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Everyone dreads the “black hole” of resume submissions, but most tools stop at grammar checks or bland tips. You’ve taken a universally frustrating experience and injected it with humor, personality, and actual utility.


As it stands the tool looks very generic. Having built a CRM, my advice to you is to focus on a nice and wrap around the workflows incredibly well. For instance you could build a CRM for beauty spas that allows clients to book appointments, track treatment histories, and purchase product refills in a few clicks. Integrate features like automated reminders for upcoming appointments, personalized skincare regimen suggestions based on past services, or loyalty programs tailored to frequent spa-goers. By deeply understanding the unique needs of your niche (e.g., handling last-minute cancellations, upselling add-on services, or managing seasonal promotions), your CRM becomes indispensable. Generic tools can’t compete with a solution that feels custom-built for their daily grind.

Your differentiator isn’t just features—it’s how intuitively your product solves real headaches for a specific audience. Start by obsessing over one niche’s pain points, then expand.


Amazing advice, thanks a lot. You feel like tech start-ups are too broad of a niche ?


We've been using Leaptable.us (https://leaptable.us/) which is much more simple (it's in beta) however's execution engine is open-source and it's support for AI Agents is the very promising.

We've found it hard to Justify Airtable within our organization. Practically 90% of it's functionality overlaps with Notion databases which users already have and is ingrained within our org deeply.


Leaptable GitHub sign in fails. User verification fails after email login. Unable to use; seems more Alpha than Beta.


Your post has the largest item ID. You are amazing.


NNext.ai | Software Engineer | Python | Full-time | NY, NY, USA | Remote

At NNext.ai (read “Next.ai”), we believe that the true power of LLMs lies in agentic behavior. By engineering a system that draws on LLMs' emergent abilities and providing an ecosystem that supports environmental interactions for tabular data, we can fully realize the full potential of models like GPT-4.

We are building building core infrastructure to simplify the process of building, deploying, and managing LLM-powered AI agents on tabular data, making it the most efficient solution available. NNext AI enables users to combine the power of Large Language Models (LLMs) like GPT with tools like the browser and Google Search, greatly increasing your productivity on workflows you once spent countless hours on. We are building a framework specialized for tabular data such as Spread sheets, Database Tables and CSVs, thereby taking advantage of the similarities and co-dependencies amongst data.

We are lean team of engineers looking for our first full time OSS contributor. Desirable experience includes distributed systems working with tools like Celery, Dash and Redis Streams. Visibility on Github is a huge plus. Show us previous OSS software you’ve contributed to or public personal projects with significant usage.

Website: https://nnext.ai

Github: https://github.com/nnextai/aigent

Email: sup@nnext.us


This is cool. What kind of prompts are you running in the background to improve the prose? How can I direct the prose in a certain way - say if I wanted my text to be official or funny?

We are building a GPT integration as well that helps users analyze reviews. Check out our demo https://show.nnext.ai/


You can ask it to rewrite the given prose and make it funnier. If the given text is already kinda funny it should spice it up. If it doesnt have much material, gpt may likely hallucinate some material to get it to be funny


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