't invented Cyberpunk 2077. So this is really our mission is to really create the product that lets people equip themselves to just get away all the work that can be automated or assisted by LLMs.Alessio [00:26:57]: And can you just comment on different takes that people had? So maybe the most open is like auto-GPT. It's just kind of like just trying to do anything. It's like it's all magic. There's no way for you to do anything. Then you had the ADAPT, you know, we had David on the podcast. They're very like super hands-on with each individual customer to build super tailored. How do you decide where to draw the line between this is magic? This is exposed to you, especially in a market where most people don't know how to build with AI at all. So if you expect them to do the thing, they're probably not going to do it. Yeah, exactly.Stan [00:27:29]: So the auto-GPT approach obviously is extremely exciting, but we know that the agentic capability of models are not quite there yet. It just gets lost. So we're starting, we're starting where it works. Same with the XP one. And where it works is pretty simple. It's like simple workflows that involve a couple tools where you don't even need to have the model decide which tools it's used in the sense of you just want people to put it in the instructions. It's like take that page, do that search, pick up that document, do the work that I want in the format I want, and give me the results. There's no smartness there, right? In terms of orchestrating the tools, it's mostly using English for people to program a workflow where you don't have the constraint of having compatible API between the two.Swyx [00:28:17]: That kind of personal automation, would you say it's kind of like an LLM Zapier type ofStan [00:28:22]: thing?Swyx [00:28:22]: Like if this, then that, and then, you know, do this, then this. You're programming with English?Stan [00:28:28]: So you're programming with English. So you're just saying, oh, do this and then that. You can even create some form of APIs. You say, when I give you the command X, do this. When I give you the command Y, do this. And you describe the workflow. But you don't have to create boxes and create the workflow explicitly. It just needs to describe what are the tasks supposed to be and make the tool available to the agent. The tool can be a semantic search. The tool can be querying into a structured database. The tool can be searching on the web. And obviously, the interesting tools that we're only starting to scratch are actually creating external actions like reimbursing something on Stripe, sending an email, clicking on a button in the admin or something like that.Swyx [00:29:11]: Do you maintain all these integrations?Stan [00:29:13]: Today, we maintain most of the integrations. We do always have an escape hatch for people to kind of custom integrate. But the reality is that the reality of the market today is that people just want it to work, right? And so it's mostly us maintaining the integration. As an example, a very good source of information that is tricky to productize is Salesforce. Because Salesforce is basically a database and a UI. And they do the f**k they want with it. And so every company has different models and stuff like that. So right now, we don't support it natively. And the type of support or real native support will be slightly more complex than just osing into it, like is the case with Slack as an example. Because it's probably going to be, oh, you want to connect your Salesforce to us? Give us the SQL. That's the Salesforce QL language. Give us the queries you want us to run on it and inject in the context of dust. So that's interesting how not only integrations are cool, and some of them require a bit of work on the user. And for some of them that are really valuable to our users, but we don't support yet, they can just build them internally and push the data to us.Swyx [00:30:18]: I think I understand the Salesforce thing. But let me just clarify, are you using browser automation because there's no API for something?Stan [00:30:24]: No, no, no, no. In that case, so we do have browser automation for all the use cases and apply the public web. But for most of the integration with the internal system of the company, it really runs through API.Swyx [00:30:35]: Haven't you felt the pull to RPA, browser automation, that kind of stuff?Stan [00:30:39]: I mean, what I've been saying for a long time, maybe I'm wrong, is that if the future is that you're going to stand in front of a computer and looking at an agent clicking on stuff, then I'll hit my computer. And my computer is a big Lenovo. It's black. Doesn't sound good at all compared to a Mac. And if the APIs are there, we should use them. There is going to be a long tail of stuff that don't have APIs, but as the world is moving forward, that's disappearing. So the core API value in the past has really been, oh, this old 90s product doesn't have an API. So I need to use the UI to automate. I think for most of the ICP companies, the companies that ICP for us, the scale ups that are between 500 and 5,000 people, tech companies, most of the SaaS they use have APIs. Now there's an interesting question for the open web, because there are stuff that you want to do that involve websites that don't necessarily have APIs. And the current state of web integration from, which is us and OpenAI and Anthropic, I don't even know if they have web navigation, but I don't think so. The current state of affair is really, really broken because you have what? You have basically search and headless browsing. But headless browsing, I think everybody's doing basically body.innertext and fill that into the model, right?Swyx [00:31:56]: MARK MIRCHANDANI There's parsers into Markdown and stuff.Stan [00:31:58]: FRANCESC CAMPOY I'm super excited by the companies that are exploring the capability of rendering a web page into a way that is compatible for a model, being able to maintain the selector. So that's basically the place where to click in the page through that process, expose the actions to the model, have the model select an action in a way that is compatible with model, which is not a big page of a full DOM that is very noisy, and then being able to decompress that back to the original page and take the action. And that's something that is really exciting and that will kind of change the level of things that agents can do on the web. That I feel exciting, but I also feel that the bulk of the useful stuff that you can do within the company can be done through API. The data can be retrieved by API. The actions can be taken through API.Swyx [00:32:44]: For listeners, I'll note that you're basically completely disagreeing with David Wan. FRANCESC CAMPOY Exactly, exactly. I've seen it since it's summer. ADEPT is where it is, and Dust is where it is. So Dust is still standing.Alessio [00:32:55]: Can we just quickly comment on function calling? You mentioned you don't need the models to be that smart to actually pick the tools. Have you seen the models not be good enough? Or is it just like, you just don't want to put the complexity in there? Like, is there any room for improvement left in function calling? Or do you feel you usually consistently get always the right response, the right parametersStan [00:33:13]: and all of that?Alessio [00:33:13]: FRANCESC CAMPOY So that's a tricky product question.Stan [00:33:15]: Because if the instructions are good and precise, then you don't have any issue, because it's scripted for you. And the model will just look at the scripts and just follow and say, oh, he's probably talking about that action, and I'm going to use it. And the parameters are kind of abused from the state of the conversation. I'll just go with it. If you provide a very high level, kind of an auto-GPT-esque level in the instructions and provide 16 different tools to your model, yes, we're seeing the models in that state making mistakes. And there is obviously some progress can be made on the capabilities. But the interesting part is that there is already so much work that can assist, augment, accelerate by just going with pretty simply scripted for actions agents. What I'm excited about by pushing our users to create rather simple agents is that once you have those working really well, you can create meta agents that use the agents as actions. And all of a sudden, you can kind of have a hierarchy of responsibility that will probably get you almost to the point of the auto-GPT value. It requires the construction of intermediary artifacts, but you're probably going to be able to achieve something great. I'll give you some example. We have our incidents are shared in Slack in a specific channel, or shipped are shared in Slack. We have a weekly meeting where we have a table about incidents and shipped stuff. We're not writing that weekly meeting table anymore. We have an assistant that just go find the right data on Slack and create the table for us. And that assistant works perfectly. It's trivially simple, right? Take one week of data from that channel and just create the table. And then we have in that weekly meeting, obviously some graphs and reporting about our financials and our progress and our ARR. And we've created assistants to generate those graphs directly. And those assistants works great. By creating those assistants that cover those small parts of that weekly meeting, slowly we're getting to in a world where we'll have a weekly meeting assistance. We'll just call it. You don't need to prompt it. You don't need to say anything. It's going to run those different assistants and get that notion page just ready. And by doing that, if you get there, and that's an objective for us to us using Dust, get there, you're saving an hour of company time every time you run it. Yeah.Alessio [00:35:28]: That's my pet topic of NPM for agents. How do you build dependency graphs of agents? And how do you share them? Because why do I have to rebuild some of the smaller levels of what you built already?Swyx [00:35:40]: I have a quick follow-up question on agents managing other agents. It's a topic of a lot of research, both from Microsoft and even in startups. What you've discovered best practice for, let's say like a manager agent controlling a bunch of small agents. It's two-way communication. I don't know if there should be a protocol format.Stan [00:35:59]: To be completely honest, the state we are at right now is creating the simple agents. So we haven't even explored yet the meta agents. We know it's there. We know it's going to be valuable. We know it's going to be awesome. But we're starting there because it's the simplest place to start. And it's also what the market understands. If you go to a company, random SaaS B2B company, not necessarily specialized in AI, and you take an operational team and you tell them, build some tooling for yourself, they'll understand the small agents. If you tell them, build AutoGP, they'll be like, Auto what?Swyx [00:36:31]: And I noticed that in your language, you're very much focused on non-technical users. You don't really mention API here. You mention instruction instead of system prompt, right? That's very conscious.Stan [00:36:41]: Yeah, it's very conscious. It's a mark of our designer, Ed, who kind of pushed us to create a friendly product. I was knee-deep into AI when I started, obviously. And my co-founder, Gabriel, was a Stripe as well. We started a company together that got acquired by Stripe 15 years ago. It was at Alain, a healthcare company in Paris. After that, it was a little bit less so knee-deep in AI, but really focused on product. And I didn't realize how important it is to make that technology not scary to end users. It didn't feel scary to me, but it was really seen by Ed, our designer, that it was feeling scary to the users. And so we were very proactive and very deliberate about creating a brand that feels not too scary and creating a wording and a language, as you say, that really tried to communicate the fact that it's going to be fine. It's going to be easy. You're going to make it.Alessio [00:37:34]: And another big point that David had about ADAPT is we need to build an environment for the agents to act. And then if you have the environment, you can simulate what they do. How's that different when you're interacting with APIs and you're kind of touching systems that you cannot really simulate? If you call it the Salesforce API, you're just calling it.Stan [00:37:52]: So I think that goes back to the DNA of the companies that are very different. ADAPT, I think, was a product company with a very strong research DNA, and they were still doing research. One of their goals was building a model. And that's why they raised a large amount of money, et cetera. We are 100% deliberately a product company. We don't do research. We don't train models. We don't even run GPUs. We're using the models that exist, and we try to push the product boundary as far as possible with the existing models. So that creates an issue. Indeed, so to answer your question, when you're interacting in the real world, well, you cannot simulate, so you cannot improve the models. Even improving your instructions is complicated for a builder. The hope is that you can use models to evaluate the conversations so that you can get at least feedback and you could get contradictive information about the performance of the assistance. But if you take actual trace of interaction of humans with those agents, it is even for us humans extremely hard to decide whether it was a productive interaction or a really bad interaction. You don't know why the person left. You don't know if they left happy or not. So being extremely, extremely, extremely pragmatic here, it becomes a product issue. We have to build a product that identifies the end users to provide feedback so that as a first step, the person that is building the agent can iterate on it. As a second step, maybe later when we start training model and post-training, et cetera, we can optimize around that for each of those companies. Yeah.Alessio [00:39:17]: Do you see in the future products offering kind of like a simulation environment, the same way all SaaS now kind of offers APIs to build programmatically? Like in cybersecurity, there are a lot of companies working on building simulative environments so that then you can use agents like Red Team, but I haven't really seen that.Stan [00:39:34]: Yeah, no, me neither. That's a super interesting question. I think it's really going to depend on how much, because you need to simulate to generate data, you need to train data to train models. And the question at the end is, are we going to be training models or are we just going to be using frontier models as they are? On that question, I don't have a strong opinion. It might be the case that we'll be training models because in all of those AI first products, the model is so close to the product surface that as you get big and you want to really own your product, you're going to have to own the model as well. Owning the model doesn't mean doing the pre-training, that would be crazy. But at least having an internal post-training realignment loop, it makes a lot of sense. And so if we see many companies going towards that all the time, then there might be incentives for the SaaS's of the world to provide assistance in getting there. But at the same time, there's a tension because those SaaS, they don't want to be interacted by agents, they want the human to click on the button. Yeah, they got to sell seats. Exactly.Swyx [00:40:41]: Just a quick question on models. I'm sure you've used many, probably not just OpenAI. Would you characterize some models as better than others? Do you use any open source models? What have been the trends in models over the last two years?Stan [00:40:53]: We've seen over the past two years kind of a bit of a race in between models. And at times, it's the OpenAI model that is the best. At times, it's the Anthropic models that is the best. Our take on that is that we are agnostic and we let our users pick their model. Oh, they choose? Yeah, so when you create an assistant or an agent, you can just say, oh, I'm going to run it on GP4, GP4 Turbo, or...Swyx [00:41:16]: Don't you think for the non-technical user, that is actually an abstraction that you should take away from them?Stan [00:41:20]: We have a sane default. So we move the default to the latest model that is cool. And we have a sane default, and it's actually not very visible. In our flow to create an agent, you would have to go in advance and go pick your model. So this is something that the technical person will care about. But that's something that obviously is a bit too complicated for the...Swyx [00:41:40]: And do you care most about function calling or instruction following or something else?Stan [00:41:44]: I think we care most for function calling because you want to... There's nothing worse than a function call, including incorrect parameters or being a bit off because it just drives the whole interaction off.Swyx [00:41:56]: Yeah, so got the Berkeley function calling.Stan [00:42:00]: These days, it's funny how the comparison between GP4O and GP4 Turbo is still up in the air on function calling. I personally don't have proof, but I know many people, and I'm probably part of them, to think that GP4 Turbo is still better than GP4O on function calling. Wow. We'll see what comes out of the O1 class if it ever gets function calling. And Cloud 3.5 Summit is great as well. They kind of innovated in an interesting way, which was never quite publicized. But it's that they have that kind of chain of thought step whenever you use a Cloud model or Summit model with function calling. That chain of thought step doesn't exist when you just interact with it just for answering questions. But when you use function calling, you get that step, and it really helps getting better function calling.Swyx [00:42:43]: Yeah, we actually just recorded a podcast with the Berkeley team that runs that leaderboard this week. So they just released V3.Stan [00:42:49]: Yeah.Swyx [00:42:49]: It was V1 like two months ago, and then they V2, V3. Turbo is on top.Stan [00:42:53]: Turbo is on top. Turbo is over 4.0.Swyx [00:42:54]: And then the third place is XLAM from Salesforce, which is a large action model they've been trying to popularize.Stan [00:43:01]: Yep.Swyx [00:43:01]: O1 Mini is actually on here, I think. O1 Mini is number 11.Stan [00:43:05]: But arguably, O1 Mini has been in a line for that. Yeah.Alessio [00:43:09]: Do you use leaderboards? Do you have your own evals? I mean, this is kind of intuitive, right? Like using the older model is better. I think most people just upgrade. Yeah. What's the eval process like?Stan [00:43:19]: It's funny because I've been doing research for three years, and we have bigger stuff to cook. When you're deploying in a company, one thing where we really spike is that when we manage to activate the company, we have a crazy penetration. The highest penetration we have is 88% daily active users within the entire employee of the company. The kind of average penetration and activation we have in our current enterprise customers is something like more like 60% to 70% weekly active. So we basically have the entire company interacting with us. And when you're there, there is so many stuff that matters most than getting evals, getting the best model. Because there is so many places where you can create products or do stuff that will give you the 80% with the work you do. Whereas deciding if it's GPT-4 or GPT-4 Turbo or et cetera, you know, it'll just give you the 5% improvement. But the reality is that you want to focus on the places where you can really change the direction or change the interaction more drastically. But that's something that we'll have to do eventually because we still want to be serious people.Swyx [00:44:24]: It's funny because in some ways, the model labs are competing for you, right? You don't have to do any effort. You just switch model and then it'll grow. What are you really limited by? Is it additional sources?Stan [00:44:36]: It's not models, right?Swyx [00:44:37]: You're not really limited by quality of model.Stan [00:44:40]: Right now, we are limited by the infrastructure part, which is the ability to connect easily for users to all the data they need to do the job they want to do.Swyx [00:44:51]: Because you maintain all your own stuff.Stan [00:44:53]: You know, there are companies out thereSwyx [00:44:54]: that are starting to provide integrations as a service, right? I used to work in an integrations company. Yeah, I know.Stan [00:44:59]: It's just that there is some intricacies about how you chunk stuff and how you process information from one platform to the other. If you look at the end of the spectrum, you could think of, you could say, oh, I'm going to support AirByte and AirByte has- I used to work at AirByte.Swyx [00:45:12]: Oh, really?Stan [00:45:13]: That makes sense.Swyx [00:45:14]: They're the French founders as well.Stan [00:45:15]: I know Jean very well. I'm seeing him today. And the reality is that if you look at Notion, AirByte does the job of taking Notion and putting it in a structured way. But that's the way it is not really usable to actually make it available to models in a useful way. Because you get all the blocks, details, et cetera, which is useful for many use cases.Swyx [00:45:35]: It's also for data scientists and not for AI.Stan [00:45:38]: The reality of Notion is that sometimes you have a- so when you have a page, there's a lot of structure in it and you want to capture the structure and chunk the information in a way that respects that structure. In Notion, you have databases. Sometimes those databases are real tabular data. Sometimes those databases are full of text. You want to get the distinction and understand that this database should be considered like text information, whereas this other one is actually quantitative information. And to really get a very high quality interaction with that piece of information, I haven't found a solution that will work without us owning the connection end-to-end.Swyx [00:46:15]: That's why I don't invest in, there's Composio, there's All Hands from Graham Newbig. There's all these other companies that are like, we will do the integrations for you. You just, we have the open source community. We'll do off the shelf. But then you are so specific in your needs that you want to own it.Swyx [00:46:28]: Yeah, exactly.Stan [00:46:29]: You can talk to Michel about that.Swyx [00:46:30]: You know, he wants to put the AI in there, but you know. Yeah, I will. I will.Stan [00:46:35]: Cool. What are we missing?Alessio [00:46:36]: You know, what are like the things that are like sneakily hard that you're tackling that maybe people don't even realize they're like really hard?Stan [00:46:43]: The real parts as we kind of touch base throughout the conversation is really building the infra that works for those agents because it's a tenuous walk. It's an evergreen piece of work because you always have an extra integration that will be useful to a non-negligible set of your users. I'm super excited about is that there's so many interactions that shouldn't be conversational interactions and that could be very useful. Basically, know that we have the firehose of information of those companies and there's not going to be that many companies that capture the firehose of information. When you have the firehose of information, you can do a ton of stuff with models that are just not accelerating people, but giving them superhuman capability, even with the current model capability because you can just sift through much more information. An example is documentation repair. If I have the firehose of Slack messages and new Notion pages, if somebody says, I own that page, I want to be updated when there is a piece of information that should update that page, this is not possible. You get an email saying, oh, look at that Slack message. It says the opposite of what you have in that paragraph. Maybe you want to update or just ping that person. I think there is a lot to be explored on the product layer in terms of what it means to interact productively with those models. And that's a problem that's extremely hard and extremely exciting.Swyx [00:48:00]: One thing you keep mentioning about infra work, obviously, Dust is building that infra and serving that in a very consumer-friendly way. You always talk about infra being additional sources, additional connectors. That is very important. But I'm also interested in the vertical infra. There is an orchestrator underlying all these things where you're doing asynchronous work. For example, the simplest one is a cron job. You just schedule things. But also, for if this and that, you have to wait for something to be executed and proceed to the next task. I used to work on an orchestrator as well, Temporal.Stan [00:48:31]: We used Temporal. Oh, you used Temporal? Yeah. Oh, how was the experience?Swyx [00:48:34]: I need the NPS.Stan [00:48:36]: We're doing a self-discovery call now.Swyx [00:48:39]: But you can also complain to me because I don't work there anymore.Stan [00:48:42]: No, we love Temporal. There's some edges that are a bit rough, surprisingly rough. And you would say, why is it so complicated?Swyx [00:48:49]: It's always versioning.Stan [00:48:50]: Yeah, stuff like that. But we really love it. And we use it for exactly what you said, like managing the entire set of stuff that needs to happen so that in semi-real time, we get all the updates from Slack or Notion or GitHub into the system. And whenever we see that piece of information goes through, maybe trigger workflows to run agents because they need to provide alerts to users and stuff like that. And Temporal is great. Love it.Swyx [00:49:17]: You haven't evaluated others. You don't want to build your own. You're happy with...Stan [00:49:21]: Oh, no, we're not in the business of replacing Temporal. And Temporal is so... I mean, it is or any other competitive product. They're very general. If it's there, there's an interesting theory about buy versus build. I think in that case, when you're a high-growth company, your buy-build trade-off is very much on the side of buy. Because if you have the capability, you're just going to be saving time, you can focus on your core competency, etc. And it's funny because we're seeing, we're starting to see the post-high-growth company, post-SKF company, going back on that trade-off, interestingly. So that's the cloud news about removing Zendesk and Salesforce. Do you believe that, by the way?Alessio [00:49:56]: Yeah, I did a podcast with them.Stan [00:49:58]: Oh, yeah?Alessio [00:49:58]: It's true.Swyx [00:49:59]: No, no, I know.Stan [00:50:00]: Of course they say it's true,Swyx [00:50:00]: but also how well is it going to go?Stan [00:50:02]: So I'm not talking about deflecting the customer traffic. I'm talking about building AI on top of Salesforce and Zendesk, basically, if I understand correctly. And all of a sudden, your product surface becomes much smaller because you're interacting with an AI system that will take some actions. And so all of a sudden, you don't need the product layer anymore. And you realize that, oh, those things are just databases that I pay a hundred times the price, right? Because you're a post-SKF company and you have tech capabilities, you are incentivized to reduce your costs and you have the capability to do so. And then it makes sense to just scratch the SaaS away. So it's interesting that we might see kind of a bad time for SaaS in post-hyper-growth tech companies. So it's still a big market, but it's not that big because if you're not a tech company, you don't have the capabilities to reduce that cost. If you're a high-growth company, always going to be buying because you go faster with that. But that's an interesting new space, new category of companies that might remove some SaaS. Yeah, Alessio's firmSwyx [00:51:02]: has an interesting thesis on the future of SaaS in AI.Alessio [00:51:05]: Service as a software, we call it. It's basically like, well, the most extreme is like, why is there any software at all? You know, ideally, it's all a labor interface where you're asking somebody to do something for you, whether that's a person, an AI agent or whatnot.Stan [00:51:17]: Yeah, yeah, that's interesting. I have to ask.Swyx [00:51:19]: Are you paying for Temporal Cloud or are you self-hosting?Stan [00:51:22]: Oh, no, no, we're paying, we're paying. Oh, okay, interesting.Swyx [00:51:24]: We're paying way too much.Stan [00:51:26]: It's crazy expensive, but it makes us-Swyx [00:51:28]: That's why as a shareholder, I like to hear that. It makes us go faster,Stan [00:51:31]: so we're happy to pay.Swyx [00:51:33]: Other things in the infrastack, I just want a list for other founders to think about. Ops, API gateway, evals, you know, anything interesting there that you build or buy?Stan [00:51:41]: I mean, there's always an interesting question. We've been building a lot around the interface between models and because Dust, the original version, was an orchestration platform and we basically provide a unified interface to every model providers.Swyx [00:51:56]: That's what I call gateway.Stan [00:51:57]: That we add because Dust was that and so we continued building upon and we own it. But that's an interesting question was in you, you want to build that or buy it?Swyx [00:52:06]: Yeah, I always say light LLM is the current open source consensus.Stan [00:52:09]: Exactly, yeah. There's an interesting question there.Swyx [00:52:12]: Ops, Datadog, just tracking.Stan [00:52:14]: Oh yeah, so Datadog is an obvious... What are the mistakes that I regret? I started as pure JavaScript, not TypeScript, and I think you want to, if you're wondering, oh, I want to go fast, I'll do a little bit of JavaScript. No, don't, just start with TypeScript. I see, okay.Swyx [00:52:30]: So interesting, you are a research engineer that came out of OpenAI that bet on TypeScript.Stan [00:52:36]: Well, the reality is that if you're building a product, you're going to be doing a lot of JavaScript, right? And Next, we're using Next as an example. It's

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Le marché B2B évolue rapidement, et les cycles de vente s'allongent. Les raisons ? Plus de décideurs impliqués, des prospects mieux informés, et un contexte économique incertain qui accroît la peur de prendre de mauvaises décisions. Résultat : les commerciaux voient leurs deals stagner et leurs efforts s'éparpiller. Mais il existe une solution efficace pour reprendre le contrôle sur vos ventes complexes : le "Mutual Action Plan" (MAP). Pour en discuter, j'ai invité Siegfried Bizit-Bila, sales coach SaaS B2B et expert en vente complexe, qui partage comment il utilise le MAP pour maintenir l'engagement des parties prenantes et éviter les blocages inattendus. Au programme : Quand et comment introduire le MAP pour maximiser son adoption. Les éléments clés à inclure : ressources, parties prenantes, étapes et échéances. Des conseils pratiques pour faire du MAP un allié incontournable dans vos ventes. Cet épisode est un must pour tous ceux qui cherchent à raccourcir leurs cycles de vente et à maximiser leurs conversions. Soutenez l'émission ❤ Abonnez-vous

We often emphasize the importance of understanding what's being talked about in sales conversations to shape content strategy and tell unique, compelling stories.In this week's SaaS Backwards podcast episode, we talk with Parthi Loganathan, Founder and CEO of Letterdrop, a platform designed to help companies do just that.Parthi explains how Letterdrop's AI assists companies in creating content that resonates with more buyers by leveraging the language their customers actually use, cutting down the time and improving the quality of their thought leadership content. He also shares how Letterdrop supports SDRs in delivering value and helps companies uncover and understand their customers' unmet needs.We also discuss the ongoing shift in SEO, the growing focus on LinkedIn, and the decline of traditional outbound sales tactics such as cold calling and cold emailing.Our conversation with Parthi offers valuable insights for SaaS CEOs, CMOs, and marketing and sales professionals in the B2B space.Key takeaways from this episode:The importance of getting context and relevance right before scaling itWhy cold calling and cold emailing no longer worksInsights on future opportunities for content on LinkedInOther resources to check out:Interview with Vinay Bhagat, Founder and CEO of TrustRadius who publishes a yearly report about how B2B buyer behavior is changing.The Lead Gen Mistake I Guarantee You're Making – how to create content that better identifies intent from today's b2b buyer.And, if you want an outside look at your content with actionable advice, take advantage of our Content Audit. Valued at $20K in free consulting---Thanks for listening to the SaaS Backwards Podcast, brought to you by Austin Lawrence Group. We help SaaS firms reduce churn, accelerate sales, and generate demand. Learn more at AustinLawrence.com.---Is your messaging a sales ally or sneaky saboteur? Let us help with our free messaging audit.We'll look at your website's messaging, content, and conversion potential from the eyes of today's buyer and deliver a presentation with new combinations to more sales conversations and demos. And the best part? It's absolutely free. Get started today!

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Renan de Villiers, CEO and co-founder of OSS Ventures, discusses his niche in B2B SaaS for manufacturing. He explains that manufacturing accounts for 25% of the world GDP and highlights the importance of software in factories. Renan shares his experience as a former factory director and how it led him to start a venture builder and investment firm focused on SaaS B2B for manufacturing. He emphasises the challenges of scaling executive talent in mature companies and the need for better incentive packages in the VC world. Renan also discusses the state of the economy, de-globalisation, and the future of manufacturing. The conversation explores the importance of hardware in tech companies, the challenges of scaling businesses, and the myths and realities of venture capital. It also delves into the personal journey of the guest and his sources of inspiration.takeawaysManufacturing accounts for 25% of the world GDP, making it a significant niche for B2B SaaS.Scaling executive talent is a challenge in mature companies, and better incentive packages are needed in the VC world.The US is decoupling from China, and there is a trend of reshoring and nearshoring in manufacturing.Energy and chip production are becoming increasingly important in the manufacturing industry. Hardware will play a significant role in the success of tech companies in the future.Scaling a business involves two major breaking points: transitioning from founder-led chaos to a more structured approach and managing the challenges of communication and processes as the company grows.Founders need to be willing to adapt and change as their company scales, and sometimes, that means letting go of the chaotic energy that fuelled the early stages.Ideas do matter in business, but they are nothing without execution.Success in life is measured by the impact you have on others.Recommended books: 'No Rules Rules' by Reed Hastings and 'Hunger, Famine, and Wealth' by London philosopher.Recommended podcast: 'Revenue Builder' for insights on revenue generation in B2B SaaS.Chapters00:00 Introduction and Niche in B2B SaaS for Manufacturing02:11 Scaling Executive Talent in Mature Companies06:21 Challenges in Incentive Packages for VC-backed Companies13:22 The Decoupling of the US from China24:07 The Importance of Energy and Chip Production in Manufacturing25:55 The Role of Hardware in Tech Companies30:25 Scaling Challenges and Breaking Points32:17 Adapting as a Founder During Growth39:37 The Importance of Ideas and Execution45:22 Measuring Success in Life49:08 Timeless Inspiration from 'Meditations'49:53 Debunking the Myth: Ideas Do Matter

In this episode, Matt Watson interviews Dale Walden, the founder of Njord & Co, a SaaS B2B marketing company. They discuss the importance of positioning in marketing and how it can help companies focus on their target audience. Dale shares his experiences in the B2C and B2B worlds and emphasizes the need for founders to niche down and focus on a specific customer profile. They also discuss the challenges of transitioning from a founder to a leader and the importance of building a talented team. Dale provides insights into pricing strategies and the differences between selling to SMBs and enterprises. Takeaways Positioning is crucial for companies to focus on their target audience and effectively communicate their value proposition. Niche down and focus on a specific customer profile to make your marketing more relevant and effective. Transitioning from a founder to a leader requires delegation and building a talented team. Consider the size of the organization you're targeting when determining your pricing strategy. Selling to SMBs and enterprises requires different approaches and considerations. Find Startup Hustle Everywhere:https://gigb.co/l/YEh5This episode is sponsored by Full Scale:https://fullscale.io/Find out more about Njord & Co here:https://www.njordconsult.com/ Learn more about Dale Walden here:https://www.linkedin.com/in/dalewalden/ Sign up for the Startup Hustle newsletter:https://newsletter.startuphustle.xyz/ Sound Bites "Positioning is difficult to define, but you know it when you see it." "Make your pitch and proposition relevant to your customer's identity or aspirations." "Transitioning from a ruthless dictator mindset to a collaborative leader is crucial for scaling a business." Chapters 00:00 Introduction and Overview 03:01 Entrepreneurial Journey and Lessons Learned 05:30 Identifying Common Challenges in SaaS Businesses 08:18 Niche Down and Focus on Ideal Customer Profile 11:18 Creating Relevance and Emotional Connection with Customers 13:15 The Benefits of Focusing on a Local Market 14:13 Defining Good Positioning 15:30 Key Questions to Answer in Positioning 16:24 Differentiating Value and Making the Proposition Relevant 19:07 The Challenges of Psychological Positioning for Technical Founders 20:04 Quantifying Differentiated Value for Enterprise Customers 21:11 The Challenges of Unfair Advantage Perception 22:06 Transitioning from Founder to Leader 23:21 The Importance of Delegation and Collaboration 25:18 The Challenges of Letting Go of Control 27:20 The Importance of Talent and Building a Great Team 28:31 The Top Three Mistakes in Positioning 29:24 The Importance of Targeting the Right Market SizeSee omnystudio.com/listener for privacy information.

In this insightful episode, we welcome Victor Antiu, Marketing Manager at Custify, a cutting-edge customer success platform.  Victor shares how Custify acts as a GPS for customer success teams, helping businesses with customer relationships. He discusses the importance of reducing churn, improving onboarding, and increasing productivity in SaaS B2B companies. Victor also offers valuable insights on organic lead generation, content strategy, and the power of authoritative, detailed content in today's digital landscape.  Learn how Custify is revolutionizing customer success operations and driving growth for businesses worldwide.

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Having no plans of becoming a CEO, engineer Marko Dinic shares his 18-year journey to becoming the leader of a company that excels in compliance solutions. Leading his company through both triumphs and challenges, Marko, CEO of Jatheon, delves into his experiences, lessons learned, and the unique insights he's gained along the way.Complex Sales Require Technical ExpertiseMarko emphasizes the need for deep technical understanding when selling intricate compliance solutions. Marko states, “In our industry, sales cycles are very long and involve numerous technical evaluations and integrations. Having a technical lead ensures that we can address any technical concerns that arise during the process, providing confidence to our clients and streamlining the sales journey.”Adapting Through Economic TurmoilFacing market turmoil and recession, Marko had to downsize and rebuild, showcasing resilience and adaptability in leadership. He recalls, “We went from 32 people down to six. So it wasn't going according to plan. But we were able to get back to a cash flow positive state by 2013.”Building the Right TeamThe journey to finding the right sales team involved trial and error, emphasizing the need for experienced, senior salespeople who understand the intricacies of the industry. Marko shares, “We arrived at our current setup, which is primarily SEO-based and PPC-based inbound leads. They come to our senior account executives. We do not have SDRs in front of them because we found that young sales executives do not help us at all.”Action Steps for CEOs:Embrace Technical Expertise in Sales: Ensure your sales team includes technical leads to handle complex details and improve the overall sales process.Focus on Resilience: Prepare for economic challenges by having adaptable strategies and a resilient mindset.Invest in Senior Talent: Hire experienced salespeople who can navigate complex sales environments and provide valuable feedback for product development.Marko Dinic's journey from engineer to CEO of Jatheon offers invaluable lessons for any leader. His experience underscores the importance of technical expertise in sales, resilience in the face of economic challenges, and the critical role of hiring the right team. To gain deeper insights into Marko's story and the strategies that have driven his success, listen to the full episode below. Whether you're a budding entrepreneur or an established CEO, this episode provides practical advice and inspiration for your own business journey. Episode DetailsChapters00:49 Overview of Jatheon Technologies02:52 Early Career and Joining Jatheon09:33 Navigating Financial Challenges and Reorganization09:33 Transitioning to CEO and Sales Department Challenges14:25 Structuring and Scaling the Sales Team20:34 Lessons from Trial and Error in Hiring24:30 Remote Work and Open Communication Culture30:51 Alignment and Continuous Improvement42:26 Recommendations and Closing RemarksAbout GuestMarko Dinic is an SaaS B2B entrepreneur, investor, and CEO of Jatheon Technologies, a Toronto-based com tech company that is a leader in the archiving and compliance technology sector.With a sharp focus on innovation and customer-centric solutions, Marko has spearheaded Jatheon's transformation into a key player in the data archiving space. His strategic vision centers around providing robust and secure archiving solutions that cater to regulated industries, including financial services, healthcare, and government entities. Marko's leadership is marked by a commitment to delivering technologies that ensure compliance with evolving regulations and enhance operational efficiency. His expertise and dedication have been pivotal in Jatheon's growth and its ability to help organizations manage their information governance and compliance challenges effectively.Social Links Connect with Marko on LinkedIn: https://www.linkedin.com/in/markodinic/Connect with Marko on Twitter: https://twitter.com/mdinicCheck out Jatheon's website: https://jatheon.com/Follow Jatheon on LinkedIn: linkedin.com/company/jatheon-technologiesFollow Jatheon on YouTube: https://www.youtube.com/@jatheonCheck out Alice's website: https://aliceheiman.com/Connect with Alice on LinkedIn: https://www.linkedin.com/in/aliceheiman/

¡Bienvenidos a la sexta temporada de Ritacast!

A community can be a "cheat code" for rapid learning and career advancement, and this week's guest knows that better than most.In this episode, we had the pleasure of speaking with Kathleen Booth, SVP of Marketing and Growth at Pavilion, the world's largest private community for go-to-market leaders. Our conversation explores the concept of community-led growth and how Pavilion encourages this by providing a platform for members to grow their network, sharpen their skills, and develop lifelong connections. Overall, Kathleen provides valuable insights into the intersection of community, social media, and growth strategies for SaaS companies. Key takeaways from this episode:The importance of community-led growth for SaaS companies and strategies for leveraging communities to drive growth and engagementHow CEOs and marketing leaders can use social media to build relationships, drive pipeline, and engage with prospectsThe challenges executives face in prioritizing social media efforts and the need to shift from viewing social media as a "nice to have" to a "must have" for business growthThis episode is ideal for SaaS CEOs, CMOs, and marketing professionals looking to leverage community-led growth strategies, enhance their LinkedIn presence, and drive pipeline through organic and personalized outreach.Other resources to check out:Interview with Vinay Bhagat, Founder and CEO of TrustRadius who publishes a yearly report about how B2B buyer behavior is changing.The Lead Gen Mistake I Guarantee You're Making – how to create content that better identifies intent from today's b2b buyer.And, if you want an outside look at your content with actionable advice, take advantage of our Content Audit. Valued at $20K in free consulting---Is your messaging a sales ally or sneaky saboteur? Let us help with our free content audit.We'll look at your website's messaging, content, and conversion potential from the eyes of today's buyer and deliver a presentation with new combinations to more sales conversations and demos. And the best part? It's absolutely free. Get started today!

En este episodio, hablamos con Jordi Romero, CEO y Cofounder de Factorial, el último unicornio español y un SaaS B2B que ha conseguido +10.000 clientes en todo el mundo, junto a Alex Granados y Lucas Frances, de Product Hackers. Con Jordi, hablamos de las claves del éxito de Factorial, los desafíos detrás de su internacionalización y de escalar producto y cultura, cómo priorizan los desarrollos, cómo experimentan y por qué se enfocan en las PyMEs. También exploramos el estado actual del mercado VC, cómo incentivar al equipo de una Startup, qué es lo que podría ir mal en Factorial y cómo definen objetivos a nivel interno. NOSOTROS 🚀 Product Hackers Conference - https://p-h.es/conference-p 🔥 Programa Profesional de Growth Manager Certification - https://p-h.es/GMCertification 🌍 Web - https://producthackers.com/es/podcast/factorial-jordi-romero?utm_source=Podcast&utm_medium=descripcion 📩 Newsletter - https://p-h.es/newsletter-growth 📈 Casos de éxito de Growth - https://p-h.es/misiones-growth RRSS 📹 YouTube - https://www.youtube.com/c/GrowthProductHackers 💼 LinkedIn - https://www.linkedin.com/company/producthackers/ 🐦 Twitter - https://twitter.com/product_hackers 📱 Instagram - https://www.instagram.com/product_hackers/ (00:00) Intro y presentación. (01:27) Las claves del éxito de Factorial. (04:21) El desafío de escalar en el momento adecuado. (07:38) Usando el mercado para priorizar. (10:09) Priorizando la experiencia del usuario. (13:11) Experimentación y crecimiento. (17:29) Por qué enfocarse en las PyMEs. (23:40) Problemas de escalar producto y cultura. (35:27) Los desafíos de internacionalizar. (45:45) Las claves de diseñar un plan para financiarte. (48:29) Estado de la financiación con VC en 2024. (51:17) Incentivando al equipo. (54:29) Definiendo objetivos en Factorial. (58:56) Consiguiendo resultados no lineales. (1:00:58) Lo que podría ir mal en Factorial. (1:02:25) Lo que fue mal en Factorial. (1:06:45) Cómo crece Jordi. (1:08:45) Referentes de emprendimiento de Jordi. (1:11:42) El consejo de Jordi. (1:13:13) Cierre y despedida.

Antoine est diplômé de HEC et a débuté dans le domaine de la tech notamment chez Vente Privée avant de rejoindre un VC, plutôt orienté sur de l'investissement dans des start-ups SaaS B2B. Cette expérience, mêlée à son intérêt marqué pour les cryptos, le pousse à réfléchir à un business dont la croissance suivrait la courbe d'adoption des cryptos. C'est comme cela que Cryptio est née début 2018. Dans cet épisode, Antoine vous dévoile : -pourquoi et comment il a lancé un SaaS de back-office crypto dès 2018 ? -comment il a très rapidement réussi à builder son produit en partenariat avec des grands noms du secteur ? -quelle est la vision et quelles sont les features proposées par Cryptio ? -pourquoi Cryptio joue un rôle clé pour 3 de ses clients en conflit avec le régulateur américain (SEC) ? -quels sont les chiffres clés et les prochains enjeux de l'entreprise ? -quels sont ses conseils financiers et comptables pour des entrepreneurs web3 qui se lancent ? -quelle est sa vision du web3 à horizon 10 ans ? ⚠️ Ce podcast ne constitue pas un conseil en investissement. Les investissements liés aux crypto-actifs et aux NFT sont risqués et peuvent conduire à une perte de la totalité de votre capital. Faites toujours vos propres recherches et soyez prudents ⚠️ Personnes, projets et structures cités dans l'épisode : Antoine Scalia : Linkedin et Twitter Cryptio ConsenSys SEC MiCA Bancolombia (article Bitcoin.com News) ❤️ Si vous avez apprécié cet épisode de Behind The Chain, n'hésitez pas à laisser un avis ou une note sur votre plateforme d'écoute ! Cela aide d'autres passionnés (ou futurs passionnés) par l'univers du web3 à découvrir le podcast.

Customer Experience |  Strategic Leadership | Customer Success | Well-being | Actionable Advice | Career Growth | Join us for a great conversation with Mel Simons, Global Director of Customer Experience at Dreamdata! Dreamdata is a SaaS B2B revenue attribution platform that gathers, joins, and cleans all revenue-related data to present a transparent, actionable analysis of go-to-market data. This empowers you to easily see a 360° customer journey view, understand ROI, reveal buying signals, send data back to ad platforms, and much more.Mel Simons is a seasoned professional with a strong background in Customer Success leadership roles across diverse industries. With previous roles at companies like ZeroNorth, GOODIEBOX, and Trustpilot, Melanie brings extensive experience in driving customer-centric initiatives and fostering brand growth through exceptional customer experience. With a strategic approach to career progression, Mel reflects on key decisions and milestones that have shaped her journey, emphasizing the importance of balancing external customer focus with internal team dynamics for sustainable growth.Learn how Mel ensures alignment between customer-centric initiatives and team dynamics, fostering collaboration among different departments and overcoming barriers through effective communication and problem-solving strategies. We discuss Mel's approach to fostering a culture of continuous improvement within her team while driving external customer satisfaction and internal team development. Mel shares real-life examples of navigating differences in perspectives across departments and stakeholders, and she uncovers practical steps for supporting the professional development and success of team members while driving business growth.Gain valuable insights into setting success roles, prioritizing mental health amidst career demands, and maintaining alignment between long-term career goals and day-to-day activities!Follow Mel Simons on LinkedIn: https://www.linkedin.com/in/melaniejsimons/

En este episodio, hablamos con Jordi Romero, CEO y Cofounder de Factorial, el último unicornio español y un SaaS B2B que ha conseguido +10.000 clientes en todo el mundo, junto a Alex Granados y Lucas Frances, de Product Hackers. Con Jordi, hablamos de las claves del éxito de Factorial, los desafíos detrás de su internacionalización y de escalar producto y cultura, cómo priorizan los desarrollos, cómo experimentan y por qué se enfocan en las PyMEs. También exploramos el estado actual del mercado VC, cómo incentivar al equipo de una Startup, qué es lo que podría ir mal en Factorial y cómo definen objetivos a nivel interno. NOSOTROS 🚀 Product Hackers Conference - https://p-h.es/conference-p 🔥 Programa Profesional de Growth Manager Certification - https://p-h.es/GMCertification 🌍 Web - https://producthackers.com/es/podcast/factorial-jordi-romero?utm_source=Podcast&utm_medium=descripcion 📩 Newsletter - https://p-h.es/newsletter-growth 📈 Casos de éxito de Growth - https://p-h.es/misiones-growth RRSS 📹 YouTube - https://www.youtube.com/c/GrowthProductHackers 💼 LinkedIn - https://www.linkedin.com/company/producthackers/ 🐦 Twitter - https://twitter.com/product_hackers 📱 Instagram - https://www.instagram.com/product_hackers/ (00:00) Intro y presentación. (01:27) Las claves del éxito de Factorial. (04:21) El desafío de escalar en el momento adecuado. (07:38) Usando el mercado para priorizar. (10:09) Priorizando la experiencia del usuario. (13:11) Experimentación y crecimiento. (17:29) Por qué enfocarse en las PyMEs. (23:40) Problemas de escalar producto y cultura. (35:27) Los desafíos de internacionalizar. (45:45) Las claves de diseñar un plan para financiarte. (48:29) Estado de la financiación con VC en 2024. (51:17) Incentivando al equipo. (54:29) Definiendo objetivos en Factorial. (58:56) Consiguiendo resultados no lineales. (1:00:58) Lo que podría ir mal en Factorial. (1:02:25) Lo que fue mal en Factorial. (1:06:45) Cómo crece Jordi. (1:08:45) Referentes de emprendimiento de Jordi. (1:11:42) El consejo de Jordi. (1:13:13) Cierre y despedida.

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If you are struggling to scale your B2B SaaS company beyond a certain point or feel like your growth has hit a ceiling despite your best efforts, you're not alone. Many businesses face similar challenges, but there is a way to break through and achieve exponential growth.In this episode, Julia Vorontsova, the founder of Innovation Park, shares a step-by-step case study on how they helped a 25-year-old B2B SaaS company scale from a mere $200,000 to an impressive $20 million in just four years. By focusing on customer journey optimization, audience targeting, and organic lead generation, they unlocked the secret to sustainable growth.If you're ready to take your B2B SaaS company beyond the plateau, listen to this episode and learn how to implement Julia's proven blueprint for success. Don't miss the opportunity to access Julia's step-by-step blueprint for scaling a SaaS B2B company from $200,000 to $20 million. Visit innovation-park.eu/revenue-blueprint for a detailed case study and actionable insights to propel your business forward.Key Takeaways:01:29 The challenge: Reviving a 25-year-old SaaS brand02:22 Identifying the target audience for the sister brand04:44 Scaling ads and uncovering organic lead generation opportunities10:34 Tracking ROI across revenue channels to maximize results15:23 Using customer language from sales calls to improve copy conversion16:18 Tailoring articles to address different customer profiles and concerns18:21 The importance of clearly communicating your offering to avoid confusion20:45 How to access the detailed case study and revenue optimization blueprintResources:Free Revenue Blueprint - https://innovation-park.eu/revenue-blueprintConnect with Julia VorontsovaWebsite - https://innovation-park.eu/ LinkedIn - https://www.linkedin.com/in/juliavorontsova/ Be sure to subscribe to the podcast at: https://www.digitalmarketer.com/podcast/Facebook: https://www.facebook.com/digitalmarketerInstagram: https://www.instagram.com/digitalmarketer/LinkedIn: https://www.linkedin.com/company/digital-marketer/This Month's Sponsors:Conversion Fanatics - Conversion Rate Optimization AgencyGet 50% Off Monthly Blog Writing Service - BKA Content More Resources from Scalable[Free Guide & Assessment] 7 Levels of ScaleFREE EPIC Challenge More Shows You'll Love

If you are struggling to scale your B2B SaaS company beyond a certain point or feel like your growth has hit a ceiling despite your best efforts, you're not alone. Many businesses face similar challenges, but there is a way to break through and achieve exponential growth.In this episode, Julia Vorontsova, the founder of Innovation Park, shares a step-by-step case study on how they helped a 25-year-old B2B SaaS company scale from a mere $200,000 to an impressive $20 million in just four years. By focusing on customer journey optimization, audience targeting, and organic lead generation, they unlocked the secret to sustainable growth.If you're ready to take your B2B SaaS company beyond the plateau, listen to this episode and learn how to implement Julia's proven blueprint for success. Don't miss the opportunity to access Julia's step-by-step blueprint for scaling a SaaS B2B company from $200,000 to $20 million. Visit innovation-park.eu/revenue-blueprint for a detailed case study and actionable insights to propel your business forward.Key Takeaways:01:29 The challenge: Reviving a 25-year-old SaaS brand02:22 Identifying the target audience for the sister brand04:44 Scaling ads and uncovering organic lead generation opportunities10:34 Tracking ROI across revenue channels to maximize results15:23 Using customer language from sales calls to improve copy conversion16:18 Tailoring articles to address different customer profiles and concerns18:21 The importance of clearly communicating your offering to avoid confusion20:45 How to access the detailed case study and revenue optimization blueprintResources:Free Revenue Blueprint - https://innovation-park.eu/revenue-blueprintConnect with Julia VorontsovaWebsite - https://innovation-park.eu/ LinkedIn - https://www.linkedin.com/in/juliavorontsova/ Be sure to subscribe to the podcast at: https://www.digitalmarketer.com/podcast/Facebook: https://www.facebook.com/digitalmarketerInstagram: https://www.instagram.com/digitalmarketer/LinkedIn: https://www.linkedin.com/company/digital-marketer/This Month's Sponsors:Conversion Fanatics - Conversion Rate Optimization AgencyGet 50% Off Monthly Blog Writing Service - BKA Content More Resources from Scalable[Free Guide & Assessment] 7 Levels of ScaleFREE EPIC Challenge More Shows You'll Love

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Emir Zecovic, an experienced marketing professional in the B2B and SaaS space, joins Mike for a discussion about how to market B2B technology products. Emir highlights how marketers often miss opportunities by not focussing on large non-English speaking markets like South America and India. He shares why marketers should be data-obsessed to understand what influences the buying journey, and why working within start-ups may offer new marketers greater career opportunities.    About TextGrid, 12min and OpenGraph TextGrid offers communication APIs for SMS, MMS, voice and email. With cloud communications, businesses are empowered to build, scale and innovate. 12min is a platform that chooses, reads and summarises the most important non-fiction books. OpenGraph generates meta tags and social media previews for any URL on the web in a few simple steps.   About Emir Emir Zecovic is CMO at 12min and is currently also in transition between roles as CMO at TextGrid and Senior Business Development Consultant at OpenGraph. He is a determined, data-driven and versatile marketer with over 7 years of experience in managing teams, devising and implementing growth strategies for SaaS B2B and B2C companies.   Time Stamps [00:51.1] – Emir shares how he got to this point in his career. [04:46.8] – Emir discusses why it is important not to overlook non-English speaking markets. [08:49.7] – Emir shares his approach to marketing as a CMO. [16:27.0] – How does Emir encourage form fills? [20:26.8] – What impact is AI going to have on the industry. [23:58.1] – Emir offers some career advice to new marketeers. [26:42.9] – Emir's contact details.   Quotes “Trying to be as international as possible in a business is always a good idea, don't underestimate countries you're not familiar with.” Mike Maynard, Managing Director at Napier. “I've heard people say that they don't like Google Ads or Facebook ads or SEO, but I doubt anybody has ever said that they regret having a good email list” Emir Zecovic, CMO at 12min   Follow Emir: Emir Zecovic on LinkedIn: https://www.linkedin.com/in/emir-zecovic-074882166/ TextGrid Website: https://textgrid.com/ TextGird LinkedIn: https://www.linkedin.com/company/textgrid/ OpenGraph Website: https://www.opengraph.xyz/   Follow Mike: Mike Maynard on LinkedIn: https://www.linkedin.com/in/mikemaynard/ Napier website: https://www.napierb2b.com/ Napier LinkedIn: https://www.linkedin.com/company/napier-partnership-limited/   If you enjoyed this episode, be sure to subscribe to our podcast for more discussions about the latest in Marketing B2B Tech and connect with us on social media to stay updated on upcoming episodes. We'd also appreciate it if you could leave us a review on your favourite podcast platform. Want more? Check out Napier's other podcast - The Marketing Automation Moment: https://podcasts.apple.com/ua/podcast/the-marketing-automation-moment-podcast/id1659211547

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In an enlightening episode of the Sales Talk for CEOs Podcast, Alice Heiman engages with Malin Schmidt, not just as the CEO of Kodiak Hub, a pioneer in supplier relationship management software, but as a visionary leader whose journey epitomizes the fusion of sustainability and technology in business. Schmidt's transition from a sustainability advocate to a tech entrepreneur offers invaluable lessons on the intersection of technology, procurement, and sustainable business practices, making her path a beacon for CEOs and leaders aiming to navigate the complexities of modern industries.A Journey of Resilience and InnovationAt the heart of Schmidt's story is her unwavering commitment to sustainability, which led her to challenge the traditional cost-centric models in procurement. Her philosophy, "What we want to do is to put the right data and insights in front of the strategic buyer...including the quality of what you buy, how it has been produced, and of course, to the right price," reflects a holistic approach to business that balances economic, environmental, and social factors.Kodiak Hub's utilization of technology to foster transparency and drive change is a testament to Schmidt's forward-thinking leadership. She emphasizes the importance of not just collecting data but using it to identify and act on opportunities for improvement, stating, "One thing is to report and to measure. But if those data points are not used to drive and identify opportunities for change...then what use is it to just report?" This approach underscores the role of technology as a catalyst for meaningful change, beyond mere efficiency gains.Schmidt's leadership journey is also marked by resilience, particularly in the face of challenges such as the COVID-19 pandemic. Her ability to lead Kodiak Hub to double its growth consecutively highlights the significance of agility and customer-centric innovation in overcoming obstacles. This resilience, coupled with a strategic focus on growth, offers a blueprint for CEOs navigating uncertain times.Emphasizing Creativity and Innovation in LeadershipA distinctive feature of Schmidt's leadership style is her emphasis on creativity in hiring. By exploring candidates' personal journeys and thought processes, Schmidt seeks to uncover their innovative potential, ensuring that Kodiak Hub's team is not only technically adept but also capable of thinking outside the box to drive sustainable solutions and innovation. This approach to building a team underscores the critical role of creativity in fostering innovation and navigating the complexities of technology and sustainability.Key Insights for CEOsSchmidt's journey and leadership at Kodiak Hub offer several key takeaways for CEOs and business leaders:Sustainability as a Core Business Strategy: Schmidt's emphasis on sustainability highlights its importance as a competitive advantage and a pillar for long-term business success.The Power of Technology for Change: Leveraging technology for transparency and to drive actionable change is crucial for modern businesses aiming to stay ahead.Resilience Through Innovation: Schmidt's ability to guide her company through challenges underscores the importance of innovation and customer-centric approaches in ensuring business continuity and growth.Creativity in Leadership: Valuing creativity in the hiring process ensures a team capable of innovative thinking and problem-solving, key components for addressing today's complex business challenges.For CEOs and business leaders looking to embrace sustainable business practices and navigate the complexities of modern supply chains, Malin Schmidt's insights provide a roadmap for leveraging technology, understanding buyer needs, and prioritizing sustainability to drive business growth and innovation. Her journey from a sustainability advocate to a leading CEO in the tech space is not just inspiring but also offers practical strategies for leadership in the 21st century.About GuestMalin Schmidt, a seasoned SaaS B2B entrepreneur, seamlessly blends her expertise in Operations, Supply Chain Management, and SustainTech to reshape global business collaborations. Malin stands at the forefront of innovation in the realm of Supplier Relationship Management (SRM) software as the Founder and CEO of Kodiak Hub. Recognized as one of the Top 100 most influential Women in Supply Chain, Malin has carved an indelible mark in the industry by steering Kodiak Hub to unprecedented success. For Malin, the creation of Kodiak Hub represents the most rewarding and enjoyable venture in her career. With a mission to assist brands in developing sustainable supply chains at scale, Kodiak Hub, under Malin's guidance, has become synonymous with innovation and excellence in the industry. She emphasizes the importance of balancing expansion with consolidation in her business building, to ensure organizational scalability and sustainable modes of operating.Her continuous mission is to develop the Kodiak Hub platform to consistently surprise and delight users, delivering top-line value for large enterprises and solving the challenges residing in global supply chains.Social Links Connect with Malin on Linked In(99+) Malin Schmidt | LinkedInCheck out Kodiak Hub's Website:Kodiak Hub | Supplier Relationship Management Platform(99+) Kodiak Hub: Overview | LinkedInKodiak Hub on YouTube:Kodiak Hub - YouTubeConnect with Alice on LinkedIn:(4) Alice Heiman | LinkedInCheck out Alice's website:Alice Heiman | Sales Consultant and Strategist for CEOs 

Just wrapped up an incredible podcast episode with Ben Kazinik, and I'm buzzing with insights to share! This conversation ventured into the realms of SEO, social media, content marketing, and the fascinating interplay between them. Ben is an experienced well-rounded marketing manager. He grew a B2C home decor company to over $1M in annual revenue. He worked for several SAAS B2B companies managing email marketing, content marketing, and affiliates. He has created and managed blogs, affiliate programs, referral programs, influencers, cold email outreach and social media. He has a deep passion for CRO, A/B testing and UI/UX. Ever find yourself pondering the heavyweight match between SEO and social media? Which should lead your digital strategy? Ben brought a wealth of knowledge, discussing how blending expert matchmaking with strategic content creation can revolutionize how we approach marketing. Imagine a world where finding the right marketing talent is as easy as swiping right on a dating app—this is the future Ben envisions with Maple, a platform connecting brands with marketing mavens. We delved into real-world examples, showcasing how companies like ClickUp are empowering experts to elevate their brands and the remarkable impact of strategic content on LinkedIn. For anyone navigating the complex digital marketing landscape, this episode is a goldmine of actionable strategies and innovative insights. Whether you're a seasoned marketer or just getting your feet wet, there's something in here for you. Curious? Dive into the full episode to turbocharge your marketing strategies. Don't forget to subscribe and join the conversation. Your next big idea might just be a play button away! Connect with Ben: LinkedIn: https://www.linkedin.com/in/ben-kazinik/ Timestamps: 0:00 Intro 0:14 Social media vs SEO strategies for content creators 2:50 Content marketing and expert matching platform 7:24 Empowering subject matter experts for brand promotion 8:45 Leveraging LinkedIn for business growth 14:47 LinkedIn content strategy and personal branding 20:44 Marketing, content, and SEO strategies 24:20 AI's impact on content creation and marketing strategies 33:03 B2B marketing strategies and SEO effectiveness 34:32 Marketing strategies and avoiding burnout 38:47 Work-life balance and creativity. 45:08 Mentorship, community building, and partnerships for business growth 50:06 Marriage advice, community-building, and overcoming fear of vulnerability Subscribe to FUNKY MARKETING: BOLD STRATEGIES FOR B2B GROWTH AND REVENUE on any podcast platform and drop a question here in the comments. Website: https://www.funkymarketing.net/funky-marketing-show/ Apple: https://podcasts.apple.com/us/podcast/funky-marketing-bold-strategies-for-b2b-growth-and-revenue/id1501543408?uo=4 Spotify: https://open.spotify.com/show/136A3zxZ5JYCukvphVP56M YouTube: https://www.youtube.com/@funky_marketing Give us a review: https://ratethispodcast.com/funkymarketingshow/ And if you need help, check out the Funky Marketing Pricing page: https://www.funkymarketing.net/pricing/ #Innovation #BusinessStrategy #Podcast #StorytellingInBusiness #MarketingInsights #B2BSaaS #ProfessionalGrowth #linkedinnetworking #funkymarketing #b2b #marketing #sales #demand #revenue #podcast #contentmarketing #strategy #MarketingAndSales #RealWorldExamples #BusinessStrategy #DigitalTransformation #GrowthMindset #MarketingStrategy #SalesAlignment #InnovativeMarketing #CustomerJourney #BusinessGrowth #PersonalBranding #B2BMarketing #Storytelling #LinkedInStrategy #positioning#LinkedInGrowth #PersonalBranding #BusinessNetworking #PodcastInsights #EngagementStrategies #FunkyMarketing #leadership #authenticity --- Send in a voice message: https://podcasters.spotify.com/pod/show/funky-marketing/message

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 Subscribe: https://www.youtube.com/channel/UCNJI2Tv2yxOLBI02nyJoprA  Learn more about us: https://www.pragmaticinstitute.com/  Start your Product Manager certification here "Disruptive innovation is when a company gets into a new category for them and attempts to engage customers on a different level or via a different set of products." – Will Scott, Product Expert In this episode of Product Chats, Rebecca Kalogeris and Will Scott discuss how businesses can approach and structure their thinking around innovation. They focus on the importance of understanding what problems a business is trying to solve, the outcomes they wish to achieve, and how they plan to grow. Key Takeaways: Takeaway 1: Innovation isn't just about creating something new; it's about understanding the problems your business is trying to solve and the outcomes you want to achieve. Takeaway 2: You can view innovation through different lenses - such as customer needs, market maturity, and your business's growth strategies - to determine the right innovation vector for your business. Takeaway 3: When thinking about innovation, consider the whole ecosystem, not just the product itself. How you package and present your product, as well as how easily customers can interact with your business, can all be avenues for innovation. ABOUT OUR GUEST: Will is a seasoned executive with over 25 years of international experience leading product marketing and management teams across hardware, software, services, and SaaS B2B companies. Originally an engineer by training, Will held senior positions with Cisco, Navisite and Capgemini, along with a range of full-time and fractional CMO positions through his own B2B product management and marketing consulting business. In addition, Will was also previously a partner at the premier product marketing agency, Aventi Group, and an instructor at the Kellogg School of Management in their executive digital marketing and product strategy programs. Learn more about Will and other Pragmatic instructors here. ABOUT PRAGMATIC INSTITUTE: Since 1993, we've provided training and professional development for product, design, and data professionals to accelerate innovation, increase customer satisfaction, and bolster revenue. Through our comprehensive methods and propriety Pragmatic Framework, we train professionals with the skills needed to accelerate their product management and product marketing careers, increase team efficiency, and boost revenue.Our online, in-person, and on-demand courses are taught by industry experts with decades of experience at top companies like Microsoft, Cisco, Dell, Hallmark, Quaker Oats, and Dun & Bradstreet. We offer individual course training in product, design and data, and certification tracks for Product Management Certifications, Product Marketing Certifications, and the Pragmatic Product Master Certification. All attendees gain access to the Pragmatic Alumni Community, a network of over 30,000 alumni worldwide. If you're looking for product management or product marketing training or are pursuing a product marketing certification or product management certification, browse our certification paths at https://www.pragmaticinstitute.com/product/. Courses are available online, in-person, or on-demand to fit your schedule.Want to learn more about becoming a Pragmatic Certified Product Manager? Learn more here. #ProductManagement #ProductManager #ProductManagementCertification #ProductManagementStrategy #PragmaticInstitute

In today's fast-paced digital landscape, where every click counts, crafting compelling copy and designing user experiences that resonate with your audience can be the difference between stagnation and skyrocketing success.  For today's episode, Jaryd Krause has invited Chris Silvestri to share his expert advice in copywriting and UX that creates exceptional profits. Chris is the founder and conversion copywriter at Conversion Alchemy, a company specializing in assisting SaaS and ecommerce businesses in converting website visitors into loyal customers. His professional journey has taken him from a background in software engineering in industrial automation to copywriting and UX design at a usability testing startup. As a "conversion alchemist," Chris leverages his diverse skill set to help clients achieve growth and success. They talked about digital psychology. How much work goes into research when creating clever copywriting and user experience? How does Chris separate the research into three different areas? What are they, and why does he do that? They also dive into constructing a homepage that your audience loves and wants to take the next step with you. Why is good copywriting not about fancy words and the actual writing itself? And what good branding can do, examples of good branding and how to use these strategies for yourself? There's so much value in this episode that it's something you definitely won't want to miss. Tune in now!     Episode Highlights 03:27 What is digital psychology?  09:08 The 3 important areas for copywriting and UX research 12:22 Proper implementation of collected data 20:29 CTAs depend on the type of decision makers 34:40 How to be good at copywriting?  37:36 How can businesses set themselves apart from the competition?     Key Takeaways ➥ Chris explains that digital psychology is his branded way of defining his services, aiming to be more specific than traditional copywriting. It involves understanding people, and research is a significant part of it, making up about 70% of his work. He dives deep into understanding the thought processes, decision-making, and knowledge gaps of potential and existing customers, using this research to inform his copywriting work.   ➥ In homepage development and testing, Chris specializes in user-centric strategies. One of his key focuses is on homepage positioning, which begins by addressing the immediate needs and thoughts of visitors, aligning with their intent and concerns. Furthermore, he tailors the placement of Call to Action (CTA) elements based on user types, distinguishing between fast and slow decision-makers. Chris relies on data-driven insights to inform the precise positioning of CTAs. The testing process is divided into several stages, starting with usability testing, an initial phase involving real users to identify usability issues. Wireframes and mockups come into play for early usability testing, and high-fidelity mockups are subjected to further validation. This meticulous approach extends into the development phase, ensuring that the website engages users effectively and guides them seamlessly through their online journey.   ➥ Chris highlights the significance of understanding a client's brand personality and using it consistently in messaging, which builds trust and allows for artistic expression while staying on-brand. They discuss how creativity can set businesses apart, even in perceived "boring" industries like SaaS B2B, by giving them a unique voice and angle on their value proposition.   About The Guest Chris Silvestri is the founder and conversion copywriter at Conversion Alchemy, where they help SaaS and ecommerce businesses convert more of their website visitors into loyal and excited customers. He went from software engineer in industrial automation to copywriter, then to UX designer at a usability testing startup. As a conversion alchemist, he combines everything he learns along the way to help his clients grow. Connect with Chris Silvestri ➥ Website -  https://conversionalchemy.net/ ➥ Newsletter - https://christophersilvestri.com/newsletter/ ➥ Twitter - https://twitter.com/SilvestriChris   Resource Links ➥ Sell your business to us here - https://www.buyingonlinebusinesses.co/sellyourbusiness ➥ Buying Online Businesses Website - https://buyingonlinebusinesses.com ➥ Download the Due Diligence Framework - https://buyingonlinebusinesses.com/freeresources/ ➥ Semrush (SEO tool) - https://bit.ly/3lINGaV➥ Non Agency (SEO Audit) - https://bit.ly/3EPd7OZ ➥ Market Muse (Content Marketing Software) - https://bit.ly/3Me39L0     *This post may contain affiliate links, so we may earn a small commission when you make a purchase through links on our site/posts at no additional cost to you.See omnystudio.com/listener for privacy information.

Communities can be super powerful. They carry trends, they generate awareness, and if you play your cards right, they can even significantly affect your overall business growth. Now, communities are far from easy to build. To explore the topic, we invited Alex Theuma, founder of SaaStock a successful community helping SaaS founders and their teams connect via expert conferences around the world. In this episode, we cover: - The origins of SaaStock - How to start a community - How to keep your audience engaged to grow the community - The KPIs of community building - More advice for aspiring community builders - And, as per usual, the Fast Five. So, is community building just a nice to have, or should SaaS B2B companies really try to benefit from it? Answer in episode 102 of the SaaS Growth Hub Podcast, with Alex Theuma, founder of SaaStock.