7 karma · joined August 24, 2025
I look for the signal in the AI noise and build products around it. Product design, architecture, engineering, all of it, solo. What I'm building right now is on https://www.linefeed.be.
I spent years in large organizations, building, then architecting, then advising. Valuable years, but the builder in me never left. Then I left. Advising is fine, building is what I love.
Here I write down what I see. The AI news as it lands, my read on it, and the field notes from building every day: what breaks, what it costs, what I would bet on. Opinions included, that is rather the point.
I test this stuff before I have an opinion on it. So if you want to know what actually works before your organization finds out the expensive way, this feed runs a few months ahead of the reports.
Core insight: Generative AI solved idea scarcity but created analysis paralysis. Founders need "auditing" tools (SWOT, PESTEL), not just more brainstorming chatbots.
Curious how others filter the noise from the signal in their AI workflows.
The core problem: chatbots are conversationalists, not systematic thought partners. No separation between creative generation and analytical validation.
The article breaks down why this matters and how separating divergent thinking from convergent analysis transforms AI brainstorming.
Curious if others have hit similar walls with unstructured AI ideation.
Production blocking accounts for 90%+ of the problem. Only one person talks at a time. You're either losing ideas while waiting or checking out to preserve them.
What surprised me: this has been proven since the 1990s. Individuals working alone generate more ideas AND better ideas than groups. Yet we keep running these sessions.
Brainwriting beats brainstorming by 42% on originality. Write ideas before sharing. No production blocking, no dominant voices.
I built Brain Hurricane because I needed a systematic process instead of waiting for ideas that never come. Proven frameworks (SCAMPER, Six Thinking Hats) + AI pattern recognition.
I'd love feedback on whether this matches your experience and what's actually worked for you.
The problem is that humans get stuck in design fixation. We recycle the same ideas. AI has the opposite problem—it hallucinates nonsense when you push it toward novelty. But for creative divergence, that's exactly what you want.
The trick is separating phases: let AI go wild during ideation, then apply human judgment to filter and refine.
The post covers practical techniques and guardrails so creative outputs don't get mistaken for facts.
Anyone else deliberately prompting AI to be "wrong" in controlled contexts? What's worked for you?
Here's the clickable link for anyone interested: https://brainhurricane.ai
I'm working on Brain Hurricane (brainhurricane.ai). It's the kind of structured tool I wish I'd had in my career. I was tired of unstructured brainstorming sessions that recycled the same ideas and the passive waiting for a "great idea" that never arrives.
My goal was to create a systematic process. It uses AI to help you generate ideas with proven methods like SCAMPER and Six Thinking Hats, then immediately analyze them with frameworks like SWOT, PESTEL, and the Business Model Canvas. It's about moving from a fuzzy concept to a validated idea with more confidence and clarity.
On a personal level, this project was my way of diving headfirst into modern AI development. I'm building it with Next.js, TypeScript, Python, and Linux, which has been a fun and humbling experience coming from a more traditional enterprise stack.
It's still early, but the core features are live. I'd genuinely appreciate any feedback from the HN community, especially from those who have struggled to turn abstract ideas into something concrete.
Ultimately, music is about the final output. Whether the creator is a human with a guitar or an algorithm on a GPU is less important to me than the feeling the track evokes