Modern GTM teams are increasingly turning to AI agents: autonomous AI-powered assistants, to turbocharge every part of the revenue funnel. Tools like Anthropic’s Claude AI Agents and HubSpot’s Agent.ai suite are automating tasks from coding and content creation to prospecting and support.
These “agentic” systems can write code, answer customer questions, personalise outreach, and more – all in natural language. For revenue leaders, the promise is huge: faster deployment of campaigns, smarter sales plays, and 24/7 customer service without hiring extra headcount.
As Paul Sullivan of Arise GTM™ (author of Go To Market Uncovered) advises, the key is aligning these agents within a strategic framework so they amplify, not scatter, your GTM efforts.
With Claude Code and HubSpot AI Agents, SaaS teams can offload repetitive work and focus on strategy. Throughout this article, we’ll dive into how Anthropic AI Agents and HubSpot AI Agents work, best practices for using them (including Claude Code tips), and real case studies of impact.
We’ll cover use cases for Marketing, Sales, Customer Success, RevOps, and Product teams, and show how Arise GTM’s methodology helps embed these tools for maximum ROI. Let’s explore how “AI GTM Strategy” is reshaping SaaS growth, with a wink and a plan, so your team can hit targets faster.
Anthropic’s Claude Code is a new command-line, agentic coding tool that “lives in your terminal, understands your codebase, and helps you code faster through natural language commands”. In practice, a developer installs the @anthropic-ai/claude-code package (via npm install -g @anthropic-ai/claude-code) and then simply runs claude in their project directory.
The Claude Code agent automatically pulls in context (like code files and docs) and can execute tasks such as writing functions, fixing bugs, creating tests, or even handling Git operations.
For example, a product team could ask Claude to “generate a Python script to pull lead data from our CRM API,” or “write unit tests for this sales-email formatter.” Anthropic’s docs recommend setting up a CLAUDE.md file in each repo with project-specific tips (coding style, common commands, environment notes) so the agent knows your conventions. This lets Claude follow your rules (e.g. “use ES modules”) without repeated prompts.
Key Capabilities: Claude Code can edit code, fix bugs, answer questions about architecture, run tests, search git history, resolve conflicts, and draft commits/PRs. For GTM product teams, this means less manual coding and faster delivery of marketing or analytics tools.
Best Practices: Anthropic suggests customising your environment to speed things up (e.g. limiting context windows) and using CLAUDE.md docs for project rules. For GTM projects, you might include sample campaigns or data schemas. Starting with small, concrete tasks (and verifying outputs) helps the agent learn your workflow.
Example Setup: Install Node.js 18+, run npm install -g @anthropic-ai/claude-code, then run claude. The first time, it will do a one-time OAuth setup. After that, you can chat with Claude in the terminal like an AI pair programmer. (Think of it like a supercharged code completion – but with real conversation!)
Case Study: Companies are already using Claude-style agents in support and operations. For instance, Tidio (an e-commerce chat software) launched Lyro, a customer-service agent powered by Claude. With Lyro, Tidio automatically resolves up to 90% of support inquiries, achieving 71% ticket automation in chat and email and handling 2 million+ conversations via AI. In effect, Claude Code enabled Tidio to build an agent that trains on past tickets and “learns” to answer common questions, freeing human agents for tougher problems.
Similarly, Intercom’s AI support agent “Fin” (built with Claude) resolves up to 86% of incoming support volume with human-quality answers, cutting response times from 30 minutes to seconds. These real-world wins show that Claude AI agents can deliver enterprise-grade support and development acceleration.
Even for non-engineers, creating a simple Claude-based agent is straightforward. The Claude Code CLI lets you interact step by step. For instance:
Install & Initialise: Follow Anthropic’s guide to install Claude Code (no sudo!) and run claude in your project folder.
Give a Task: At the claude> prompt, type something like Explain what this SQL function does or Write a script to query new leads from our API.
Iterate: Claude will answer or generate code. You can ask clarifying questions or ask it to fix errors. For example: claude> Use a different library for HTTP requests or claude> Add error handling to the Python script.
Review & Commit: Once satisfied, you can have Claude draft a commit message or even create a pull request with the changes.
By crafting clear, stepwise prompts, you turn Claude into a code assistant. Anthropic’s documentation and communities provide more examples, but the gist is: the agent encodes your intent and can even modify its own output based on feedback. Over time, your team refines its Claude usage patterns (e.g. through CLAUDE.md), which is exactly what Arise GTM™ advises: establishing repeatable processes so everyone “speaks” to AI the same way, ensuring alignment.
HubSpot has been rolling out its Breeze AI Agents, a suite of AI tools embedded in the CRM to help every GTM function. As of Spring 2025, major AI agents include:
Content Agent: An AI copywriter in Marketing Hub. It “helps marketers create and scale content across channels” – from blog posts to emails to podcasts. The agent can ingest your uploaded brand guidelines and past content, suggest better blog topics, write meta descriptions, or even draft follow-up emails. For example, marketers might ask Content Agent: “Draft a LinkedIn post about our new fintech feature.”
Prospecting Agent: Built into Sales Hub (and the new Target Accounts app), this agent researches target accounts, personalises outreach, and even initiates engagement. In practice, a rep selects an account in the CRM, launches the agent, and it scours internal data plus public sources (websites, news, LinkedIn) to summarise the company, key contacts, and recent initiatives.
It can then suggest a custom email or LinkedIn message. The enhanced agent learns your product and persona selling profiles, so it tailors its approach by market or product line.
Customer & Knowledge Base Agents: In Service Hub, HubSpot now offers a Customer Agent chatbot and a Knowledge Base Agent that work together. The Customer Agent can be deployed 24/7 to auto-respond to support tickets and chat inquiries, pulling answers from your knowledge base and documentation.
HubSpot reports that customers using this AI Customer Agent “resolve over 50% of support tickets and spend nearly 40% less time closing them”. (Independent coverage says the average resolution is ~52%, with top customers hitting 90% ticket deflection.)
The new Knowledge Base Agent works behind the scenes to find gaps in your docs. If an incoming question has no good answer, it identifies that gap so teams can expand the KB – a multi-agent orchestration that keeps training data fresh.
HubSpot has branded this network Agent.ai – a “professional network of AI agents” for marketing, sales, customer success and ops. At their 2024 Spotlight, HubSpot even teased an upcoming Agent Builder tool so customers can create custom AI agents on the platform. (Imagine building an “EventBot Agent” that knows your unique ticketing policies!) For now, you can get started with the out-of-the-box agents above via the HubSpot UI (no coding required).
For example, to spin up a simple Customer Chatbot: go to your HubSpot account, navigate to Automation > Chatflows, choose Create Chatflow → Customer agent, and connect it to your knowledge base. The result is an AI bot that answers common FAQs automatically.
HubSpot AI Agents – Team Benefits:
Marketing: Content Agent rapidly drafts and optimises marketing copy. For instance, it can automatically generate confirmation emails, craft metadata for SEO, or even brainstorm campaign ideas. Marketers save hours on copywriting and can double down on creative strategy.
Sales: Prospecting Agent saves reps from manual research. Instead of combing Crunchbase and LinkedIn, the agent delivers account insights with one click. This accelerates pipeline building. (HubSpot’s data shows it “can even engage prospects, helping sales teams build pipeline faster”.)
Service: Customer and KB Agents drastically cut support load. Agents answer routine questions and perform simple tasks (e.g. order status or password resets) on their own. This frees CS teams to focus on complex issues and proactive outreach, and delivers 24/7 support without hiring.
Case Study: The impact is already evident in HubSpot users’ success. According to HubSpot’s own exec Andy Pitre, their Customer Agent now “resolves an average of 52% of customer issues, with some HubSpot customers reporting resolutions as high as 90%”. TechTarget reports that clients are using these Breeze agents to scale support and marketing with fewer resources. (And HubSpot provides 100 free credits to get started with Agent.ai, a risk-free sandbox.)
AI agents are not a one-off novelty as they weave into every part of a SaaS go-to-market strategy:
Marketing & Growth: Beyond the Content Agent, GTM teams use AI for lead scoring, segmentation, and personalisation. HubSpot’s new Lookalike Lists (in Marketing Hub Enterprise) analyses your Smart CRM to generate lists of “soon-to-be customers” based on patterns from your best accounts. Agents can also automate ABM tasks: for example, an AI agent could update Target Account lists by pulling in firmographic data.
In campaign planning, Claude or HubSpot AI can analyse past performance data and suggest next best offers. Arise GTM emphasises data-driven messaging, and AI can surface insights like which value props resonate most with each segment.
Sales: The combination of HubSpot’s Prospecting Agent and agentic AI coding transforms the sales toolkit. Reps can ask Claude-like agents to draft personalised outreach, then switch to the CRM’s agent to gather account intel.
For example, a rep might type a natural-language prompt: “HubSpot, find me the latest news on Acme Corp and draft a follow-up email mentioning their product launch.” HubSpot’s Prospecting Agent already does this research step and even starts an email thread on their behalf.
Bonus: Claude Code can integrate with sales dev kits. A RevOps engineer could use Claude to auto-generate API calls or workflow scripts for HubSpot to automate enrichment.
Customer Success & Support: We’ve seen above how Claude-powered agents (Tidio, Intercom, Decagon) and HubSpot’s agents relieve support teams. For instance, Decagon’s platform now uses Claude to give “white-glove customer service at scale” across industries. They report 70% fewer mistaken responses (“over-inferencing”) and drastically lower support volume by letting AI agents complete tasks for customers (not just answer FAQs). Claude agents literally “check eligibility and process refunds” automatically.
The lesson for CS managers: AI agents can not only speed up ticket handling but also perform end-to-end actions behind the scenes. That means higher customer satisfaction and shorter time-to-resolution, while the human CSMs focus on proactive outreach or churn prevention.
Product & Engineering: Product teams can leverage agentic coding to accelerate feature delivery and integrate AI capabilities into the product itself. Claude Code enables faster prototype iteration (e.g. generating front-end templates or analytics pipelines via prompts).
Meanwhile, HubSpot’s ecosystem allows product teams to build smarter integrations: for example, a SaaS app could plug into HubSpot and use its Customer Agent to offer in-app support, or use HubSpot’s AI content tools for generating product documentation. In short, AI agents are tools that your tools can use.
The Arise GTM methodology underscores the importance of aligning product roadmaps with market needs, and agents provide new capabilities (like automated account insights) that product managers can prioritise.
RevOps & Strategy: RevOps can harness AI to keep data clean and processes lean. Consider an AI agent that scans CRM data to identify missing contact info or flag accounts for follow-up. HubSpot’s Journey Automation (with AI-driven insights) helps RevOps teams “create personalized customer experiences with an easy-to-use builder”.
Revenue forecasting can also be improved: for example, an AI tool could analyse past deal data and external signals to adjust forecasts more accurately. And of course, Arise GTM’s focus on user data means agents can be used to surface user segmentation insights.
The upshot: RevOps leaders who leverage agents will see more reliable pipeline predictions and can allocate resources (ad budget and SDR time) against data-driven targets.
In all these roles, the common thread is efficiency and scale. A cheeky way to put it: AI agents can handle the “tyranny of to-dos” so your teams can think and strategise. Imagine asking an agent, “What are our top 3 marketing channels given last quarter’s ROI?” or “Summarise feedback from 200 support tickets”. The answer comes back in seconds. That’s the power Anthropic and HubSpot are bringing into the GTM suite – and Arise GTM helps weave it into your existing playbook.
None of this technology delivers value on its own. It needs to be harnessed within a strong GTM framework. That’s where Arise GTM™ comes in. Paul Sullivan, former CTO/CMO and author of Go To Market Uncovered, developed the ARISE methodology to align all teams around a unified strategy, operations, and execution. In essence, Arise GTM™ teaches companies to integrate customer data, refine positioning/ICP, and synchronise go-to-market motions, now including AI adoption.
Arise GTM advocates a data-first approach: feed your AI agents the right inputs (customer segments, brand voice, and policy rules) so they deliver strategic value. For example, Arise consultancies would help you build that CLAUDE.md and onboarding for Claude Code, or define a governance model for HubSpot’s agents (who can see what data, who approves responses, etc.).
By training teams and iterating on the AI’s role in sales/marketing processes, Arise ensures the agents don’t just automate noise, but actually move the needle on KPIs. (After all, “agents” don’t replace strategic thinking; they amplify it when used correctly.)
In practice, companies working with Arise GTM have used AI in their pilots. Paul Sullivan often cites client stories where AI went live within 30 days, aligned with messaging tweaks. He emphasises human-AI collaboration: we’re aiming for an “AI team member”, not a replacement. Wiley recently published his book Go To Market Uncovered in 2025, offering more on this integrated approach.
The takeaway: To stay ahead, SaaS leaders should explore AI Agents within a structured GTM program. Leverage Claude’s agentic coding for dev ops, and HubSpot’s Breeze agents for front-line teams – but do it with an overarching plan. Arise GTM™ can guide you through that plan, from vision to execution.
An AI agent is a system that performs tasks autonomously via natural language. Unlike fixed chatbots, agents like Claude or HubSpot Breeze can plan, act, and iterate in complex workflows. They “think” in context: reading your codebase, database, or docs, then writing or doing tasks for you.
In GTM, an AI agent might draft an email campaign, build a sales report, or resolve a customer query – all after you give it a prompt. Anthropic’s Claude and HubSpot’s agents are leading examples of this trend. (See how Claude Code runs in your terminal, and HubSpot’s agents plug into Marketing/Sales/Service hubs.)
Claude AI (via the Claude Code tool or API) can speed up development and analytics tasks. Developers use Claude Code to refactor code, generate tests, and answer codebase questions.
Product teams can also use Claude models (through Claude Code or Anthropic API) to analyse large data sets (like sales trends or survey comments) and summarise insights.
On the GTM side, Claude agents can automate customer support answers and internal reports – for example, Decagon’s Claude-based agents perform routine support tasks end-to-end. Best of all, Claude focuses on accuracy and safety.
For instance, Claude 3.7 “ranks highest on honesty, jailbreak resistance, and brand safety” among LLMs, which means your agents will generally follow guidelines (especially if you codify them in a CLAUDE.md) and avoid risky outputs.
HubSpot AI Agents (often branded as Breeze Agents) are built into the HubSpot CRM platform. They cover content, marketing, sales, and support:
The Content Agent drafts and optimises marketing content (blogs, emails, social media copy, etc.) and can automate tasks like writing meta descriptions.
The Prospecting Agent conducts account research and personalises sales outreach with just a few clicks.
The Customer Agent chatbot auto-responds to support queries 24/7, pulling from your knowledge base.
The Knowledge Base Agent spots gaps in your help docs and helps fill them, so the Customer Agent keeps learning.
In short, HubSpot’s agents tackle the repetitive GTM tasks: writing copy, researching leads, answering FAQS, letting your teams focus on strategy.
Absolutely. Real-world stats show dramatic gains. Tidio’s Claude-powered agent achieved 71% automation of its own support tickets. Intercom’s Claude-based Fin agent handles 86% of incoming support volume and gets a 51% resolution rate out of the box.
HubSpot reports customers resolving 50–90% of support tickets via Customer Agent. Marketing teams using Content Agent have doubled content output by auto-generating blog and email drafts. Sales teams using Prospecting Agent find and contact leads faster, with initial trials showing it “helps build pipeline faster”.
Even on safety, Claude has a strong reputation: it consistently “follows instructions and adheres to prompts better than alternatives,” according to user CTOs. These cases validate that AI agents can pay off quickly in a SaaS GTM context.
Start small with a pilot and the right support. Anthropic’s Claude Code is in beta: try it on a non-critical project (their docs and GitHub have setup guides). For HubSpot, turn on the AI features in your CRM (they roll out to existing HubSpot users in 2024–25). Build a simple agent: for example, use HubSpot’s chatflow to create a Customer Agent linked to one knowledge base.
Monitor the results and train your team on best practices. Key tip: involve your Arise GTM or RevOps analysts early. Define success metrics (ticket deflection rate, campaign turnaround time) and review outcomes weekly.
As you scale, apply Arise GTM’s methodology: align the new AI agents to your messaging and target profiles, and iterate process changes. When in doubt, consult experts. Paul Sullivan’s Arise GTM team specialises in this AI+GTM journey.
Arise GTM™ weaves AI adoption into a bigger alignment playbook. Paul Sullivan’s methodology (the ARISE framework) ensures that before deploying any new tool, teams are unified around who the customer is and how to talk about value. In practice, this means Arise would help you set up Claude Code and HubSpot agents in lockstep with your positioning and ICP.
They emphasise a “human-first” tone (so the AI output always sounds on-brand and friendly), and they build governance (who reviews agent output, how to update knowledge bases, etc.).
Think of Arise GTM as the project manager for your AI rollout – making sure every department knows its role, from Marketing to DevOps. (Paul’s recently published book, Go To Market Uncovered, has a whole chapter on digital transformation, including AI.) By the end, you’ll have an integrated AI GTM Strategy: software that works for your people, not the other way around.
Ready to Supercharge Your GTM? Archetypal GTM leaders are already on board with AI agents. Claude and HubSpot have created the tools; Arise GTM provides the roadmap. To see how AI agents can fit into your B2B SaaS strategy, reach out to Paul Sullivan and the Arise GTM team today.
They specialise in guiding SaaS and fintech teams to “arise” with new tech: aligning people, processes, and agents for better growth. (Remember, even a cheeky AI intern needs a human manager – that’s what Arise does best!)