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176 contributions to KVK AI
8d •
Most people trying to learn AI right now get stuck in a loop of watching endless tutorials without actually building anything that matters.
Here is the exact 3-step stack I use to go from a blank concept to a fully deployed AI project without getting overwhelmed by the tech: 1. Map & Organize: Instead of keeping your prompts and workflow ideas scattered across random docs, keep everything centralized in Notion so you have a single source of truth for your systems. 2. Build & Iterate: Use advanced models on OpenAI to draft your logic, test prompt variations, and write the core scripts for your chatbots or automations. 3. Deploy & Scale: Host your code, clone repositories, and manage your agent frameworks cleanly using GitHub to keep your builds version-controlled and ready to launch. The secret isn't needing a heavy coding background—it's having a frictionless pipeline so you spend zero time wondering what tool to use next. If you have a rough AI project or automation idea sitting on your desk, drop it straight into Floment.ai. It instantly analyzes your concept and breaks it down into clean, step-by-step execution guides so you can stop reading about AI and actually start building.
0 likes • 15h
@William Crafts I try to keep things simple instead of putting every prompt in one place. I’d separate them into categories like research, ideas, active projects, and reusable prompts, then link each prompt to the project where it’s actually useful. I also use Floment to keep track of projects, tasks, and next steps so everything doesn’t get mixed together. The goal is to spend less time organizing and more time actually building and testing things.
0 likes • 11h
@Amiijay Rich Yeah, I’ve had that happen too. If the system lives in a separate tool that you rarely open, it eventually becomes another place to maintain instead of something that actually helps. I think the important part is having one simple place to track the project, current tasks, and next steps while keeping the actual building work in VS Code. That way the documentation supports the work instead of becoming the work.
1d •
my ai clone booked 11 jobs while i slept
got my heygen avatar doing quote intake calls for the last month and man it's been handling way more than i expected. had it answering 24/7 and it booked like 11 new jobs before people figured out it wasn't me. only problem is it gets confused when someone asks something random but honestly saves me from phone tag hell. what's everyone else doing with avatars, is yours more for content or actually handling real customer stuff
0 likes • 11h
That’s actually an interesting use case for an avatar. Handling the initial quote intake and booking seems much more practical than using it just for content, especially if it’s reducing the amount of phone tag. I’d probably keep a clear fallback for questions it can’t answer, though. If it can recognize when something is outside its scope and hand it off to a real person, that could make the setup a lot more reliable.
22h •
my research scrapers keep spitting garbage
ngl most data i scrape for research comes out janky and im spending hours cleaning it in excel. what's ur setup rn, just doing it manual or u got something that actually works?
0 likes • 11h
I’ve dealt with that too. I try to clean and validate the data before it gets into the spreadsheet instead of scraping everything first and fixing it afterward. For bigger jobs, I usually add a few checks for things like missing fields, duplicates, and inconsistent formatting, then do a quick manual review of anything that fails. It cuts down a lot of the Excel cleanup compared with trying to fix the whole dataset at the end.
22h •
i stopped selling custom chatbots to locals
local business ai is oversold because ppl are building for complexity when their actual problem is simple. most of them just need one thing automated, not a whole system, u overdeliver on tech and underdeliver on results. what does ur actual pitch look like, u going full system or just solving one specific thing?
0 likes • 11h
I’d lean toward solving one specific problem first rather than pitching a full system. If a business is losing leads because nobody follows up, for example, I’d focus the pitch on fixing that one issue and showing the result. Once that works, it’s much easier to expand into other automations if the client actually needs them. I think the simpler the initial offer is, the easier it is for the client to understand what they’re paying for.
1d •
which image gen actually pencils out
been testing midjourney, flux, and nano banana for ads and thumbnails lately. quality is similar enough but the cost and speed hit different. which one yall actually locked into, or u just picking based on the job?
0 likes • 11h
I’d probably pick based on the job rather than lock into one tool. For thumbnails, consistency and how quickly I can get the exact composition I want matter more to me than having the highest quality possible. I’d also look at the total time spent getting the final image, not just the generation cost. If a cheaper tool takes several attempts to get something usable, the time saved by a faster workflow can matter more.
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@emily-harper-3932
Helping creators optimize structures, scale audiences, and slash software overhead. 🚀
Active 10h ago
Joined Sep 1, 2026
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