Daniel Gąszczyk

Time blocking fails when you treat it like a prison. Instead of 'work on project from 10-12 PM,' I try 'explore one specific feature.' The flexibility within the constraint keeps my brain engaged. It's not about forcing focus, but protecting curiosity.

The startup timelines you see on social media are highlight reels. The reality is months of talking to users, building, realizing you're wrong, and rebuilding. If you're 8 months in and feel behind, you're probably right on track. The messy middle is the real work.

Everyone talks about finding a co-founder with complementary skills. I think that's secondary. The real challenge is finding someone with a complementary obsession level. The person who will also be thinking about the problem at 11 PM on a Tuesday. Without that, it falls apart.

Sergey Brin says you can't start Google in a garage anymore. He's right, you can't build a new foundational model that way. But you can absolutely build a profitable SaaS on top of an existing one from your laptop. The core challenge is the same as always: find a real problem.

People love seeing new UI mockups, but nobody gets excited about server monitoring or database backup automation. Yet, that's the stuff that lets you sleep at night. A solid foundation is the most important feature you can build, even if it's invisible.

Building a product is one thing, but building a cofounder relationship is the real challenge. It requires shared values, aligned commitment, and honest communication. I've learned that skillsets matter less than the shared obsession to make it work, day after day.

Everyone's worried about big tech competition, but the real threat to your startup isn't a new feature from OpenAI. It's poor user onboarding, a confusing product, or a solution nobody actually needs. Focus on solving a real problem for a specific group of people first.

My corporate analyst brain and my indie hacker brain are finally in agreement. It's all about the requirements. With AI writing the code, the quality of your product is a direct reflection of the quality of your spec. Garbage in, beautiful garbage out.

The flood of new "AI-powered" apps is overwhelming. My filter is simple: Does this tool solve a problem I actually have, or does it just create a new process I have to manage? Most of the time, a simple script is still the better answer.

I've learned that `The Mom Test` is the most important book for a founder. Don't ask "Would you use this?" Ask "How do you solve this now?" Their answers and frustrations are your real market research. This simple switch saves months of building things nobody wants.

I treat AI coding assistants as junior developers. They need precise instructions, clear examples, and well-defined scope. If I give them a vague idea, I get back creative-but-wrong code. My main job now is writing the perfect spec.

For solo founders feeling unstructured: My biggest shift wasn't working more hours, but improving my inputs. I now spend 80% of my time creating crystal-clear requirements and 20% letting AI tools handle the code. Good requirements are the ultimate structure.

My workflow has flipped. I used to spend 80% of my time coding and 20% planning. Now, with AI assistants, it's the reverse. The hard part isn't implementation; it's the detailed, unambiguous specification. Getting the requirements right is the new coding.

With AI coding assistants, the bottleneck isn't writing code anymore—it's defining the problem. I now spend most of my time on crystal-clear requirements and rapid prototyping. If you can't provide a perfect spec, AI will just generate beautiful garbage, faster.

AI coding tools have changed the game, but not how you think. The bottleneck isn't writing code anymore—it's knowing *what* to build. My process is now 80% defining clear requirements and 20% implementation with AI. Vague ideas fed to an AI just produce well-written garbage.

AI coding tools have shifted the main challenge from writing code to defining what to build. If you can't provide crystal-clear requirements, you'll just get well-written nonsense. The most valuable skill is now articulating the problem, not just coding the solution.

The biggest lie about AI development is that it replaces developers. It doesn't. It replaces ambiguity. You can't just 'vibe' a feature with an AI—you need a precise, documented plan. It's making us all systems analysts first, coders second.

I stopped asking people, "Would you use my app?" They always lie to be nice. Now I ask, "How do you currently solve this problem?" Their workarounds and frustrations tell me if there's a real need. Their words become my feature list.

My corporate job taught me the value of solid requirements. My startup journey taught me how to write them fast. With AI coding assistants, the game isn't who codes fastest, but who can define the problem most clearly. That's the real leverage.

Built a tiny habit tracker that beat my 'real' products. Secret? Copied my archery training log structure—simple, visual, daily win. Sometimes the best SaaS ideas hide in your non-tech hobbies. What everyday system could you digitize this week? 🏹 #IndieHacker #SaaS