Going forward by looking back

Tag: AI Tools

  • Spotlight on Kelsey Parks: Helping Startups Build Systems That Stick

    One of the best parts of doing interviews for Kinsta Talks is getting to sit down with people I already know—but haven’t yet had the chance to really dig in with. That was the case with Kelsey Parks, a local friend, fellow WordPress Meetup organizer here in Durango, and the co-founder of Psyche Digital.

    We recently sat down to talk about her journey into marketing, what she’s learned from years of working with startups, and how her agency helps founders build the kind of systems that don’t just survive—they scale.

    From Startups to Systems

    Kelsey’s path into agency life didn’t begin with marketing degrees or a traditional agency climb. It started with startups—and with chaos.

    “I got completely addicted to the unemployable startup founder,” she told me. “The oddballs in a warehouse, making cool things happen from thin air.”

    After stints in D.C. and China—where she helped Chinese companies position themselves for North American markets—Kelsey eventually returned to Southwest Colorado and teamed up with her childhood friend (and now business partner), Kate. The two had stayed connected since the third grade, and they launched Psyche Digital together to serve companies during one of the most intense phases of business: the early growth stage.

    Why Systems Matter

    Kelsey works with founders who are often at a critical juncture—what she calls the “we’re going to make it or we’re not going to be here in a year” phase. Rather than overwhelm them with trendy marketing tactics, Psyche Digital focuses on something more sustainable: building repeatable systems.

    One line really stuck with me:

    “Another thing that’s important to startup founders is knowing that the work we’re doing isn’t going to be lost when they bring in their own marketing team.”

    That mindset—treating systems as something founders can keep—feels like the kind of long-term thinking a lot of fast-moving businesses forget to prioritize.

    On AI and Interns

    We also talked about AI, of course.

    Kelsey doesn’t see AI as a threat. She sees it as a tool. Specifically:

    “I think of AI as part of my workforce—more like an intern in my workforce.”

    That framing resonated. Use AI to gather ideas, generate outlines, or even write drafts—but then let your experts take it from there. It’s not about replacing creativity. It’s about removing bottlenecks.

    Meet Her at the Meetup

    In addition to running an agency, Kelsey co-hosts the Durango WordPress Meetup with me. She’s been instrumental in building a welcoming space for folks working with WordPress across the Four Corners.

    If you’re a local and haven’t joined us yet—now’s a good time. We meet monthly, and our conversations are always lively (and occasionally spicy—like Kelsey’s favorite Sichuan food from her days in Chengdu).

    Watch the Full Interview

    You can watch the full interview on YouTube here:

    🎥 How Psyche Digital Helps Startups Build Systems That Stick

  • What Cooking Taught Me About Using AI Tools

    Early Food Memories

    I grew up around food. Not in a Michelin-star kitchen or a trendy farm-to-table bistro, but in my mom’s deli store—where we sold everything from stacked sandwiches to Beluga caviar. It wasn’t fancy, but it was serious about quality. We catered to some high-end tourists, and I got exposed to ingredients most kids didn’t know existed. Brie, Camembert, Muenster—you name it, I tried it.

    It’s a bit ironic now that I’m vegan, given how much cheese was part of my early palate, but that upbringing gave me an appreciation for good food and the craft of making it.

    The Chef That Wasn’t

    That appreciation followed me for a while. I worked in kitchens during college and even considered culinary school. But after enough shifts in hot commercial kitchens—sweating over fryers, sprinting through prep lists, getting burned both literally and metaphorically—I realized professional cooking might not be the dream. Hard work, low pay, and not enough creative spark for me.

    Much later, I flirted with the idea of becoming a vegetable farmer. That dream wilted too, once I understood how truly hard farming is. Again, deep respect. Again, not quite my path.

    Why This Matters Now

    So why bring all this up on a blog about media and technology?

    Because every experience we have—failed careers, childhood snacks, prep shifts in hot kitchens—builds the lens through which we see the world. Lately, I’ve been thinking a lot about how large language models like ChatGPT fit into that lens. And one answer I keep circling back to is this:

    They’re most useful when you bring something to the table.

    The Art of Prep (and Prompting)

    Let me explain. I’ve been using ChatGPT to help me with meal planning. Not just one-off recipe suggestions, but complete weekly meal plans: multiple dinners, tailored to our diet (vegan), with full ingredient lists, caloric targets, and bulk prep checklists.

    Last week it gave me five solid meals: zucchini fritters, a butternut lentil shepherd’s pie, a Thai-style curry, a stir-fry, and something I’m now forgetting—but all delicious. I gave it the ingredients I had on hand, asked for meals to serve four, and it generated the full plan, shopping list, and prep workflow.

    I spent Sunday doing all the bulk prep—chopping, steaming, roasting. Just like a line cook in a restaurant. The biggest difference between home cooking and restaurant cooking is preparation. Once you have things chopped and portioned, making a meal on a Tuesday night takes 20 minutes instead of 60.

    The Festival Twist

    This week was different. Kate and I are heading to a bluegrass festival halfway through the week, so I had ChatGPT help me create four one-pot meals we could reheat easily in a trailer. We froze some, packed others, and just like that, festival food was solved.

    Was it perfect? No. The shopping list still takes some cleanup. Getting it into Apple Reminders involves a little copy-paste dance. But the value is there—and it keeps getting better.

    Experience Still Matters

    Here’s the key point though: this works because I know how to cook. I’ve been cooking for over 40 years. I can glance at a recipe and tell if it’s going to work—or not. I’ve chopped every vegetable under the sun, cooked rice a thousand ways, burned things and salvaged them. That experience matters.

    LLMs don’t replace knowledge. They amplify it.

    If you don’t know the difference between sauté and simmer, it won’t matter how good the recipe looks. If you can’t taste for salt, AI won’t help you. But if you’ve got some knowledge—just enough to see patterns, evaluate options, and tweak where needed—then these tools can be transformative.

    The Tools Are Here. Use Them.

    There’s a lot of debate out there about AI tools. Some people think they’re going to take over the world. Others think they’re glorified spell checkers. I live somewhere in the big, messy middle. They’re not magic. They’re not junk. They’re useful.

    You don’t need to be a technologist to try them. Just be curious. Give them something to work with. Treat them like a very fast, mildly unreliable intern. And then—like in cooking—trust your taste.

    Explore. Experiment. Prompt boldly. Adjust generously.

    Who knows? You might end up with a perfect zucchini fritter. Or a new way of thinking.