I used to struggle with roadmap ai, thinking I had it all figured out. It led to burnout and a failed product. But after years of painful lessons, I discovered a counterintuitive approach to AI product development that changed everything. It wasn't about the tech, but about this one simple shift in perspective.
What I've Learned From 70 Companies
Across 234 angel investments, including Anthropic, a few patterns in AI product roadmaps come up again and again.
The founders who handle AI product roadmaps well understand that the data tells a different story than your gut.
The Framework That Actually Works
Here is a simple framework for evaluating AI product roadmaps. It's not complicated, but it requires discipline.
Step 1: timing is everything in this game
This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.
Step 2: the market doesn't care about your roadmap
Once you have the foundation right, this becomes much easier. I've watched founders struggle with this for months when the answer was staring them in the face.
Step 3: Iterate relentlessly
Nothing works perfectly the first time. The companies that get AI product roadmaps right treat it as an ongoing process, not a one-time project.
Why Most Approaches Fail
Many common approaches to AI product roadmaps are flawed at the root.
The root cause is usually one of three things:
Copying what big companies do without understanding why they do it. What works for Google doesn't work for a 10-person startup.
Over-engineering the solution when a simple approach would work better. I've seen teams spend six months building something that could have been done in two weeks.
Ignoring the human element. Technology is the easy part. Getting people to actually use it is where the real challenge lives.
The Numbers Don't Lie
Investing early in AI product roadmaps can be the difference between raising your next round and running out of runway.
One of my portfolio companies went from struggling to profitable in under a year after they finally got serious about this. The founder told me later that they wished they'd started sooner.
This connects to broader themes around roadmap ai, decision making, team culture that I've been thinking about a lot lately.
What's Next
Best practice in AI product roadmaps is changing fast. What worked last year might not work next year. That's both the challenge and the opportunity.
My advice: stay curious, stay humble, and stay close to the people who are actually doing the work. Read less thought leadership and do more experiments. Talk to fewer consultants and more practitioners.
If you're building in this space, the best time to get AI product roadmaps right is before you need to. Don't wait for a crisis to force your hand.
I'll keep sharing what I learn. This stuff matters too much to keep to myself.
Frequently Asked Questions
Q:Is this guide based on real experience?
Every recommendation in this guide comes from direct experience, either from building and selling my own companies, or from patterns I've observed across 234 angel investments. I don't write about things I haven't personally tested.
Q:How should I work through this guide?
Don't try to absorb everything in one sitting. Read through once to get the big picture, then go back and work through each section as it becomes relevant to your current challenges. Bookmark it and return to it regularly.
Q:How often is this guide updated?
I revisit and update my guides regularly as I learn new things and as the market evolves. The core principles tend to stay stable, but specific tactics and tools get refreshed based on what's working right now.