Daniel Janisch

Most A/B testing tools are built for data teams at scale. Dashboards with dozens of metrics, feature flags, statistical engines that require a full-time analyst to operate. I wanted something different: a tool for one person making product decisions with limited data and limited time.

Blazeway started from a simple observation. Teams run experiments, get results, and move on. Six months later nobody remembers why a decision was made or what was tested before. The learning disappears. The same experiments get repeated. The same mistakes get made.

So I built an experiment journal. A place where every test has a hypothesis, check-ins as data arrives, and a documented learning when it's done. Not another analytics dashboard. A decision trail that compounds over time.

Seven Years of Running Experiments

I've spent the last seven years running experiments on products. Different stacks, different markets, one consistent pattern: the teams that learned fastest were the ones who wrote down their hypotheses before the test and their takeaways after. Most didn't.

Years before I started Blazeway, I ran a test on automated offers, betting that a shorter time-to-offer would lift sales. It didn't. Customers preferred to speak with a consultant first. They had too many questions, and wanted the offer to feel tailored to their specific situation rather than instant. The fastest path was not the best path. That's the kind of counterintuitive result that quietly disappears when nobody documents it.

On @deliverhonestly I share the same loop in public: assumption, test, result, learning. Not polished case studies, just the real trail of experiments while I build Blazeway, with concrete examples of how I validate the assumptions behind every decision.

Deliver Honestly

I build Blazeway in public. Every hypothesis I test, every result I get, every failure I document. Bold bets mostly fail. That's where the real learning happens, and where trust gets built. An audience that watches someone make a public bet, fail, and document it honestly develops more trust than one that only sees polished success stories.

That's not just a philosophy. It's how the product works. Blazeway turns every experiment into a learning artifact: hypothesis, outcome, insight. The same loop I run publicly, the tool helps you run on your product.