How do you accelerate experimentation?
Compressing the path from idea to data with new AI tools
Welcome to the Experimenter’s Edge newsletter. Great to have you here!
Go from AI and product ideas to evidence in weeks. We help you validate fast, stop the wrong ideas early, and make decisions with data, not opinions.
Join 3,000+ pretotypers, product leaders, and experimenters getting hands-on tactics for rapid experimentation. Not theory, real techniques you can use this week.
The Real Goal: Finding the Best Ideas to Invest In
Experimentation is great, but what you’re really looking for is the best ideas to invest in. The goal is to run as many experiments as possible as fast as possible to reduce your time to data, while still keeping the human element and diversity of thinking. Gather ideas, prioritize, design experiments, run them, get feedback, and make decisions.
We’ve been exploring how to compress each of these steps using new AI capabilities, drawing on thousands of experiments we’ve run and the body of knowledge based on pretotyping.
Compressing Each Step of the Innovation Process
Let’s break this down step by step to see how we can speed up each stage.
1. Compress the brainstorming
We’ve been experimenting with a tool to generate quality, reasonably unique ideas based on understanding your company, your competitors, and your strategic goals. It can generate 10, 20, 50, or even 100 reasonably good ideas, which then go straight into the platform for evaluation.
2. Augment the prioritisation step
This is still a judgment call for your teams to prioritise, but we built a tool to quickly assess the idea. it’s still in the pretotype phase, but you can try it here. I’d love your feedback.
3. Speed up the Exploration phase
This is where the AI tools have really been effective. We’ve used our knowledge from thousands of experiments and Lean Canvases we’ve built to embed best practices for doing pretotyping and rapid experimentation at scale in the real world, while considering risk, governance, and legal constraints, of course with fully anonymised data. We’re able to take a first pass at evaluating your idea, generate a Lean Canvas, and suggest a reasonable XYZ hypothesis. It’s still a work in progress, but it’s exciting to see how we can make this go faster for you.
4. Get to experimenting as fast as possible
We’re also experimenting with a tool to recommend and suggest experiments for your particular business, its stage, and what you’re trying to learn. And we’re getting really good results from this. So watch this space.
5. Build and run the experiments
Up until now, with the variety and complexity of customers we’ve worked with, we haven’t run experiments on their behalf and we might still not do that. And that is often a bottleneck on how to get access to resources and engineering talent. But with the advent of AI we’ve been testing how you can spin up quality safe experiments within a day or two. They conform to brand, risk, and compliance, and we get them out the door fast.
Spotted in the Wild
I’ve been eating my own dog food. Here’s what I built over the past 8 weeks experimenting with Claude Code:
1. Exponentially Platform re-platforming (37 hours)
Consolidated and rebuilt the entire platform with AI-accelerated features.
2. Custom time management system (22 hours)
100% tailored to my workflow instead of settling for 80% SaaS solutions.
3. Property research automation (2 hours)
Built on a Friday night. Auto-generates research summaries for property inspections, tracks preferences, and surfaced pre-inspection details we never would have found manually.
4. Pipedrive sales bot
Connects Claude to our CRM. Summarises deals, drafts follow-ups, flags stale opportunities. Replaced manual pipeline reviews.
5. Claude Ralph (open source)
Autonomous AI development loop for Claude Code. Runs overnight and builds features without manual intervention. github.com/LeslieCBarry/claude-ralph
The So What: $80,000 to $90,000 Saved
By my estimate, I’ve saved about $80,000 to $90,000 by doing this. That’s real money that would have gone to SaaS subscriptions and development costs, and ongoing cost-avoidance for 2026.
How to Get Started
So how do you activate this? What’s your next experiment?
Have a look at all the services that you use and ask AI to brainstorm with you on the parts that you actually use, not the 80% that you don’t. See if you can build that yourself.
The space is moving fast, so get your hands on the tools, whatever your role. You’ll be amazed.
A quick example: I’ve fully replaced Zapier, Rebrandly, and multiple other tools by building exactly what I needed.
Tool of the Month
After 20 years away from coding, Claude Code has reminded me that everything is code. If you’re not doing this, you’re missing a superpower to accelerate your understanding of what’s possible. I’ve shipped more working tools and platform updates this month than we did in the last year.
https://github.com/LeslieCBarry/claude-ralph
Here’s my best tip from the past few weeks: I found and tested a way to build features autonomously with a self-improvement loop. The tool is called Ralph, and it’s been incredibly useful. I modified it to use Claude Code instead of AMP, and it ran flawlessly, building a new feature in just a few hours.
Thanks to Greg Isenberg and Ryan Carson for getting this walkthrough out there so fast. Follow them if you want actionable, practical tips and tools in this space.
Find the Best Ideas to Invest In
I work with teams to go from ideas to evidence in weeks. We embed rapid experimentation using pretotyping as a core capability to validate fast, stop the wrong ideas early, and invest in the winners.
👉 If you want to hear more about how we do this, happy to do a 15 or 30 min free call. Just reply.
👉 If you’d like to try any of these tools I’ve mentioned in their current pretotyping state, reach out and I’m happy to share the links with you.
“Run as many experiments as possible as fast as possible to reduce your time to data.”
Until next month, happy innovating!
Leslie