Building an AI content platform for SEO teams who are tired of generic AI copy
I'm Michael, founder of Byline. Just joined Indie Hackers and figured I'd start with why I'm building this instead of a product pitch.
I spent years watching content teams use AI tools that write fast but write generic copy. The output reads like AI. It scores fine on basic SEO checks but falls apart for teams who actually need to compete: rank well, read well, and now, get cited by AI answer engines.
Byline is built specifically for that audience: experienced SEO and content practitioners, not casual bloggers. A few things that came out of building it:
Most AI writing tools optimize for one thing (usually traditional SEO) and ignore the rest. We score every piece across four dimensions: SEO, readability, GEO (generative engine optimization), and AEO (answer engine optimization). Most teams haven't even started thinking about the last two yet.
We built an Editorial Agent with three modes (Review, Assist, Auto) because not every team wants the same level of AI involvement in their editing process. Some want a second pair of eyes. Some want a co-writer. Some want to set it and check the output later.
Content quality is brand-specific. A Brand Profile system feeds tone, terminology, and positioning into every generation, so output doesn't read like it came from a tool that's never met your company.
Still early. Would genuinely value feedback from anyone here running content or SEO operations, especially if you've hit the wall where AI tools start producing forgettable copy at scale.
What's been your experience with AI content tools? Where do they actually fall short for you?
The GEO/AEO angle is the sharp part, and the one thing here that isn't already crowded. "AI writes generic copy" is what every AI writing tool now claims to solve (Jasper, Copy ai, Writer all say "on-brand, not generic"), so four-dimension scoring becomes table stakes fast. But scoring for answer-engine citation specifically is early enough that few tools do it well, and it's where content teams are genuinely anxious right now because nobody knows how to optimize for it yet.
That's your wedge, and I'd narrow the whole positioning onto it. "AI content platform for SEO teams tired of generic copy" competes with everyone. "The tool that gets your content cited by AI answer engines" competes with almost no one, and hits the exact pain keeping SEO leads up at night in 2026. GEO/AEO isn't a feature to list fourth, it's the headline.
To your question, where AI content tools fall short: they optimize the artifact, not the strategy. They'll write a great post about the wrong topic, wrong angle, wrong reader, because they don't pressure-test whether the piece should exist. The wall teams hit isn't "the copy reads like AI," it's "we're producing publishable content faster than we can decide what's worth publishing."
That strategy-vs-artifact gap is what I spend most of my time on, I'm part of the team building Hivemind, an AI strategy copilot that pressure-tests positioning and messaging rather than just generating copy. So it's the exact problem space I live in. Happy to go deeper on the GEO-first positioning if useful. Either way, lead with the answer-engine angle.
I think the shift from "AI-generated" to "AI-citable" content is one a lot of teams still underestimate. Ranking in search is no longer the only goal—being the source AI systems trust and reference is becoming just as important. That's a much more interesting problem than simply generating articles faster.