We didn’t become an AI company. We started out that way.

When we founded Knock AI at the end of 2023, we knew we weren’t going to hire large teams. Every function had to be designed so AI could do the heavy lifting, while humans focused on strategy, creativity, context, and relationships.

So we set a simple rule: AI does what it’s best at. Humans do what they’re best at. We win when they work together.

We’re three founders. No SDRs, no RevOps, no sales team. And we crossed $1 million in ARR in our first year.

Here’s how we made it happen (and how you can apply the same playbook).

How AI Powers Every Function

Marketing

We built automations with n8n that scan LinkedIn, Reddit, and X in real time for conversations that matter. When a relevant post pops up, the AI identifies it, explains why it’s worth engaging with, and suggests a comment. That package goes straight into Slack, where a human edits and posts the final reply.

We don’t follow a fixed content calendar. We just show up in the right conversations at the right time.

Customer Learning & GTM Strategy

Every demo call, email and Slack conversation is transcribed and analyzed with AI. It extracts every question, objection, and recurring theme shared by prospects. That insight helps us shape our content strategy, build features people actually need, and onboard using the authentic voice of the customer.

These insights shape how we position, sell, and scale our GTM motion.

Sales Funnel

We run our own sales funnel entirely on Knock AI. Inbound leads are enriched, qualified, prioritized, and engaged in real time. Fit and intent signals drive automated workflows that determine channel, message, and CTA. AI agents handle everything from demo booking to LinkedIn outreach.

Product

Before we build anything, we validate it. We use Figma Make to prototype and present product concepts as if they’re already live. This lets us collect feedback early and refine GTM direction without writing a line of code.

AI supports the process with UX writing, product documentation, and edge case detection.

Development

We use CodeRabbit to streamline pull request reviews. If something breaks in production, Claude checks the logs, analyzes the code, and suggests a fix or alerts the right person. Support, CS, and product teams can ask AI in Slack how something was built or troubleshoot issues without waiting for engineering.

Business and Product Analysis

We built an internal AI analyst right into Slack. Any team member can ask questions about usage, pipeline, or product performance and get real-time answers.

People

We use Notebook LLM to create a podcast-style experience that explains our product, customers, position, and approach. Listeners can ask questions in natural language during the sessions and get instant answers.

How We Train and Manage AI Agents

We treat AI agents like team members. We track their performance, improve their workflows, and retire them if they’re not creating value. If a task can be fully owned by an agent, we automate it. If it requires creativity, judgment, or relationship-building, a human takes it.

Every role, whether human or AI, must earn its place by contributing to growth.

What We’ll Never Use AI For

We don’t use AI to build relationships. That’s one of our superpowers.

The way we talk to prospects and customers matters. How we listen. How we respond. How we earn trust. These moments shape the experience we deliver, and they’re one of the strongest differentiators we have.

AI can enrich the context. It can suggest the next step and document the journey. But the conversation itself stays human. That part doesn’t change.

The Impact of Building AI-First

With only three founders, we crossed $1M in ARR in our first year.

Knock AI handled lead enrichment, qualification, engagement, follow-up, and CRM sync. That let us scale efficiently without hiring a traditional go-to-market team.

This approach shaped every workflow, every handoff, and every product decision we made. We gave each function a clear role, whether owned by a human or an AI agent. It helped us move faster, stay focused, and give customers a better experience.

The same model is within reach for any early team willing to build for AI-first from day one.