While studying Python, FastAPI, LLMs, and AI, I decided to stop just watching tutorials and start building.

I created AI Assistant v1 - a chat that answers technical DevOps and Kubernetes questions in a clear, fast, and practical way.

Everything runs 100% locally on my machine with no paid APIs.

What it does now:

- Explains Kubernetes concepts (Pods, Deployments, Services, Ingress, etc.)

- Provides real-world examples and useful kubectl commands

- Includes best practices for cloud-native environments

- Answers like an experienced Senior DevOps Engineer

Tech stack I used (built from scratch):

- Frontend: Streamlit (clean chat interface)

- Backend: Python - FastAPI (async /analyze endpoint)

- LLM: Ollama + Llama 3.2:3b (using OpenAI compatible client)

- Prompt Engineering: Optimized system prompt

I tested it with questions like “What is a Pod in Kubernetes?” and the improvement was huge.

It’s still an MVP with room for improvement, but seeing it work locally really shows me how powerful local LLMs can be for developers and DevOps engineers and also to create a big products.

I’ll upload the full project to GitHub soon with a proper README, requirements, and setup instructions.

below are some screenshots.

If you want the code once it’s on GitHub, just let me know.

Is there some Discord Server? I would like to trade ideas.

I’m exploring an idea and want honest feedback before going deeper.

Thinking of building something for solopreneurs and founders:

A single page where you can:

• list all your products in one place
• add context (what it does, link, status)
• show traction (MRR, users, growth)
• Product journey documentation
• less than 2 mins setup time
• track analytics
• Subscriber Capture
• Zero Friction Updates, 0 line of code to write (100% no code)

share one link when someone asks “what are you working on?”, link in bio but for solopreneurs and founders focused.

So instead of:

• scattered links
• random posts
• personal sites / Notion pages

you have a clean, structured place focused on your products + outcomes. so the question is as a solopreneur and founder will you pay and use it ?

If you're interested, fill out this quick 11 questions form

I'm a solo founder. I've been running TikTok ads and large scale UGC (scaled 2 apps to 100k+ users and 1 acquistion) for my own app and kept hitting the same wall: there was no good way to know what UGC creative formats were actually working right now across my category.

Tools like AdSpy exist but they're expensive, bloated, and built for e-commerce. For mobile app founders, the data that matters is different — hook formats, emotional angles, engagement by app category, what's trending vs. what's saturated.

So I built HackUGC (hackugc.com).

What it does:
- Shows trending TikTok videos in your industry/category
- AI-analyzes patterns across high-performing creatives (hook types, pacing, emotional framing, CTA styles)
- Lets you see engagement rates broken down by category
- Gives you the data to write better UGC briefs

The core insight that shaped it: most app founders brief UGC creators based on what they think sounds good, not what the data shows is working. This shifts that.

What I built it with: Next.js, TikTok data API, Claude Opus API for pattern analysis.

Biggest thing I learned building it: the hardest part wasn't the tech, it was figuring out how to surface insights in a way that was actually actionable, not just data for data's sake. "Here are 500 trending videos" is useless. "The top 3 hook patterns in productivity apps this week" is useful.

If you're running TikTok UGC and want to check it out, I'd genuinely love feedback from builders. The only way for it to be a succesful product worth sharing, would be if i were able to use it to scale my own apps. Clearly that's working so next I want to add tools that will 100x my research.

Successful ones never stop working after publication.

To most founders, content is a visibility game: create, publish, get noticed, and forget about it. But this is only half of the strategy. The other half is creating content that compounds over time.

Your content doesn’t need to go viral for it to compound. Successful founder content is a valuable asset that ranks, earns trust, and attracts traffic, long after being published.

Achieving this requires a system, not just a publishing calendar.

Here is a breakdown of what a sound content strategy looks like.

1. Capture ideas consistently.

Document all insights as they happen, through voice notes, meeting notes, and informal discussions.

2. Align with search intent.

The insight is yours as the founder. Align your content with what the target audience is already searching for..

3. Create long-form content.

Turn your ideas into deep dive articles or comprehensive guides.

4. Use multiple formats.

Create LinkedIn posts, videos, and other content formats in addition to the long-form articles.

5. Build over time.

The content forms support each other to deliver value.

Visibility isn't built overnight. But with the right tools, every piece compounds and this moves you forward.

Read the full framework here: https://penmocontent.com/the-visibility-multiplier-how-founder-content-accelerates-company-seo-and-brand-awareness/

Salam everyone,

I’ve been working on a Quran app focused on a clean and simple experience — no ads, no clutter, just reading and listening.

Main focus:

• 📖 Easy reading (Mushaf-style)
• 🎧 Simple audio playback
• ⚡ Lightweight and fast

I’d really appreciate any feedback, especially from people who regularly use Quran apps.

Here’s the link:
https://play.google.com/store/apps/details?id=com.codelady.quran

Thank you 🤍

Hey r/StartupSoloFounder 👋

I'm a Java developer working in insurance (yes, legacy systems, yes, WebSphere — I've seen things). For years I watched business teams struggle to get data out of internal APIs. They'd file tickets, wait days, and still get the wrong report. Meanwhile, the API docs were right there in Swagger files that nobody outside engineering could read.

So I built Alesqui Intelligence — an AI assistant where you upload your Swagger/OpenAPI spec and it generates a conversational agent that can discover, call, and explain your APIs in natural language.

What it does

• You upload your Swagger/OpenAPI spec (and optionally a Postman Collection to enrich context with examples)
• The system parses and unifies them into a single knowledge base
• Users chat in natural language → the AI agent figures out which endpoints to call, executes them, and streams back the answer with step-by-step reasoning
• It can also filter, aggregate, generate charts, and export to Excel
• Fully responsive — works on desktop and mobile, so field teams can query APIs from their phone
• Full RBAC: admins control which teams see which APIs

The "why should I care" version

Think of it as "ChatGPT but it actually talks to your company's APIs" — except it's self-hosted, so your data never leaves your infrastructure.

🎬 Quick demo: https://www.youtube.com/watch?v=dRJc_Pn4Ypo

Tech stack

• Backend: Java 21, Spring Boot 3.5, WebFlux (fully reactive), Spring AI 1.0
• AI: ReAct pattern with tool calling (LLM-agnostic, currently using GPT-4o-mini)
• Database: MongoDB 7.0 with Reactive Streams
• Frontend: React 19
• Auth: JWT + RBAC (3 roles: SuperAdmin, IT, Business)
• Deployment: Docker multi-stage builds, self-hosted or cloud trial

Architecture

Backend architecture diagram

The backend follows a reactive pipeline end-to-end. When a user sends a message, it hits the Chat Engine which orchestrates a ReAct loop — the AI reasons about which tools to use (list_apis, inspect_endpoint, call_api, filter, aggregate, chart, export), executes them, and streams the reasoning steps back via SSE. This means users see what the AI is doing in real time, not just the final answer.

Some things I learned building this

1. Spring AI's Tool abstraction is genuinely great. Defining tools as annotated methods and letting the framework handle the function-calling protocol saved me weeks. The ReAct loop basically writes itself once your tools are well-defined.
2. Reactive + SSE is the right call for AI streaming. WebFlux with SSE gives you backpressure for free. When the AI is thinking, the client sees real-time "STATUS" events with each reasoning step. It transforms the UX from "waiting for a black box" to "watching the agent work."
3. The "Unified Format" abstraction was key. Supporting both Swagger and Postman meant I needed a common internal representation. This also made the AI's job easier — instead of dealing with format-specific quirks, it reasons about a clean, normalized API definition.
4. Enterprise features aren't optional, even for side projects. If you want companies to actually deploy your tool, you need audit logging, RBAC, password reset flows, and deployment modes from day one. I built both a CORPORATE mode (admin manages users) and a TRIAL mode (self-registration with 14-day expiry).

Current status

• Cloud trial is live (you can sign up and test with your own Swagger files)
• Self-hosted distribution package available via Docker Compose
• Landing page: alesqui.com
• Source code:
  • Backend (Java 21, Spring Boot, WebFlux, Spring AI)
  • Frontend (React 19)

What's next

I'm exploring adding support for multiple LLM providers configurable by the admin from the dashboard — so companies locked out of OpenAI by policy can still use the platform. Also planning a usage analytics layer with cost tracking per team, so admins can monitor API calls, LLM token consumption, and justify ROI internally.

Feedback welcome

I'd love to hear your thoughts — on the architecture, the product, the approach, anything. If you work with internal APIs and this resonates, I'd especially love to know what features would make this useful for your team.

Thanks for reading! Happy to answer any questions.

I'm a solo founder. I've been running TikTok ads and large scale UGC (scaled 2 apps to 100k+ users and 1 acquistion) for my own app and kept hitting the same wall: there was no good way to know what UGC creative formats were actually working right now across my category.

Tools like AdSpy exist but they're expensive, bloated, and built for e-commerce. For mobile app founders, the data that matters is different — hook formats, emotional angles, engagement by app category, what's trending vs. what's saturated.

So I built HackUGC (hackugc.com).

What it does:
- Shows trending TikTok videos in your industry/category
- AI-analyzes patterns across high-performing creatives (hook types, pacing, emotional framing, CTA styles)
- Lets you see engagement rates broken down by category
- Gives you the data to write better UGC briefs

The core insight that shaped it: most app founders brief UGC creators based on what they think sounds good, not what the data shows is working. This shifts that.

What I built it with: Next.js, TikTok data API, Claude Opus API for pattern analysis.

Biggest thing I learned building it: the hardest part wasn't the tech, it was figuring out how to surface insights in a way that was actually actionable, not just data for data's sake. "Here are 500 trending videos" is useless. "The top 3 hook patterns in productivity apps this week" is useful.

If you're running TikTok UGC and want to check it out, I'd genuinely love feedback from builders. The only way for it to be a succesful product worth sharing, would be if i were able to use it to scale my own apps. Clearly that's working so next I want to add tools that will 100x my research.

Hi everyone,

I have build a Blockchain with some unique features.

All details here -

https://github.com/jcinfosolution-hash/Uracil-Labs

Requesting everyone to please have a visit and give feedback, suggestions if any.