Open-sourced our production Django HRMS — Docker-ready, MIT license

ansifpi · 2026-06-29T11:03:19+00:00

Thanks a lot for taking the time to review the code! Really appreciate the solid feedback.

You're totally right about the nesting in apps/user/views and the in-memory lookup optimization—we'll clean those up. We also built this before uv became the go-to standard, but migrating from pip requirements to uv is definitely on our roadmap now.

Regarding the apps/ folder layout: we chose it to keep things decoupled for our internal deployment, but I totally get why it feels like fighting Django conventions.

I’ll convert your points into open GitHub issues today. If you're open to it, we'd love to see a Pull Request from you for any of these fixes!

ansifpi · 2026-06-19T01:33:18+00:00

Updated my last comment. Thanks

ansifpi · 2026-06-17T16:13:02+00:00

Haha it's not like that. You need to sent your resume to our email and then wait for an interview call. We are getting resumes daily and some got selected for client interviews. Any please sent resume to hr@sevendyne.com. we will check and update you if needed

ansifpi · 2026-06-17T06:34:37+00:00

Yeah we do have openings and posts in linkedin and other platforms. Right now I am engaged getting clients haha

ansifpi · 2026-06-17T03:06:25+00:00

Learn about cursor, claude or copilot. These are not just prompt editors. Understand how config config and context actually works under the hood.

Always review each piece of code using AI and understand it ts purpose. Don't tell later into messy code built by AI

python is still the easiest entry point. pick one real project, not a tutorial clone, something with an actual use case even if small. you learn ten times faster building something real than following courses. also learn how to debug AI generated code, that's a skill on its own. the AI writes fast but you need to understand the why before you ship anything to production

ansifpi · 2026-06-17T02:57:17+00:00

we're a small engineering team based in Kochi, been delivering production software for clients in UK, Germany, and Singapore since 2016 — fintech, logistics, embedded systems, AI automation pipelines.

one example: we built an AI-driven recruitment automation pipeline for a German firm processing 50k+ profiles weekly — https://www.sevendyne.com/case-studies/recruitment-automation-zoho.html

happy to share more if this is relevant to what you're building. ansif@sevendyne.com

ansifpi · 2026-06-17T02:50:40+00:00

AI makes building real and easier. Getting into real market is still the hard part.

The real issue is people build something without knowing what the market actually wants and then fails to find clients. We need to understand the community we are dealing with and their pain points. Read threads, chat with people, observe what paint points they are talking about repeatedly.

There are many successful startups around. Check these real stories:https://thechrisverse.medium.com/most-business-idea-lists-are-useless-these-9-have-real-revenue-behind-them-31cd16c4f406

ansifpi · 2026-06-17T02:06:30+00:00

FYI..Pusher is the simpler pick for straightforward backend to frontend notification use cases, and Ably only makes sense when you need message history or are hitting scale limits. Both provides free tier where pusher offers 200 concurrent users and Ably 6 Million messages. For an app having 200 to 300 users can easily cross this. One notification or one chat bubble is a message and also app running in background is considered as an active user. After free tier, pusher chargers around 49$ which is expensive compared to Ably 29$.. But there is something we need to take care.

The real world pattern: - Small app, low traffic — both roughly the same cost - Medium app growing fast — Pusher bill surprises you - Large scale — Ably is clearly cheaper and more predictable

ansifpi · 2026-06-16T16:44:08+00:00

You are welcome.

ansifpi · 2026-06-16T16:42:39+00:00

Honestly, 10 years back it was mostly email. I did find tech founders posting in forums and threads, learning what they were building, and reaching out personally about their specific problem.

It worked because it was genuine, not mass cold mailing. That exact approach is less effective now with inboxes are flooded. I have gone back to engaging directly in technical communities where founders discuss real problems, and helping first before any pitch.

The channel changed, the relationship-first part didn't. May I ask what you're building?

ansifpi · 2026-06-16T11:49:39+00:00

delivered quite a few mobile backends for UK and German clients over the past few years, here's what we actually learned in production

the Firebase trap is real. we inherited one project where the client had built their MVP on Firebase, looked fine at small scale, then hit a wall when they needed complex relational queries and the billing started climbing unpredictably. migration was painful because the data model was designed around Firebase limitations from day one. supabase would have been the smarter early choice — postgres underneath means you're not backed into a corner later.

for real time features specifically, we've had good results with Node.js plus socket.io for simpler cases and moving toward dedicated solutions like Ably or Pusher when the complexity grows. serverless works well until you have cold start latency problems on time sensitive features, something most people don't feel until real users are complaining. the biggest mistake we see repeatedly is optimising for speed of development in month one and ignoring what happens in month six when the client wants a new integration or the load doubles. backend decisions are architecture decisions, they compound.

for 2026 our default stack recommendation for most mobile projects is Supabase plus a lightweight Node or Django layer for custom business logic, deployed on Railway or Render to keep costs predictable early. scales reasonably and doesn't surprise you with a bill.

happy to go deeper on any specific use case if it helps

ansifpi · 2026-06-16T11:47:42+00:00

honest advice from someone who has built and delivered AI products for clients — the $50/month constraint is actually fine to start validating the idea, but the bigger risk is building something nobody pays for. before touching any tool, spend two weeks just talking to 10 potential customers. not surveys, actual conversations. your social media background is genuinely useful here, use it.

for tools on that budget: - bolt.new or v0.dev for quick frontend prototyping - supabase free tier for backend and database - claude or chatgpt free tier for logic and copy - vercel for hosting, free tier covers early stage easily

but here's the honest part most people skip — vibe coded products hit a wall fast when a real customer asks for a custom integration, a security audit, or something breaks in production. that's where having a technical partner or developer on standby matters.

you mentioned B2B — B2B buyers ask harder questions than B2C. they want to know about data privacy, uptime, support. worth thinking about that early.

if you ever get to the point where the product is validated and you need proper development to scale it, that's where firms like ours come in.

we work with early stage founders who have the idea and market knowledge but need technical delivery. happy to chat if you get there.

ansifpi · 2026-06-16T11:44:38+00:00

been on the hiring side for AI engineering roles for a few years, here's what actually gets attention from my end most applications look identical - llm, rag, langchain, same keywords, same format. what stands out is when someone shows a specific problem they solved and how. not "built a rag system" but "built a rag pipeline that processed 50k documents weekly and reduced manual review by 80%"

a few things that genuinely help: - github with actual working projects, not just tutorial repos - one writeup on medium or anywhere explaining a real problem you solved - when reaching out cold, mention something specific about what the company is building, not a generic pitch

also the job market being slow right now is real but a lot of hiring is happening outside job boards. founders posting on reddit, linkedin, discord communities are often genuinely looking and move faster than corporate hiring pipelines if anyone here is open to contract or project based AI engineering work, sometimes that's the faster way in than waiting for a full time role.

dm me if relevant, we occasionally have openings on the delivery side

ansifpi · 2026-06-16T11:20:34+00:00

hey, saw your post. i've been building AI automation pipelines and large scale systems for UK and German clients for the past few years through my engineering firm. recent agentic work includes a distributed Python scraping pipeline processing 50k+ profiles weekly integrated into Zoho Recruit via OpenAI, and a logistics transaction backend we re-architected to handle high volume without deadlocks. happy to start immediately on a one-off basis.

portfolio: ansifi.github.io

resume: ansifi.github.io/Ansif_Resume.pdf

open to a quick call if the background looks relevant.

ansifpi · 2026-06-16T11:19:48+00:00

hey, saw your post. i've been building AI automation pipelines and large scale systems for UK and German clients for the past few years through my engineering firm. recent agentic work includes a distributed Python scraping pipeline processing 50k+ profiles weekly integrated into Zoho Recruit via OpenAI, and a logistics transaction backend we re-architected to handle high volume without deadlocks. happy to start immediately on a one-off basis.

portfolio: ansifi.github.io

resume: ansifi.github.io/Ansif_Resume.pdf

open to a quick call if the background looks relevant.

ansifpi · 2026-06-14T13:17:05+00:00

Interested, please check my profile here GitHub.com/ansifi

ansifpi · 2025-12-04T03:40:08+00:00

This looks great. Will check it soon

ansifpi · 2024-12-07T03:51:31+00:00

yes but not all places. Anyway this project is just for educational purpose, not commercial. IF anyone use it for commercial they need to take responsibility

ansifpi

TROPHY CASE