Naveen Gupta

GTM Engineering is the real secret moat since AI has reduced the barrier to creating products. Finding a unique signal, carving out a proprietary channel, and the ALPHA, these add the necessity to solve the growth maze from a different lens. Andrew Chen wrote a piece on this a few months ago: https://lnkd.in/gF3wJxUN Clay created the GTM Engineering role. And Maven created lightning sessions to learn about this fast. If you're in ops and not adding this to your reading/learning list, you're missing out.

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Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data. Learn more at: https://lnkd.in/gSNHmYbA

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Legacy ABM deployment models that launched between 2014-16 are breaking. It’s been 9 years  →  and leaders are starving for a path to modernize. Since DAY 1 our mission at ForgeX has been to fill this modernization and innovation gap. THIS is why we have pioneered: → Modernized Deployment Models = Enterprise ABM, Growth ABM, Deal-Based ABM → Account-Based GTM Architecture™ = our 6 pillar framework to design, scale and optimize an account-based strategy that reflects how successful orgs are operationalizing ABM in 2025. → Account-Based Arrow™ = a unified data model and measurement framework to *actually* transition off of MQLs and operationalize buying groups. And TODAY we’re excited to announce that ForgeX is a founding partner of ABM Leadership Alliance. Through the revival of ABMLA, the partnership reinforces our mission to close the innovation gap and equip GTM leaders with the research, models, tools, and frameworks they need to grow their programs and careers. There is a LOT more to come…….. P.S. we just dropped our new strategy guide on ForgeX’s modernized deployment models in ABMLA’s resource center.

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We hosted another Executive Marketing Roundtable in Seattle yesterday - Prepping for AI Search: The Rise of GEO - with marketing leaders from $100M+ revenue companies. Tight agenda, great food, and plenty of insights (plus some fun). Few insights from our discussion: ✅  PR, UGC & Topical Authority Drive AI Search Wins – Third-party mentions, high-quality PR, and strong topical authority significantly improve visibility and citations in LLM platforms ✅  Entities & Freshness Are Key Ranking Factors – AI Search increasingly prioritizes entity-based content mapping and fresh updates, especially on platforms like Perplexity ✅  GEO is the Local SEO of AI – Like Local SEO optimizes for maps and local listings, GEO optimizes for AI-generated answers across ChatGPT, Google AI Overviews, Perplexity, etc. ✅  Visual & Multimodal Content Rising – Infographics, videos, and multimodal assets are gaining weight in AI Search rankings, offering a competitive advantage ✅  AI Content Has Limits – AI can scale awareness content but is less effective at driving conversions; human-led, high-intent messaging remains crucial Super thankful to all who attended - Kate Rundell (Amazon), Lucas Welch (Highspot), Jackie Johanson (Capgemini Invent), Jake Milstein (Contrast Security), Michella C. (Congo Brands), Bala Vishwanath (SeekOut), Melody Peng (ex- Avalara), Michael Merwin (MacDonald-Miller Facility Solutions), Rekha Thomas (ex-Seismic), Marina Resto Black, Anirudh Singla There is no looking back when your attendees say this - "This is the best event in terms of value and organisation that I have been to, in recent times" Lot more coming up from Pepper. Stay Tuned :) Pepper Content #AI #GEO #SEO #AEO #AISearch #AIinMarketing

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Last week at Zoomtopia, I sat down with innovator, entrepreneur, and co-founder of Andreessen Horowitz, Marc Andreessen. Marc’s insights are highly relevant to how we approach AI at Zoom, moving at the speed of today’s ‘tech revolution’ to apply the latest AI advancements to how we connect and collaborate.Zoom Here are my top 5 takeaways from our conversation: 1. The next tech revolution is here: Every generation has its own tech revolution, from the Internet to cloud computing to AI – the eras that matter yield entire industries and new ways of doing things.  2. AI is the new Internet, on hyperspeed: Today’s AI era is what the Internet era was 30 years ago– but happening at a much faster pace.  3. AI + industry evolution = invest: The companies to watch are those harnessing AI while their industries rapidly change- think the intersection between AI and crypto or AI and biotech. 4. Hands-on learning, at work: Urge employees to experiment with AI, freeing up time so they can try new ideas and prototype new systems. 5. Equipping the next generation: Students must learn how to responsibly use AI, both in K-12 and higher ed. We couldn’t agree more at Zoom and have pledged $10M to bring this to life. Marc shared a great example of his son coding on his own, then using AI to debug the code. Students still need to learn the fundamentals, but AI can help them learn, improve and grow.

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Super excited to announce that UserEvidence has acquired Zealot, and raised an additional $7M (bringing our total to $21M) to fuel our product development and help B2B enterprises deliver customer proof across the entire funnel - from customer evidence, to advocate engagement, and 1:1 references. When Ray Rhodes and I met Sam Farber, Srikar Chava, and Brandon Jakobson back in May - we were instantly stoked on the potential. Their product instincts, speed, creativity, AI-native approach to building, and the incredible traction they had made in a short amount of time blew us away. Big congrats to the Zealot team! Customer content, advocate engagement, and reference management are not inherently distinct concepts. In fact, they are inextricably related and supportive of each other. Yet - there were different technologies in each of these 3 pillars, and arms-length integrations often fell short of their potential. Bringing these 3 pillars together under the same platform creates a massive opportunity for #customermarketers to holistically engage and harness and organizations most important asset - their customers. In an age of increasing noise and complexity when it comes to choosing the right vendor - substantive, credible, specific proof - whether delivered as content or delivered through live connection with a reference - is going to be the key to inspiring buyer confidence. Customer Marketers will be at the center of the organization, and UE + Zealot will power the future of #customermarketing Read more about the news here - https://lnkd.in/gd5Dygu8

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Cresta's Got M@il ! I am excited to introduce Cresta Conversation Intelligence & Agent Assist for Email, extending Cresta’s real-time #AI capabilities to one of the most critical and underserved channels in #CX. Customer conversations happen everywhere, but email has remained one of the hardest channels to optimize. It’s asynchronous, high volume, and often disconnected from the systems that power coaching, insight, and efficiency. That changes today. With this launch, Cresta now provides a single platform to drive speed, consistency, and intelligence across voice, chat, and email: 🔹 Bring real-time intelligence to the inbox with AI that understands email context, customer history, support templates, knowledge base, and continuously learning from all agents.  🔹 Accelerate agent productivity with accurate, on-brand draft replies, auto-complete suggestions, generated instantly. 🔹 Elevate quality and coaching through automated scoring and prescriptive guidance for every email. 🔹 Uncover trends and insights at scale by analyzing full email threads across teams and time. 🔹 Enhance your existing email app by embedding Cresta’s AI seamlessly, turning the inbox into a smart, guided workspace. Cresta now serves as a complete intelligence layer across every major customer channel, empowering teams to move faster, operate smarter, and deliver exceptional experiences at scale. This is a huge step toward our mission: turning every conversation into a competitive advantage. Read the full announcement here: https://lnkd.in/gaKqWWTj

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Lots of new AI goodness from Heroku team for app and agentic development, bringing powerful tech to developers without adding complexity and cognitive load -- simplicity and ease of use are critical to maximize productivity -- but business require this to be secure and operationally efficient. Check out these three new releases for Heroku's Managed Inference and Agents: 🌟 Added support for OpenAI's new open-weight model, gpt-oss-120b https://lnkd.in/gF98nA2R 🌟 Support for LlamaIndex to build data aware AI apps https://lnkd.in/gJj22YG4 🌟 Support for Pydantic AI - a popular agent framework for #python https://lnkd.in/graThjk6 Salesforce #Heroku Python #PydanticAI #LlamaIndex #OpenAI Salesforce Developers #AI #LLM #AIAgents #softwareengineering #developers

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Many marketers are applying first-order thinking on how to take advantage of emergent AI channels to grow their business. Optimizing for LLM visibility, building crawlable sites for AI traffic, eventually buying ads on these platforms -- this is the conversation. Our discussion with Dmitry at Perplexity delved into second-order effects of the shift that's underway. In a world of agent-based discovery and native checkout inside Perplexity’s new Comet browser (where the agent sees user's full context and can transact), "personalization" looks very different. A few topics we delved into: - Optimizing for decision quality vs transaction friction - How Comet turns every tab into a shopping agent, and which signals it weights in surfacing hyper-personal recommendations. - The role of AI browsers & sidebar agents in threatening display ad real estate - Moving from keyword-orientation to dynamic offers/discounts - Trust remains the hard currency. How to think about AEO and Ads wrt trust Hope this is a valuable episode. Feedback welcome. cc Rishabh https://lnkd.in/gmYtigaC

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At Amazon, one of the most important and misunderstood parts of the Annual Operating Plan is the Investment Envelope. When done right, it aligns executive priorities with the plans of each business unit. When skipped or rushed, it leaves teams planning in a vacuum. The Investment Envelope is the first major step in the OP1 phase of planning. It usually happens in July and comes from the top. At Amazon, this meant that the CEO and CFO provide top-down guidance on expected revenue, free cash flow, and resource constraints. These are the high-level financial and strategic guardrails for the year ahead. This guidance included financial targets such as: → Revenue, gross profit, contribution profit, and free cash flow → Variable and fixed operating expenditure caps that shape headcount and operational spending. → Capital expenditure guidance that is especially critical for hardware and infrastructure teams. It also included non-financial targets for input metrics such as inventory turns, variable cost per item shipped, click to deliver time, or fast track in-stock percentage. And also targets for new initiatives such as “Launch Free 1-day shipping in 10 major cities,” or “Launch Project Kuiper.” These targets should be specific to each function and business unit in the company. Some teams might be required to keep fixed and variable costs flat, while other teams might need to invest to expand their team or infrastructure. Each team would then take this envelope and begin crafting their OP1 plan. That plan was bottom-up: teams defined their initiatives, resource needs, and key metrics. The tension between the top-down strategy (investment envelope) and bottom-up planning (OP1) was the point of this exercise. Working through this tension is what eventually resulted in a final plan. This work was done in a series of planning reviews throughout the fall: VP reviews in September, SVP reviews in October, and ultimately the CEO/S-team reviews in Q4. Without the investment envelope, teams would often propose too many initiatives, too much headcount, or revenue forecasts that didn’t align with company guidance. The Investment Envelope is essentially a forcing function that gives teams a structure to plan within. It forces tradeoffs early, aligns expectations, and gives every team a clear sense of how their plans fit into the broader company strategy. If you want help designing your own investment envelope, take our new online course on Operating Plan Mastery: https://lnkd.in/gVQB3Qj9

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Incredible The Josh Bersin Company case study has just launched detailing how HiBob supports team.blue across 60 different portfolio companies spanning 20 counties to deliver 💡 AI Insights at scale 👏 84% adoption across all global employees ✍ 95% reduction in manual tasks Link to complete case study in comments

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Launch day! Continuing the drum beat on new provider integrations: today we're announcing a native integration with Anyscale! Anyscale kicks off a series of AI-specific provider integrations we're going to be announcing for the remainder of the year. When I started Vantage, I had a belief that companies were going to be using more and more third-party providers beyond the main three hyperscalers to run their infrastructure. Today, AI has materially accelerated that trend. Each of these AI providers has their own bespoke pricing structure that we need to work with to provide the single pane of glass view into total cost of ownership for an organization. As companies leverage these AI providers, they expect that their Finops platform has support accordingly. As with the ~25 other native integrations Vantage currently supports, Anyscale costs will support all the #FinOps features you know and love across cost allocation, budgeting, forecasting and beyond. Getting starting is as simple as providing an API key and we do all the heavy lifting from there. To see all the details, check out the blog post below.

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