Whenever you image experimentation in product growth, you in all probability don’t consider pipettes, enzymes, or Petri dishes. However as Dr. Christina Agapakis reminds us within the kickoff to Season 4 of Productside Tales, product groups and scientists aren’t as totally different as we’d assume.
Christina—an artificial biologist turned model builder (Oscillator founder, former SVP of Inventive & Advertising and marketing at Ginkgo Bioworks)—has lived each lives. She’s spent years in labs working experiments that fizzle out and years in boardrooms promoting tales that form billion-dollar biotech. Her verdict? Discovery isn’t a pipeline. It’s an excellent hairball of hypotheses, constraints, funding fashions, and collaboration.
Sound acquainted, PMs?
Product Administration and the Scientific Technique
The parallels are virtually one-to-one. Scientists body hypotheses, check them, analyze outcomes, and refine their fashions. Product managers do the identical with buyer issues, prototypes, and roadmaps.
However right here’s the kicker: the neat flowchart model of the scientific methodology is simply as deceptive as these “good” design pondering slides. In actuality, each science and product discovery contain detours, useless ends, and uncomfortable ambiguity.
Christina recollects educating college students who identified: “You’re not truly displaying us how to do that. You’re simply telling us to do it.” And she or he admits they had been proper. The toughest half isn’t drawing the loop. It’s navigating the judgment calls, the “this doesn’t really feel proper” moments, and the messy suggestions that by no means suits the tidy diagram.
That’s the guts of product administration and the scientific methodology: each are experiments in understanding the unknown, one iteration at a time.
Breaking Down Silos in Product Groups
One in every of Christina’s most sensible classes is that silos exist in each science and product. In labs, there’s a wall between “pure” analysis and utility. In product orgs, engineering, design, and advertising usually run on separate tracks.
The consequence? Friction, misalignment, and missed alternatives.
Christina describes sitting in rooms with scientists, engineers, and entrepreneurs—all fixing the identical drawback, however from utterly totally different angles. What truly unlocked progress wasn’t higher handoffs, however cross-pollination. The CRISPR professional and the microbial sequencing professional wanted to be in the identical dialog, simply as PMs and buyer success managers must co-create options collectively.
For product leaders, breaking down silos in product groups is much less about reorganizing bins on an org chart and extra about creating shared language, shared constraints, and shared outcomes. Silos don’t vanish—you simply cease letting them block the circulate of perception.
Failure as Information in Innovation
If experimentation in product growth has a patron saint, it’s failure. Christina places it bluntly: most scientific experiments don’t “work” within the typical sense. However disproved hypotheses nonetheless generate information.
The identical precept applies in product. Too many groups nonetheless deal with failure as wasted effort as a substitute of information. The truth is, each dead-end prototype or rejected roadmap merchandise provides to your collective understanding—of your clients, your constraints, your market.
And the price of avoiding failure is worse. As Rina Alexin (Productside CEO and podcast host) warns, whole groups have burned years constructing merchandise that by no means obtained adoption—as a result of they weren’t allowed to validate early and fail small. That’s not simply a monetary loss; it’s a folks loss.
Productside’s strategy (and Christina’s scientific actuality) are aligned: failure as information in innovation is the one method ahead. The quicker you gather suggestions, the much less painful it’s.
Staying with the Bother in Product Administration
Christina brings in Donna Haraway’s well-known phrase: “stick with the difficulty.” In science and in product, the work is inherently messy. Retreating into sanitized frameworks or lab silos is tempting, however unhelpful.
For PMs, staying with the difficulty in product administration means resisting the urge to oversimplify complexity away. It means sitting in the anomaly, iterating in the actual world, and leaning into the friction factors the place precise influence is solid.
It’s not comfy. However neither is ignoring actuality till your “good” plan collapses in market.
Funding, Constraints, and Who Decides What Ships
One of the fascinating components of Christina’s story is her candid have a look at funding. In science, authorities grants, personal donors, or analysis organizations resolve what will get studied. In product, budgets, incentives, and buyers resolve what will get shipped.
The similarity? Who pays shapes what will get constructed.
That actuality test is essential for product leaders. Your roadmap doesn’t simply mirror buyer wants—it displays monetary pressures, institutional incentives, and typically even politics. Acknowledging that doesn’t make you much less customer-centric. It makes you trustworthy.
Why Experimentation in Product Growth Issues
Don’t give it some thought as chasing good solutions. It’s about:
- Operating discovery as a loop, not a pipeline.
- Treating failure as information, not disgrace.
- Breaking down silos so information truly travels.
- Accepting that incentives form outcomes.
- Constructing tales that transfer execs, groups, and clients—not simply tidy slides.
Whether or not you’re managing microbes or managing metrics, the mindset is similar: experiment, keep curious, and stick with the difficulty.
