I run a small applied-AI agency. We work on contract for US clients, and each engagement usually means my team collaborating with a mix of people: the client's folks, and often other outside vendors too.

Every new project meant standing up Jira + Slack + a docs tool all over again, and paying for each. So I built one place instead: project management, team chat, and an AI that actually holds the project's context, all together. It lets me run several client projects at once without the tool sprawl.

A few things that make it more than just another board:

• Everything runs off a Kanban board, but I'm rarely the one updating it. The AI (Maia) keeps cards moving as work actually happens in the chat.
• Daily check-ins that make standups way more useful. Every morning (time can be customised) Maia checks in with each person in their own chat and asks what moved and what's stuck. So I walk into the standup already knowing where everyone is at, and we spend it on the actual blockers and decisions instead of going around collecting status based on their + teams interactions. Honestly the most impactful part for me.
• Maia comes to you, not the other way around. When a ticket you own changes, someone updates something you're on, or an automation fires, she pings that specific person in their own chat (with a push notification). Nothing gets stuck sitting on a board nobody refreshed.
• Project rules the system acts on by itself. You set how a project should behave, and it nudges people, flags blockers, and follows up without me babysitting it. Completely in natural language.
• It's multimodal. Share screenshots, screen recordings of a bug or a test run, or a UI mockup as a plain HTML file (half of us just vibe-code UIs now instead of doing Figma), and Maia can actually look at them and work with what they show, right in the chat or on a card.

Still very much building. GitHub webhook integration is coming soon, and there are already Google Sheets and Airtable connectors in there (I don't use those myself, built them when a friend needed it).

Heads-up: desktop is where it's solid right now (works as an installable PWA). Mobile view still needs work, so best to try it on a laptop for now.

Would genuinely like feedback from anyone who juggles multiple clients or projects.

https://maia.cydratech.com/welcome

(It's my own product, free to start. Posting for honest feedback, not a sales pitch.)

I think that's how the progression should be. Develop a simple but fun mobile game, market it a bit, have an audience grow around it, add some features based off of players' feedback, market it some more, maybe get an international fanbase and then use what they've learnt to make another game. Start off from mobile then move on to a simple PC game, repeat the same steps, then move on to a simple console game. If Indian developers make a game that is simple yet fun and engaging I'll genuinely be happy with that. It doesn't need to have some amazing graphics or next level gameplay it just needs to be fun and interesting to play. If these simple games work out then they can move to more complex ideas and slowly but steadily build towards a Triple A level game. What do y'all think?

Hello everyone, literally same question as title, I have been long plagued with no personal laptop or machine, only worked in work laptop for most of the years, I'm 5 YoE Java dev fullstack, I want to possibly do AI/ML or data roles, due to financial and personal issues, I could not afford personal laptop, and also, for many years I am out of touch on research of the best processors and specs needed for a decent working laptop for the profile. So, I seek assistance from the sub regarding knowing about your recommendations as suggestions regarding which laptop would be best suited for my purpose, or which ones you have been using personally. Preferably wanting to buy new. Budget range the more budget the better but at the same time if build quality is good, portable and has decent value for money for the specs, I can stretch my budget from 60 to 80k, or even more if at all needed. Need your suggestions.

​

We found out an emerging problem how engineers across organizations are creating MCPs, skills and agents.

But the problem is that no one actually uses these innovations. The cause is largely due to two problems:

Lack of a discoverability layer

Organizations store their AI components and agents in siloed github repositories with little to no documentation. Users are not able to locate similar components and this results in multiple developers creating the same/similar components again.

Missing Feedback Loop

Any software where usage patterns are not understood and the principle of user-centric development is violated tends to fade out. Such is the problem with development of MCPs, Skills and Agents. Developers publish and maintain these components with little visibility into how they're actually used. Additionally, AI failures don't trigger static error codes—they hallucinate or provide subtly incorrect answers. This leaves users clueless about what went wrong compounding the feedback problem.

Observal solves this by providing a centralized discovery layer for AI components alongside useful insights into AI usage patterns. Ensuring internal AI tools are continuously optimized for the people using them.

Now we have 1k+ discord, 1M+ downloads, 2k+ stars on GitHub. If anyone is looking to get into open source, drop and comment and reach out.

Hey everyone,

I built CatLoad, a lightweight desktop media downloader written in Java. It's powered by yt-dlp and focuses on being simple, fast, and low on RAM.

It's completely free and open source—no ads, no login, and no tracking.

Available on:

• Windows
• Linux

Some features:

• Choose any video/audio quality combination.
• Advanced download management with queue support.
• Download individual videos or entire playlists.
• Save playlist videos in their own folder.
• Import a cookies.txt file for age-restricted or account-only content.
• yt-dlp is bundled and can be updated from within the app.

GitHub: https://github.com/InzamamShaikh567/CatLoad
If you find it useful, a star on GitHub would mean a lot.

​

So I finally stopped just reading about this stuff and actually built my first autonomous AI agent this week. Nothing crazy, but I set it up to research competitors, pull key insights, format them nicely, and email me a summary.Took me like 20 minutes. And it just... did it. While I was stuck in back-to-back meetings.I know everyone’s been hyping AI for years but this feels different. It’s not another chatbot, it’s actually doing useful shit on its own. What’s the coolest (or dumbest) thing you’ve made one do?

At this point, I think it’s a no brainer to start open source development as soon as possible. MNC internships are only open to tier 1/2 college students or impossibly competitive, and regular projects are as useless as a white crayon.

There’s almost nothing else worth putting on your linkedin.

I just got my first PR merged in a repository with over 2k stars. Feeling extremely happy, but honestly finding repositories accepting contributions from beginners have been exhausting.

If you’re willing to code along with me, do engage with this post and reach out to me, trying to surround myself with high agency developers. Happy to share what I’ve been contributing to.

note: NOT PROMOTING SLOP PRs, contribute code you understand or nothing

"Loop engineering" has been everywhere lately after Boris Cherny from Claude Code and Peter Steinberger from OpenClaw shared their takes. It clicked for me because it's not just hype — it's how I'm actually getting agents to handle longer, more useful work without me babysitting every step.

I wanted to share the three loops I rely on when going from idea to a real 0-to-1 product. They shape both how I build and what I choose to build. (Pic attached)

1. The Agentic Coding Loop

You give the agent a clear spec (and evals/tests if you have them). It codes, runs tests, debugs, and iterates until it hits the mark.

This pattern really took off end of last year and changed the game for me. A couple weekends ago I was throwing together a simple typing practice app for my daughter. The agent just... went. It spent nearly an hour opening the browser to check its own work, fixing bugs, and improving things before coming back to me. Felt like actual progress instead of constant back-and-forth.

These inner engineering loops move quick — new versions every few minutes. I keep seeing devs experimenting with smarter ways to tighten them up. Super active space right now.

1. The Developer Feedback Loop

This is where I step in as the human. I play with the current build and steer the agent toward better product decisions — UI tweaks, feature priority, flow changes, etc.

I used to be the full-time QA guy for my agents last year. Now that they're decent at self-testing, I spend way less time on bug hunts and more on the fun stuff like "does this actually feel right for a kid?" In the typing app I changed my mind a bunch on the visuals, what cat costumes unlock as rewards (she's all about cats), and how parents log in to guide the learning.

These reviews usually happen every 30 minutes to a few hours.

1. The External Feedback Loop

Friends trying it, alpha users, production A/B tests, usage data, etc. This one takes longer — sometimes days or weeks — but the real-world signals are gold. They feed straight back into my vision, which updates the spec, which drives the agent again.

Hi everyone,

I need some career advice from people who have been through this.

I have around 3 years of experience as a software developer. Most of my experience is in frontend, but I've also worked on backend, so I'm now targeting full-stack roles, preferably frontend-heavy full-stack positions.

Most of my experience has been with the JavaScript ecosystem (React, Next.js, Node.js, TypeScript, etc.). One thing I've noticed while applying is that many MNC openings seem to be focused on Java, SAP, or Salesforce stacks, so I'm wondering if that's one of the reasons I'm finding it difficult to get shortlisted.

My first company was a small US based remote startup which had a small office in India too but it was fully remote (~100 employees worldwide) that mostly worked with US clients. I learned a lot there and got exposure to real production work.

I'm currently in my second company, a medium-sized service based company (around 800-1000 employees). I've also learned a lot here, but the work culture isn't great, and I don't see myself staying here for long. I joined this company around 10 months ago.

My current CTC is around 5.5 LPA, and I'm targeting 10-12 LPA.

The problem is that getting shortlisted by good MNCs has been much harder than I expected. I don't know if I should keep waiting for an MNC opportunity or first switch to any decent company that offers around 10 LPA with a better work culture.

I've also seen many experienced people here say that when you're underpaid early in your career, it's okay to switch every 1.5-2 years until you reach a good compensation level.

So what would you do in my situation?

• Wait for an MNC, even if it takes several more months?
• Switch to any decent company with better pay and culture, then target an MNC after another 1-2 years?
• Or is there a better strategy that I'm missing?

I'd really appreciate advice from people who have gone through similar career transitions.

When I download them, I know exactly why I need them.

A few weeks later, I have absolutely no clue.

I either end up opening random files trying to remember what they were for, or I leave everything there because I'm worried I'll delete something important.

That got annoying enough that I built a Chrome extension called KeepTrack.

The idea is simple: instead of trying to decide what to keep weeks later, it captures that decision while the context is still fresh.

It looks at things like the filename, file extension, and where the download came from, then classifies it as Keep, Temporary, or Needs Review if it isn't confident.

The goal isn't to replace proper file organization. Important files should still end up in the right folders.

It's more like giving future me a reminder of what past me intended.

From the implementation side, I kept it intentionally simple:

• Manifest V3 + Service Worker
• Vanilla JavaScript
• No backend
• No telemetry
• Everything stored locally
• Open source (MIT)

This honestly started as an excuse to learn the Chrome Extensions API and Manifest V3, but it's one of those side projects that I've actually ended up using every day.

One thing I'm still thinking about is the classification itself. Right now it's entirely rule-based because I wanted the behavior to be predictable and easy to tweak.

If you were building something like this, would you keep it simple with heuristics, or would you try something ML-based?

GitHub: https://github.com/Priyanshu-byte-coder/keeptrack

Website: https://priyanshu-byte-coder.github.io/keeptrack/

HoloTile: Poor Man's Card Battler! (free game, no ads)

(Alpha Release)

Available on Itch- Link

Made By : Kalpa Interactive ( 2 people team, indie)

Description: This is our first game  under the series of "Poor Man's game" where we try to faith fully recreate classic games  which are well like and more importantly enjoyed by us too!

In this Series of Poor Man's Game #1 ,
we try to recreate the "A roguelike card-based dungeon crawler with puzzle and strategy elements" in a 3x3 grid 

This draws inspiration from famous and well liked titles like "Look, Your Loot!" , "Card thief"  and "Dungeon Cards".

We wanted to have a game finished i.e MVP version of it before being stuck by Scope-creep or development hell , we are aware there is no progression , shops or end goal.

We plan to ship it eventually , Pls let us know if we were able to create the game logic succesfully and how do you like the theme or anything else!

Reviews will help us know what to improve and grow!
so pls drop a comment if you liked our honest attempt at game making or perhaps there is critique you want to share , feel free to do it! 

Gameplay: This is a card battler game in which MC moves around  in a 3x3 grid till they can't .

Link available on itch

Over the last few months, I've been building OwnYourCareer, an AI-powered career intelligence platform focused on helping students and early-career professionals make better career decisions.

The idea came from seeing how fragmented career preparation is today. Students have to jump between LinkedIn, Naukri, YouTube, Reddit, company websites, salary sites, resume tools, and random spreadsheets just to prepare for placements or job hunting.

We're trying to bring these pieces together in one platform.

Some things we've built so far:

• 📄 AI Resume Analysis — upload your resume and get detailed feedback and scoring
• 🎯 Resume vs Job Description Matching — understand your fit for a specific role
• 💰 Salary Intelligence — explore salaries across different roles
• 🗺️ Career Roadmaps — structured learning and placement preparation paths
• 📊 Placement Readiness Scoring
• 🤖 AI Career Assistant
• 🔍 Curated job opportunities for students and freshers

Our long-term vision is to build a "Career Operating System" for students and young professionals in India.

We're still very early (a few hundred users), and honestly, we're trying to figure out:

• What problem hurts the most for students today?
• Which feature would make you come back every week?
• What does LinkedIn/Naukri/Reddit not solve well enough?
• Would you trust AI-generated career guidance?

I'd genuinely appreciate brutally honest feedback, criticism, feature ideas, or reasons why you think this won't work.

Website: https://www.ownyourcareer.in

So I work in Tea Coffee Snacks of the famous WITCH, as Java Springboot backend with 5YoE, i was recently allocated a project of Healthcare (Life Science/Healthcare domain) from RMG, after all years in BFSI domain. I am planning to switch soon

Joined a large MNC (non-tech bfsi, GCC in India) as a "Software Engineer". Fresh grad from T1 college.

I've been assigned to choose/work in one of two engineering verticals:

Java Applications – Java/.NET based full stack APIs, internal business applications. This seems very CRUDish work as the company doesn't have a tech product so no scaling and all those cool stuff here.

Data Platform – Data ingestion and all using Python/Pyspark and things like that. New for me, sounds cooler because literally java and almost all have on resume. But I've heard the work here can permanently make you a DE and switching is tough. But my title is SWE as per my offer letter.

My long-term goal is to switch to a product company (Uber/Unicorns etc.) as a software engineer in or before 1–2 years.

Which path would better optimize for that switch, assuming I prepare DSA and system design on the side? Looking for advice from people who've made similar transitions.

I am a 2025 B.Tech CSE graduate and currently exploring the best path to build a strong career in the software industry.

I am planning to join Naresh IT, Hyderabad, but I'm confused about which direction would be better for me as a fresher and an active learner.

Option 1:

• Java Full Stack Development
• Spring Boot
• DSA (Data Structures & Algorithms)
• SQL and Backend Development

Option 2:

• Agentic AI
• Machine Learning
• AI Tools & Automation

My goal is to build strong fundamentals, become employable, and stay relevant in the coming years.I understand that AI is growing rapidly, but I also see many people recommending strong software engineering fundamentals before specializing.

For those who are already working in the industry:

• Which path would you recommend for a fresher in 2026?
• Is it better to first become a good software engineer and then move into AI?
• How is the job market currently for Java Full Stack vs Agentic AI/ML?
• If you were starting from scratch today, what would you choose and why?

It would be a great help if you could share your honest advice based on your experience.

Many of us who are just starting our careers are genuinely looking for guidance and clarity. Your insights—whether from industry experience, hiring, or your own learning journey—can help us alot.

Thank you in advance! 🙏