Becoming AI-first

✨ Lessons from 100s of conversations on AI products and how teams are adopting AI.

Every tuesday and thursday, I take 3–5 calls with builders, CTOs, and CEOs of companies. One question on every CEO's mind is:

"How do I make my company AI-first?"

Common variations include: how can we use AI better? should we be building Agents? how do we add AI to our products?

Over time, I've identified patterns in how leading companies are approaching this question, and what separates the ones making real progress from those still in exploration mode.

What "AI-first" really means

Being AI-first doesn't mean using AI everywhere, or re-architecting you entire company or product around a chat interface.

It means understanding where intelligence creates leverage for your team, your operations, and your product. If you can identify where AI genuinely moves the needle, you're already halfway there.

Broadly, I've found three high-leverage entry points:

  1. Internal tools that improve productivity and decision-making.
  2. Workflow automation that saves time and reduces operational load.
  3. User-facing products that create revenue and differentiation.

Each represents a layer in your company's AI maturity. Let's dig in.

1. Internal Tools

These tools help your team save time, become more productive, and build intuition around AI. General-purpose agents (ChatGPT, Claude), coding assistants (Cursor, Claude Code), or vertical agents (legal, sales, marketing) all fit here. I'm yet to meet a team that's not all-in here.

These don't require a polished UX or commercial rollout — just curiosity and experimentation. The payoff is your team becoming AI-native faster than your competitors.

Most teams I speak to give everyone access to a multitude of AI tools. The cost is trivial compared to the learning dividend.

If you're not doing this already, get your team a ChatGPT subscription and cursor/CC for coding. Connect these tools to your company knowledge, databases, and documents. Let your team explore, learn, and build intuition.

2. Workflow Automation

Once your team sees what's possible, you'll start spotting repeatable patterns ripe for automation. This is where AI turns mundane tasks into automated processes that can run in the background.

Examples: invoice classification, market research, sales prep, support summarization, or daily reporting.

The highest-ROI workflows are almost always specific to your team. They take effort to design — and while "no-code" tools like N8N or Zapier can help, most serious setups eventually involve code. Frameworks like Agno can help here if you have engineering resources.

Treat automation as part of your system design, not a side project. Its ok to invest in it, if only to learn and build intuition.

3. User-Facing AI Products

This is where AI creates compounding value — by improving the product your users already love. You can:

  1. Buy off-the-shelf products that add AI-powered features to existing products (e.g., a support agent). I highly recommend this as a starting point, its easy to get started and you start seeing immediate value.
  2. Build new AI features specific to your product. The goal here is to make your product smarter, faster, and more delightful.

Your goal here isn't to "add AI" — it's to make the experience better. The best AI features often don't look like AI at all.

Our most successful case studies are ones where users don't even realize AI is at work, they just notice things getting smarter, forms getting filled automatically, and buttons that automate what was previously a 10-step manual process.

So general recommendation is to start with off-the-shelf products that add AI-powered features to your product. But once you need to build AI-features that are specific to your product, here's how to do it.

  1. Add small, reliable AI features - ideally as "magic buttons" or "magic interactions". Reliability is the keyword here.

  2. Automate targeted, well-defined problems - solve one painful step at a time. Serve the AI application as a RestAPI, which your product can call when the user clicks the "magic button".

  3. Avoid generic chatbots - they shift the cognitive load to the user and expose an incredibly vast surface area, which is bound to disappoint. Instead, build clear, purposeful interfaces that do the work for them. This will also force you to think about the user experience and how to make it more intuitive and delightful.

Each of these "magic moments" compounds. Over time, your product becomes AI-first not by branding, but by behavior.

Start simple, focus on clarity and reliability over complexity.

From exploration to execution

If you want to accelerate this journey, Agno is a starting point.

It will give you the right primitives for building AI features and a FastAPI application that you can deploy in your cloud (for privacy and security). Your product can easily integrate with this API and before you know it, you'll be serving AI features to your users.

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