24:I[50237,["/_next/static/chunks/0db4v-xi1q-jq.js","/_next/static/chunks/02-tqo9.1..63.js","/_next/static/chunks/0d3shmwh5_nmn.js","/_next/static/chunks/12wcqrolhhiqu.js"],"Posts"] 25:T528,Hi HN!

I'm an SEO and AI search consultant. I've spent years creating topical maps and content strategies for brands and that led me to building Floyi.

I’ve seen over the years, long before AI-generated content, how content strategies started with individual keywords and disconnected article ideas. Teams published more, but organic traffic stalled and sometimes declined because the content focus was fragmented.

That’s why I always start by defining the brand, what it wants to be known for, and their buyers’ needs. Then I turn that context into topical research, a topical map, and a content publishing plan.

The problem I kept having was keeping the brand’s context across the separate tools, documents, and spreadsheets throughout the workflow. By the time you were ready to start a brief or writing, you had to remember to find the brand and writing guidelines first to ensure the brand’s voice was intact.

I built Floyi to keep the process in one workflow, carrying brand/audience context from research to mapping to content briefs to articles.

You can try it here for free: https://app.floyi.com/

I would appreciate feedback on improvements, especially where the workflow feels fragmented.26:T524,During my work at Brokk last year we developed a task-slicing system. The idea was to have a bunch of tasks where each task can be implemented and verified in isolation. So I can mentally focus only on one task at a time with checking the evidence it works as expected. Most follow-up tasks are based on their predecessor(s).

After my time at Brokk I picked up this idea and developed Casefile. To avoid loading the entire previous session context, the agent creates a task log. So a follow-up task only needs to load the necessary task logs + git state as the base to implement its task. Each log is linked to its commit, so git blame on a line leads back to the decision behind it. Another advantage of this approach is that you can retrieve the intent why a code change was made and which alternative solutions were skipped. You can see the workflow in the open at https://github.com/native-federation/devtools.

Last month I extended the system to store the plan and task logs in a non-public Casefile repository because my enterprise customers don't allow work artifacts like these in their repositories.

Give it a shot if you think it's useful. I would like to hear your feedback!27:T484,Hey all,

TLDR: When you sign up you get an email alias @audioreality.ai that you can use to sign up for newsletters, have agents send output to, etc. Once a day you get a private podcast with a multi-host format/conversation, so it’s not a basic summary and it’s not a verbatim readout. You can configure multiple shows too, so I personally have some based on different subjects I’m interested in.

I built this because I have much more opportunity to listen to content than sit and read (exercising, commuting, background noise), but I find a lot of really valuable newsletters out there. So I’ve been trying to dial in a tolerable AI-generated format to get the info out in a way that’s easy for me to consume.

This opened a few adjacent use cases like having scheduled agents email research, Google News style updates, etc. (even top HN feed stuff).

I’d love feedback on the format approach, the script quality, “host” behaviors/personalities, and anything else. The audio quality is a constant work in progress as I test different audio models (and I completely understand if audio AI totally creeps you out).

Thanks!

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