Introduction

Are we entering an era where AI “does the work” while we simply set the vision? For software developers, the answer is trending toward yes – thanks to vibe coding, a new paradigm where programmers let AI generate code from natural language prompts(2). Instead of painstakingly writing every line of code, developers using vibe coding “express their intention using plain speech” and let AI agents transform those ideas into executable software(2). The result? Coding projects can be spun up in a fraction of the time – in fact, AI models can produce code an order of magnitude faster than even expert human coders(3). This “forget that the code even exists” approach, as AI luminary Andrej Karpathy describes it, allows creators to focus on ideas and prototypes while the AI handles the heavy lifting(3).

Now, that same principle of effortless AI-driven execution is coming to the world of sales and marketing through VibeGTM. Just as vibe coding empowers developers to build software by simply describing what they want, VibeGTM (short for “vibe go-to-market”) enables business teams to launch full-fledged sales campaigns with minimal manual effort. Landbase – an AI technology company recognized as the leader in agentic AI for go-to-market (GTM)(1) – is pioneering this approach as a core part of its strategy and technological positioning. The idea is straightforward: make GTM as easy as setting the vibe. Instead of weeks or months of planning, list building, and outreach, Landbase’s platform can suggest and orchestrate a multi-channel campaign in minutes(1). The user simply specifies high-level goals or target audiences, and the AI does the rest – much like a developer saying “build me a simple app that does X” and watching the AI generate it.

According to Salesforce research, 83% of sales teams using AI have seen revenue growth, versus 66% of teams without AI(4). Results like these underscore why trends like vibe coding and VibeGTM are gaining momentum – they promise to boost productivity and outcomes in fields that traditionally required intensive manual effort. In this blog, we’ll compare vibe coding and VibeGTM side by side, exploring how each works, the problems they solve, and what this means for professionals in telecom, commercial real estate, managed services, and beyond. We’ll see how Landbase’s agentic AI-powered VibeGTM approach is revolutionizing go-to-market execution, much as AI coding assistants have transformed software development. By the end, you’ll understand why Landbase positions itself as a category leader in this space and how embracing these innovations could give your business a strategic edge.

From Vibe Coding to VibeGTM: Two AI Revolutions, One Philosophy

Vibe coding and VibeGTM originate in very different domains – one in software engineering, the other in sales/marketing – yet they share a common philosophy: let AI handle the grunt work. Both emerged as responses to the question: what if we could achieve our goals by simply telling AI what we want, and letting it figure out the “how”?

• Vibe Coding (software development): Coined by AI researcher Andrej Karpathy in early 2025, “vibe coding” is a fresh take on programming that puts AI at the forefront of writing code(2). Developers using this approach rely on AI coding assistants (powered by large language models) to generate and even debug code, while they guide the process with natural language prompts and high-level feedback. As IBM’s AI experts describe, vibe coding lets users “express their intention… and the AI transforms that thinking into executable code,” enabling a “code first, refine later” mindset(2). This means faster prototyping and iteration: one can build an application by simply describing features or changes (e.g. “make the login button blue and half the size”) and accepting the AI’s suggestions, without manually digging through code for every tweak(3). The payoff is tremendous speed and flexibility in development – early vibe coding adopters report launching weekend projects in hours instead of weeks, as the AI can produce functional code 10x faster than a human(3). Of course, a human remains in the loop for oversight and final polish (especially for production-quality software)(3)(2), but the heavy lifting of generating boilerplate, fixing minor bugs, and scaffolding entire modules is largely automated. Vibe coding, highlighted in major media from The New York Times to Ars Technica(3), has quickly gone from a niche term to a mainstream movement in programming – all within a few months of its inception.
• VibeGTM (go-to-market execution): Coined by Landbase CEO Daniel Saks in early 2025, “vibe GTM” is inspired by the success of vibe coding. Landbase pioneered VibeGTM to bring a similar “AI does the work” experience to go-to-market strategy. In essence, VibeGTM is about using agentic AI to automate the complex, multi-step process of B2B sales outreach – from identifying target customers, to crafting personalized messages, to executing multi-channel campaigns. Rather than a sales team manually researching leads, writing emails, and following up tirelessly, VibeGTM envisions a world where a business user can say, for example, “Get me meetings with procurement managers in the top 50 healthcare companies in our region,” and the AI-powered system will handle everything needed to make it happen. Landbase’s CEO Daniel Saks explains that their latest product update – the Campaign Feed – “brings the fun and effortless experience of the ‘vibe coding’ phenomenon to GTM, making it easy to review, edit and launch campaigns in minutes instead of months.”(1). In practice, this means Landbase’s platform will recommend complete campaign strategies (audience selection, messaging, timing, channels) as easily as a coding AI suggests code changes. A user can review the suggested go-to-market campaign, tweak any details if needed, then launch it with one click – the AI takes care of executing the outreach across email, LinkedIn, phone, etc., and even monitors responses to optimize the next steps(1). This is made possible by Landbase’s proprietary AI engine, GTM-1 Omni, which is a domain-specific, multi-agent AI system purpose-built for sales and marketing workflows. Much like an AI pair-programmer in vibe coding, GTM-1 Omni acts as an “AI GTM team” that can design and run campaigns autonomously, while the human sets the high-level objectives.

At their core, both vibe coding and VibeGTM are about democratizing expertise through AI. Vibe coding allows even non-experts or time-strapped coders to create software by leveraging the AI’s knowledge of best practices and vast coding patterns. Similarly, VibeGTM allows a small business or a lean sales team to execute sophisticated marketing campaigns (traditionally requiring an army of SDRs, marketers, data researchers, and various tools) simply by tapping into Landbase’s AI, which carries the learned experience of thousands of successful campaigns. In both cases, AI acts as a force-multiplier for human creativity and strategic thinking: you focus on the “what” (the vision or goal), and the AI figures out the “how” (the execution steps). It’s a paradigm shift in how work gets done.

VibeGTM vs. Vibe Coding: Side-by-Side Comparison

How exactly do vibe coding and VibeGTM stack up against each other? Let’s compare these two AI-driven approaches across key dimensions:

As the comparison above shows, vibe coding and VibeGTM both empower users to achieve more with less effort – but they do so in different arenas. Vibe coding tackles the technical complexity of software creation, while VibeGTM addresses the operational complexity of scaling pipeline and sales outreach. Each lowers the barrier to entry in its field: you no longer need to be a veteran programmer to build a web app, and you no longer need a 20-person sales team to reach thousands of qualified prospects.

Importantly, both still benefit from human insight at the right moments. AI isn’t magically omniscient – a developer still must verify critical code, and a sales leader still sets the overall campaign strategy and ensures the messaging aligns with brand tone. But the time and effort saved are enormous. In software, this means more experiments and faster innovation. In GTM, it means more customer conversations and a fuller sales funnel without proportional headcount growth.

To illustrate, consider a telecom company using Landbase’s VibeGTM: traditionally, their sales team might spend weeks preparing outreach for a new product launch – compiling lists of businesses expanding to new locations, drafting emails about upgrading network services, ensuring compliance with telecom regulations. With Landbase, the AI can instantly identify, say, all multi-location businesses in the region that are growing (using real-time data signals), draft a tailored pitch about reliable connectivity for expansion, and ensure every message meets telecom compliance standards automatically. One Landbase telecom client added $400,000 in monthly recurring revenue during a slow season by having the AI find “hidden pockets of demand” and engage them at scale – something their human team alone struggled to do in that timeframe. This is the power of VibeGTM in action.

Meanwhile, software teams embracing vibe coding have similarly reported double-digit productivity boosts. A survey by HubSpot found that 47% of sales professionals (who often have to script emails or write reports) are already using generative AI tools like ChatGPT to help draft content(5) – essentially a form of “vibe writing” – and 52% use AI to analyze data for decisions(5). Developers are doing the same with code: relying on AI for boilerplate allows them to focus on creative problem-solving. The trend is clear across industries: routine content generation (whether code or emails) is being offloaded to AI so humans can concentrate on strategy and relationships. In the next section, we’ll dive deeper into the specific pain points in GTM that VibeGTM solves, and how Landbase’s approach uniquely addresses them by building on the lessons from vibe coding.

Solving GTM Challenges with VibeGTM (Inspired by Vibe Coding’s Success)

Implementing a go-to-market strategy has historically been a resource-intensive endeavor. Let’s face it: traditional GTM execution is rife with challenges that drain time and money. This is precisely why an AI-driven solution like VibeGTM is so game-changing – it directly tackles these pain points. Many of the breakthroughs that made vibe coding appealing (automation of tedious tasks, real-time suggestions, learning from feedback) are now being applied to solve long-standing GTM headaches. Here are some key GTM challenges and how Landbase’s VibeGTM approach provides a solution:

• Fragmented tools and data silos: Modern sales teams often juggle a patchwork of tools – a CRM for contacts, an email platform for outreach, LinkedIn for social selling, separate databases for leads, etc. Data ends up siloed, and reps waste time switching contexts. This fragmentation makes it hard to coordinate campaigns or get a unified view of what’s working. Landbase’s Solution: A single, unified AI platform that consolidates data and workflow. Landbase’s GTM-1 Omni acts as the central brain that integrates prospect data, engagement history, and campaign analytics. By replacing a “scatter” of point solutions with one intelligent system, Landbase ensures nothing falls through the cracks. Just as vibe coding tools integrate into your coding environment to provide on-the-fly help, Landbase’s platform integrates formerly disparate GTM functions into one seamless experience. The AI can then optimize holistically – for example, if email responses are low but LinkedIn messages get replies, the system shifts focus accordingly, something a human might miss if tools are disconnected. The result is a streamlined process where all moving parts of a campaign are orchestrated together. No more exporting lists from one system to import into another or manually reconciling metrics – the AI sees and manages the whole funnel in one place.
• Time-intensive manual outreach: Prospecting and outreach can feel like a grind. Sales development reps (SDRs) might spend 70% of their day researching contacts, writing cold emails, and following up(4) – leaving only a sliver of time for actual selling or learning about customers. This manual workload limits how many prospects a team can touch and slows down pipeline generation. Landbase’s Solution: Automation of repetitive tasks and 24/7 productivity. Landbase’s agentic AI essentially operates as an always-on SDR team that never sleeps. It can scour databases and the web to discover new leads, automatically generate personalized outreach, and send follow-ups at optimal times, all without human intervention. Early adopters of this AI outreach saw huge efficiency gains – one report noted Landbase’s system enabled companies to launch a full outbound program “in minutes rather than months”. In fact, Landbase estimates that using their platform can reduce the cost and effort of scaling a sales pipeline by 60–70% compared to hiring a traditional SDR team and piecemeal tools. Just as vibe coding saves developers from typing boilerplate code so they can focus on creative design, VibeGTM saves sales teams from drudgery (like piecing together lead info or writing yet another intro email) so they can focus on high-level strategy and closing deals. The AI handles the busywork of outreach at machine speed, sending potentially thousands of personalized touchpoints across multiple channels in the time it would take a human to manually send one batch of emails.
• Low conversion from generic campaigns: “Spray and pray” emails and untargeted cold calls typically yield dismal results – prospects ignore messages that don’t speak to their needs. Many companies have seen their mass email campaigns lost in the noise, with meager reply rates and poor ROI. The problem is lack of personalization and relevance at scale; human teams often can’t customize every message deeply when contacting hundreds of leads. Landbase’s Solution: Hyper-personalization and continuous optimization using AI. This is where a domain-trained AI truly shines. Landbase’s model analyzes each prospect’s context (industry, role, company news, etc.) and tailors messaging accordingly. It’s trained on a vast dataset of what works – over 40 million sales email samples – so it crafts outreach with proven best practices for conversion. During early tests, this led to up to 7x better conversion rates versus standard one-size-fits-all emails. Think of it as the GTM equivalent of an AI coder knowing the optimal algorithm: the AI knows the optimal pitch for a given prospect. Moreover, Landbase employs a feedback loop akin to how vibe coding tools learn from user corrections. The platform tracks responses in real time and auto-tunes the campaign – if certain messaging resonates more or certain subject lines get better open rates, the AI adapts on the fly. This continuous learning is a hallmark of “agentic AI”: it not only executes tasks but also learns and improves from results. Humans alone would struggle to A/B test and iterate so rapidly at scale. Landbase’s AI essentially personalizes and optimizes every step automatically, ensuring each prospect interaction is as effective as possible. The outcome is significantly higher engagement and ROI from outreach efforts.
• Scaling pipeline is costly and slow: If a company wants to dramatically increase its sales pipeline, the traditional playbook is to hire more SDRs, subscribe to more data services, and invest in more tooling – an approach that is expensive and can take months to ramp up. Hiring and training reps, for instance, might take 3-6 months before they are fully productive, and even then, their capacity is limited by working hours. Landbase’s Solution: On-demand scalability with AI at a fraction of the cost. Landbase offers what is essentially a scalable “AI SDR team” in the cloud. Need to double your outreach volume for a new product launch? Simply instruct the platform, and it can double the campaign outputs – no new hires required. Landbase has reported that companies using its platform can scale outreach at ~60% lower cost than scaling with human teams and traditional tools. This is because the AI handles more accounts simultaneously than a human ever could, and it doesn’t need benefits, office space, or sleep. One company executive described this as compressing a process that took months into minutes. In practical terms, a business can enter a new market or segment much faster. For example, a managed services provider (MSP) could traditionally only target a handful of industries at once due to limited sales staff. With Landbase, that MSP can launch tailored campaigns to multiple verticals in parallel – e.g., one campaign aimed at healthcare companies emphasizing compliance support, and another aimed at tech startups emphasizing agility – all driven by the same AI platform concurrently. This agility was unheard of before agentic AI. As a bonus, because the platform is subscription-based, companies move from high fixed labor costs to more flexible costs that scale with usage, improving efficiency. In one case, after implementing Landbase, a tech startup was able to significantly shorten its sales cycle by letting the AI rapidly zero in on the right audience and message, something that took them much longer before.
• Knowledge and expertise gaps: Not every organization has top-tier sales ops experts or data scientists to optimize their go-to-market. A mid-sized commercial real estate firm, for instance, might not know the best practices to find tenants in a new market or what messaging yields responses from CFOs looking for office space. Similarly, an industrial supplier may not be adept at using intent data to time their outreach. Landbase’s Solution: Built-in expertise and best practices encoded in AI. Landbase’s agentic AI was developed by training on best-in-class sales workflows and copy – including input from veteran SDRs and marketing experts. It’s as if Landbase took the collective wisdom of dozens of high-performing sales teams and made it available on-demand through the platform. This means even a small team can execute like a seasoned pro. The AI “knows” which job titles are key decision-makers in different industries, what value propositions resonate in, say, telecom vs. finance, and even the optimal time of day to send an email to a VP-level contact. For example, Landbase’s knowledge graph and models understand that in telecom deals, emphasizing reliability and compliance is critical, whereas in commercial real estate outreach, referencing local market trends or expansion news might grab attention. The AI will automatically incorporate such insights. This flattens the learning curve for users – you don’t need a PhD in marketing to benefit; the AI provides suggestions and content that have a high likelihood of success out-of-the-box. In vibe coding terms, it’s like having an AI that already knows all common design patterns and pitfalls, so even a novice coder can produce decent software with its guidance. With Landbase, even a novice in GTM can run a solid campaign, because the agentic AI acts as an expert coach and executor in one. Moreover, Landbase’s team continues to update the AI (via their Applied AI Lab and continuous learning from all client campaigns)(1), ensuring that the latest tactics and market shifts are reflected. This is crucial in fast-changing markets where what worked last quarter might not work now – the AI adapts faster than human training cycles.

In summary, VibeGTM directly addresses the pain points that have long frustrated sales and marketing professionals, using the same playbook that made vibe coding successful: automate the tedious stuff, augment human skill with AI insights, and iterate quickly based on data. The result is a solution-oriented, confident approach to GTM. Instead of being mired in operational logistics, teams can proactively strategize and engage with prospects who matter, leaving the rest to AI.

For professionals in industries like telecom, commercial real estate (CRE), and managed services, this is especially powerful. These sectors often involve complex B2B sales with long cycles and timing is everything – missing a single market trigger (like a company relocating offices, or a telecom client expanding infrastructure) can mean a lost deal. Landbase’s VibeGTM ensures you never miss a beat in the market. As soon as a relevant signal appears (e.g., a firm raises a new funding round or a tenant’s lease is up for renewal), the AI can pounce on it with tailored outreach, far faster than a human team could react. In a world where 76% of salespeople agree that by 2030 most people will use some form of AI or automation in their job(5), those who leverage VibeGTM will clearly have an edge in efficiency and effectiveness.

The Technology Behind the Scenes: How Vibe Coding and VibeGTM Leverage AI Differently

While vibe coding and VibeGTM share a vision of AI-driven ease, the underlying technologies are tuned to their respective domains. Understanding these differences can help decision-makers appreciate why a specialized platform like Landbase is needed for GTM, rather than trying to use a generic AI assistant.

Vibe coding’s tech stack: At the heart of vibe coding are large language models (LLMs) specialized in programming. Models like OpenAI’s Codex (which powers GitHub Copilot) and others (e.g., those behind Replit’s Ghostwriter or Cursor) have been trained on billions of lines of source code from public repositories(2). They effectively predict code given some context (like code that was already written, plus a developer’s prompt). Modern coding assistants also incorporate voice recognition (Karpathy mentions using voice input with “SuperWhisper” to talk to the AI(3)) and integrate with development environments to read the developer’s entire codebase for context. There’s also an element of agent behavior emerging – for example, if the code doesn’t compile, the assistant can read the error and automatically attempt a fix, looping until tests pass. This starts to resemble an “agentic” approach, but generally these tools are not fully autonomous; they react to the developer’s prompts or corrections. Importantly, vibe coding tools prioritize not breaking the flow: they give real-time suggestions as you code or converse, with the goal that the human can keep “in the zone” of creativity(2). The success of vibe coding thus far has relied on LLMs that are generalists in code (able to work across languages and frameworks), paired with a tight user interface loop that makes interacting with the AI quick and intuitive (e.g., hitting tab to accept a suggestion, or asking a question in natural language). As these models improve and perhaps incorporate more reinforcement learning from how developers use them, we might see even more autonomous coding agents. But currently, the developer is the orchestrator, and the AI is the savvy assistant.

VibeGTM’s tech stack (Landbase’s approach): Landbase’s GTM-1 Omni is a purpose-built AI specifically for go-to-market tasks, and this specialization is its strength. Instead of a single large model trying to do everything, Omni combines multiple AI components each optimized for a facet of the GTM process. According to Landbase, it integrates three types of AI capabilities into one system:

1. Predictive models – to analyze data signals and predict which prospects are likely to convert or which actions will yield the best results. For instance, predictive algorithms score leads based on thousands of intent signals (funding events, job postings, website visits, etc.) to prioritize outreach.
2. Generative models – to create content (emails, LinkedIn messages, call scripts) tailored to each situation. This includes natural language generation fine-tuned on successful sales communications. It’s not just general GPT-4 writing an email; it’s an AI trained on what a high-performing SDR would write when reaching out to, say, a VP of Finance in the SaaS industry, including appropriate terminology and pain points.
3. Action models – to execute tasks across systems, meaning the AI can actually send emails, schedule calendar invites, update CRM entries, etc., via API integrations, without needing a human to press the button. This is where agentic AI comes in – the system can act autonomously in digital environments (email servers, CRM, social networks) to carry out the steps of the campaign.

These components are orchestrated by an agentic framework that understands objectives, not just instructions. As Landbase’s team explains, unlike a typical AI assistant that only responds to direct prompts (“write an email about X”), an agentic AI can take a higher-level goal (“generate pipeline in healthcare sector”) and break it down into sub-tasks – identify healthcare companies, find relevant contacts, craft messages, send, follow-up, and so on – adjusting along the way. This is analogous to having an AI project manager combined with AI workers for each task. Under the hood, Landbase’s platform is also powered by a massive proprietary dataset: a knowledge graph of over 220 million contacts and 40 million sales interactions feeds the AI’s understanding of business relationships and language. This is a stark contrast to generic models like ChatGPT which, while trained on a broad swath of the internet, don’t have up-to-date or deep proprietary sales data and often have to be manually given context about a company or market. Landbase’s system already knows a lot about a given industry or account from its data, so it can proactively use that context in campaigns.

Another key tech difference is continuous learning and optimization. Landbase’s agentic AI doesn’t stop at sending messages – it monitors what happens next (did the prospect open the email? click a link? reply with interest? ignore it?) and feeds that outcome back into its models to learn and improve. It’s akin to how a self-driving car AI learns from each mile driven. Over time, the system becomes more and more effective for each user and in each domain. Traditional vibe coding assistants also learn (e.g., Copilot refines suggestions based on your codebase), but the learning is narrower (mainly about code style, not outcomes in the world). Landbase’s AI is learning what business strategies bear fruit.

For decision-makers, the implication is that while a general AI like GPT-4 could theoretically write a sales email if prompted, it’s not enough to run a full VibeGTM motion. Landbase’s technology advantage lies in integrating the full stack of GTM tasks with an AI that has domain expertise and can take actions autonomously. This is not trivial to build from scratch. It’s why Landbase, founded in 2024 by experienced entrepreneurs (Daniel Saks, co-founder of AppDirect), invested in being the first mover with an agentic GTM model – carving out a technological lead that is hard for others to replicate quickly. They effectively built a vertical AI solution, whereas vibe coding largely leverages horizontal AI tools.

From a strategic standpoint, using Landbase’s VibeGTM is more comparable to hiring an AI-powered consultancy than using a simple tool. It’s a holistic system. This is reflected in how Landbase goes to market as well – they have an Agentic AI Lab to keep advancing the tech and even an agency network to help clients succeed with the platform(1). They recognize that technology adoption in GTM isn’t just plug-and-play; often some change management and expertise helps. This is different from vibe coding tools, which are usually self-serve and purely product-led (developers just install a plugin). The extra layer of support Landbase provides (blending human expertise and AI, as they emphasize) indicates that VibeGTM technology, while powerful, is deployed in partnership with businesses to reshape their processes, not just as a casual assistant.

In short, vibe coding and VibeGTM both use cutting-edge AI, but one size does not fit all. Vibe coding rides on the coattails of general LLMs trained on code and is delivered as lightweight tools for devs. VibeGTM runs on a purpose-built, multi-agent AI ensemble trained on sales data and is delivered as an enterprise-grade platform. For companies evaluating solutions, understanding this difference is key. If you try to use a generic chatbot to do your GTM, you’ll likely hit a ceiling – it won’t know your context deeply, and it can’t take autonomous actions safely. Landbase’s VibeGTM, on the other hand, was engineered to be your GTM co-pilot from day one, with guardrails, data, and integrations needed for real business use.

Embracing the Vibe: How to Leverage Vibe Coding and VibeGTM in Your Business

By now, it’s clear that both vibe coding and VibeGTM represent a significant shift in how work gets done – shifting many tasks from humans to AI, and freeing up humans to do higher-value thinking. The question for business leaders and professionals is: How can we practically embrace these trends to stay ahead?

1. Start with a pilot in a low-risk area. Whether it’s coding or GTM, a prudent first step is to experiment. For vibe coding, this might mean allowing your software team to use AI assistants on an internal tool or non-critical project to get familiar with the workflow. For VibeGTM, you could identify a particular campaign or segment that’s not core to your revenue and let Landbase’s AI run with it as a trial. Treat it as an A/B test: AI-driven campaign vs. your normal process. Early pilots often build confidence. For example, one sales team might test Landbase on a dormant lead list that hadn’t been touched in a year – if the AI manages to revive some of those leads with clever emails, that’s immediate proof of value. Keep the scope defined, measure results, and iterate. Many companies find that initial successes make it easier to get buy-in for broader AI adoption.

2. Educate and involve your team. A common misconception is that AI will replace humans wholesale. In reality – and this has been echoed by early vibe coding practitioners – the best outcomes come when humans collaborate with AI, not just turn it on blindly(3). Make sure your team understands that vibe coding or VibeGTM are tools to enhance their capabilities, not threats to their jobs. Involve your sales reps in the process of refining AI-generated content; their feedback about message tone or customer pain points will train the AI to be even better for your specific context. Similarly, developers should review and learn from AI-written code – it can actually be a learning opportunity to see how the AI approaches problems. By fostering a mindset of AI as a teammate, you’ll reduce resistance and get more value. At Landbase’s clients, for instance, SDRs who initially feared being replaced ended up appreciating that the AI took over the drudgery, allowing them to focus on live conversations where their skills shine. It’s worth noting that 97% of business owners believe ChatGPT (and by extension AI tools) will help their business(5), but employees need to see it helping them personally. So highlight wins like, “AI saved you 5 hours this week – now you can spend that time closing deals or building client relationships.”

3. Leverage data – yours and external – to maximize AI effectiveness. VibeGTM works best when it has rich data to chew on. Internally, integrate your CRM and marketing data with the platform so it learns from your history (Landbase can use a company’s past email performance, for example, to tailor its model). Externally, take advantage of the data Landbase provides (their massive B2B contact database and intent signals). A telecom firm might feed in its customer profiles and let the AI find lookalikes in Landbase’s database, using criteria a human might not think of. The more the AI knows, the better the vibes it can operate on. For vibe coding, feeding your codebase or style guides to the AI can help it align with your standards – for instance, tools allow you to provide example code or tests so the AI writes code that passes them. Essentially, don’t treat these AI solutions as black boxes; treat them as adaptive systems that you can train with the right data for superior results. Landbase’s platform, for one, allows customization and learning based on your feedback – utilize that by consistently tagging what a “good” vs “bad” lead or email looks like for you, so the AI gets smarter in targeting and messaging.

4. Monitor, measure, and maintain oversight. Even after you adopt VibeGTM, keep humans in the loop for oversight, especially in the initial stages. This is not because the AI is likely to go rogue, but because nuances in business (or code) sometimes require a judgment call. For sales, ensure someone reviews the AI’s messaging periodically for brand alignment and checks that the campaign outcomes align with quality leads (not just quantity). You might set up a dashboard to track open rates, reply rates, conversion rates of AI-led campaigns vs. historical benchmarks – Landbase’s analytics can help with that. If something seems off (e.g., a particular sequence underperforming), the team can adjust parameters or provide feedback to the AI. Essentially, treat the AI as an apprentice – capable of doing a lot, but still benefiting from mentorship. Over time, as trust builds and the AI consistently meets or exceeds targets, you can dial back the level of human review. Many Landbase customers find that after a few months, the AI’s suggestions are so on-point that they rarely need to edit outreach content – they shift to focusing on the increase in meetings and deals coming from the campaigns. Similarly, developers who use vibe coding tools often start by double-checking every AI-generated line, but soon learn to trust the AI for routine tasks and only deeply review the critical logic. The goal is a calibrated balance where human oversight is there, but not a bottleneck.

5. Address compliance and ethics proactively. With AI taking on actions like sending emails or generating content, ensure you have guidelines to prevent any mishaps. Landbase’s system has built-in compliance checks (for opt-outs, regional regulations like GDPR, etc.) – make sure those are configured for your needs. For example, a commercial real estate outreach might need to avoid certain statements that could be seen as investment advice; those should be communicated to the Landbase team so the AI can be tuned accordingly. In vibe coding, if your company has policies on open-source licensing or code security, ensure the AI suggestions are vetted for compliance with those (e.g., avoid copying large chunks of code from unknown sources). The good news is that AI can actually enhance compliance – Landbase’s AI, for instance, automatically manages opt-out lists and respects communication preferences, reducing the risk of human error in sending an email to someone who unsubscribed. It even keeps messaging on-script to avoid unapproved claims. But it’s important to set these guardrails early. Engage your legal or compliance team in reviewing the AI’s approach. This builds confidence that AI isn’t a wildcard but a controlled, strategic asset.

By following the above steps, organizations in telecom, CRE, managed services, and beyond can gradually and successfully integrate both vibe coding and VibeGTM into their operations. The benefits – from faster time-to-market, to cost savings, to higher conversion rates – are too significant to ignore. As one study highlighted, 81% of sales teams are either experimenting with or fully using AI in some capacity already(4). Those who haven’t started risk falling behind competitors who can engage customers faster and more effectively with AI’s help. The same goes for software development: teams not leveraging AI may struggle to match the rapid iteration and output of those that do.

The era of AI-augmented work is here. The “vibe” revolution, whether in coding or go-to-market, is all about reclaiming our time and focusing on what humans do best – creativity, strategy, relationship-building – while delegating the rest to capable AI agents. As Andrej Karpathy humorously noted, vibe coding can feel like you “barely even touch the keyboard” and just let ideas flow(3). Landbase’s vision for VibeGTM is analogous: you barely have to touch the tedious parts of GTM execution, you just set the direction and watch pipeline flow. Companies that embrace this mindset stand to unlock unprecedented efficiency and agility.

Conclusion: Embrace the VibeGTM Revolution in GTM Strategy

Both vibe coding and VibeGTM highlight a transformative truth: when humans and AI collaborate, the sum is far greater than the parts. Developers have learned that by embracing AI “co-pilots,” they can ship software faster and focus on innovation. Now, sales and marketing leaders are discovering that by harnessing an agentic AI like Landbase’s VibeGTM, they can supercharge their go-to-market execution and focus on strategic growth initiatives rather than manual toil.

For professionals in telecom, commercial real estate, managed services, or any sector that runs on B2B relationships, the message is clear: Don’t get left behind in the AI-driven GTM wave. Early adopters are already seeing outsized gains – more leads, faster deal cycles, and lower costs. The comparison between vibe coding and VibeGTM isn’t just academic; it’s a roadmap for how work is evolving. Just as writing code by hand is giving way to guiding code with AI, the days of building pipeline solely through human effort are numbered. The future of GTM is agentic, intelligent, and incredibly efficient.

Landbase, with its first-of-its-kind agentic AI platform for GTM, is positioning itself as the category leader in this new era of go-to-market. The company not only provides powerful technology but has demonstrated a commitment to customer success (through its AI lab, support network, and continuous innovation)(1). This means when you partner with Landbase, you’re not just buying software – you’re gaining a cutting-edge AI team member that’s constantly improving and working tirelessly for your revenue goals.

Ready to experience the power of VibeGTM for yourself? Now is the time to take action. Start by exploring how Landbase’s agentic AI platform can fit into your organization’s GTM strategy. Consider running a pilot campaign and see the results firsthand – the numbers and ROI will speak louder than any words. As the saying goes, the best way to predict the future is to create it. By adopting VibeGTM, you’re not only predicting the future of sales and marketing – you’re actively creating a future where your go-to-market engine is smarter, faster, and more adaptable than ever before.

Embrace the VibeGTM revolution and put your go-to-market on autopilot. Landbase is here to help you lead this change, with confidence, as a true category leader in AI-powered GTM. Don’t work for your software – let your software work for you, so you can reclaim your day and do more of what you love. It’s time to let AI set the vibe for unprecedented growth.

References

1. landbase.com
2. ibm.com
3. simonwillison.net
4. salesforce.com
5. blog.hubspot.com

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