r/developers

Lot of discussion here about prompting strategies, CLAUDE .md setups, MCP configs, all useful, but the conversation about what happens after Claude Code generates something is pretty thin

The agent produces a diff, you review it, maybe run it, but actually verifying the app behaves correctly end-to-end across the real UI with real interactions, that step is still almost entirely manual for most people

Not a dig at Claude Code specifically, just a gap in the agentic dev loop that hasn't been closed yet, the generation side is moving fast, the verification side is roughly where it was two years ago

Anyone actually built codeless test automation into their workflow that handles this? Not linting or unit tests, actual behavioral verification

so i have made a package that solves most people problem and is that most people lost token because they dont know how to use AI properly , so you dont need to know deep complex workflows for cursor or claude or codex , now download package and saves millions of tokens per day. so if you want to contribute you can contribute to this package also . you can check repo from pip and npm.

Hi people, I am testing a 32inch 4k Ips monitor. I took that instead of 2 Fullhd 27inch monitors. I like how it looks but somehow i am afraid that at a moment it will be either not enough space or just want be able to transition.

I thought 1 monitor vs 2 should boost my productivity thats why i did this.

Please tell me your expiriences with this subject. Best regards

I feel a bit stuck figuring out how to position myself in the current tech market and would really appreciate some honest advice.

Here’s my background:

• Built banking backend applications using Spring Boot, JPA, Kafka, and PostgreSQL
• Developed a full-stack AI Therapist Agent (agentic conversational AI) and even wrote a research paper on it
• Completed 1 AI internship + 2 Data Analyst internships
• Won $300 at Stellar Hackathon (Blockchain) and secured 3rd place at Classiq Hackathon (Quantum Computing)

One challenge is that my college didn’t really have strong placement support,not even single company (no Superset, limited exposure). I don’t blame them, but it does mean I’ve had to figure things out on my own.

Now I’m confused about positioning:

• I’m strong in Java and Python
• Some people suggest I should focus purely on being a Java backend developer
• But I also have AI + data + some blockchain exposure

My concern is: am I too “all over the place”? Should I narrow down and brand myself strictly as a backend engineer, or try to position myself as something broader like “AI + backend”?

What would you do if you were in my position in today’s market?

Any advice on positioning, job search strategy, or what recruiters actually value right now would help a lot.

I want something along the line of:

Search for a comment of reddit,

use some kind of llm to challenge the comment in the most stupid way possible,

if user reply then repeat

if there isn;t one would anyone want to make one with me? (dm if collab), just send link in the chat many thanks

Work often happens in short resumptions. What does it feel like for you?

I am a business cofounder handling product design, leadership, go to market, and operations for my startup. We are a social app meant to connect people in a unique way that the market is starving for.

What I’ve already done:

- The product is already fully conceptually designed with clear specs and features (MVP + longterm future features). There has also already been a prototype tested, and a tech stack available, though it’s not locked yet without engineer input.

- An active go to market strategy including a healthy waitlist that is still actively growing (high 10+% conversion rate on cold outreach) and a clearly defined market/avatar. Users are ready as soon as MVP ships.

- Daily content production will begin in April as well. My personal account has ~200,000 views after only ~35 days of posting. I cumulatively have nearly 6000 followers between Tiktok and Instagram

- Leadership ability through over a decade of work directly with people, both client and colleague.

- Developed business skills through previous business successes. All business metrics are tracked and help determine how we execute our work and make adjustments when necessary.

What I’m offering:

- Longterm Cofounder position is available. I’m also open to other dev positions if you prefer (founding engineer, contracting, something else).

- Full ownership over the technical side of the project. You won’t have to handle anything else but the dev side, and you control how it’s done.

- Negotiable terms that I’d be happy to establish before any work starts getting done. Profit share, equity, etc. I want this to be a satisfying win for both of us.

- Full spec sheet and preparedness to communicate clearly. Communicating is extremely important for success to me. You’re the tech expert so I’m open minded.

DM for more information.

Hey everyone,

I’ve been diving into advanced workflow orchestration lately—working with tools like LangChain / LangGraph, AWS Step Functions, and concepts like fuzzy canonicalization.

I’m trying to get a broader, more future-proof understanding of this space. What other tools, patterns, or concepts would you recommend I explore next? Could be anything from orchestration, distributed systems, LLM infra, or production best practices.

Would love to hear what’s been valuable in your experience.

Hey everyone,

I’ve already gone through a few older posts on switching to AI/ML, but most discussions are around freshers or people with formal ML backgrounds, so wanted some advice specific to my situation.

I recently quit my SDE role at a FAANG company (~1 YOE). I’m planning to spend the next 3–4 months focusing on the ML fundamentals and creating projects.

My concern is that I don’t have a formal background in ML, no MTech, no research papers. But since I’ve already left my job, I’m trying to be realistic, are there hard filters for mtech degree/research papers for entering into AI/ML roles?

Good evening everyone,

I study Computer Science in a private college in Greece, and I have about 1.5 years left.

In the meantime, I’ve started building and deploying my own projects, and I’m looking for my first junior developer job. I’ve already secured my first interview, and given that I have good English and soft skills, I believe I can definitely land a junior role within the next few months.

The problem is that starting in September, university begins again with a heavy schedule, and attendance is mandatory. So I won’t be able to work full-time and study at the same time.

So now I’m thinking… If I wait until i finish my studies to get my first job, my parents will spend €15k (for the remaining courses), and for the next 1.5 years I'll be financially dependent on them. And I will also not progress as quickly as I would in a job.

Dropping out, starting work, and learning while I'm getting paid sounds a lot better. Especially since the IT field is more progressive and I’ve heard that even self-taught developers can get hired.

Do you think it’s worth it? What would the disadvantages be?

Hey everyone! I'm not sure if this is a right place to post it, in case it's not, I will delete the post.

I'm a student currently working on a final project involving Credit Risk, and I’ve hit a bit of a wall. I need to build a basic web app/interface using SAS Viya to showcase the models, but I’m struggling with the deployment side of things.

I’m looking for someone with Viya experience who can help me get this over the finish line. Since it's a college project, it doesn't need to be enterprise-grade or super flashy, it just needs to be functional and meet my requirements by the end of May.

I am a student, so I don't have a massive corporate budget, but I value your time and will absolutely pay for the help. If you’re familiar with Viya and interested in helping a student out, I can share more details about the specific calculations and the project scope in DMs.

Thanks in advance!

From the point of view of someone just getting into devops, it's extremely odd to me that the philosophy centered around automation spends so much time manually testing things in the QA process. A quick google search shows that there are some products out there that can, supposedly, automate web app testing right in the browser itself, without the need for containers/VMs. Before I spend too much time looking into this, are these types of products too good to be true? Has anyone had any success with these automated Ul testing tools?

We’re looking for experienced developers who want to focus on creating and shipping real software — not just sitting through endless meetings.

If you enjoy writing clean code, solving practical problems, and delivering features that matter, this role is for you.

What you’ll do:

Develop and maintain software applications

Build new features and improve existing systems

Debug issues and optimize performance

Work with APIs, databases, and third-party integrations

Collaborate on enhancing product functionality and reliability

What we’re looking for:

Strong experience in software development

Proficiency in one or more programming languages (JavaScript, Python, Java, PHP, C#, etc.)

Understanding of APIs, databases, and software architecture

Ability to work independently in a remote setup

What we offer:

Fully remote (Prefer EU/US/CA)

Flexible, part-time friendly schedule

$21–$43/hour based on experience

Work on meaningful, real-world projects

Interested? Send a message with your location 📍

The real reason why 16 gigs of RAM is not sufficient is AI — but not in the way everyone thinks.

My point is: engineers use AI to develop apps that turn out sloppy (bad UI, poor UX). But the fault here is not about using AI — the app can still be optimized, developers just choose not to. The reason is that the big companies they work for give them high-end, high-performance computers for development, so they don’t care about lower-end devices. Of course the app may work on potato PCs, but the thing is it will have way more issues than the developer expected.

Luckily I have a solution — ban AI. lol just kidding.

Give developers low-end machines so they are forced to optimize their apps to the absolute max.

Let me involve an example to support my case — WhatsApp. WhatsApp was good, working, no issues. But now WhatsApp is basically a web wrapper, requiring internet to even open, and it lost lots of other features too like the popout chat where tf is it !?

So the developers are tricked into thinking they are doing a good job, but in reality tech is evolving backwards.

Most of us spend a lot of time making sure code works as expected, but I’ve been thinking more about how often we actively test how it fails.

In one of our recent projects, we tried a slightly different approach — instead of only writing tests and reviewing code, we simulated adversarial scenarios on a forked environment.

We also used something like guardixio to generate potential exploit paths automatically, then verified them manually. A few unexpected issues came up that we hadn’t caught in normal testing.

It made me rethink how much confidence “passing tests” really gives.

Do you actively test failure and exploit scenarios, or mostly focus on expected behavior?

Web development still seems to be booming in 2026, and I keep seeing more opportunities, tools, and demand for developers everywhere. For those already working in the field or learning now, do you feel the growth is still strong? As a beginner, I also keep hearing that data modeling is important for building solid backend skills. Is that something every new developer should start learning early, or is it better to focus on coding first? Curious to hear everyone’s thoughts.

Purely for monetary things. Because i know good bad experience depends very much on each place so money wise which is more valuable in today's world?

We just added OpenCode Go as a provider in Manifest. If you have an OpenCode subscription, you can now route to their full model catalog through your existing setup.

Here's what's available:

• GLM-5
• GLM-5.1
• Kimi K2.5
• MiMo-V2-Omni
• MiMo-V2-Pro
• MiniMax M2.5
• MiniMax M2.7
• Qwen3.5 Plus
• Qwen3.6 Plus

Some of these are genuinely strong! Kimi K2.5 has been getting a lot of attention for reasoning tasks. GLM-5.1 is solid for general use, and Qwen3.5/3.6 Plus gives you access to Alibaba's latest without dealing with their API directly.

The interesting part for routing: these models are included in the OpenCode subscription. That changes the cost math pretty significantly.

It's live now. Just connect your OpenCode credentials in the provider settings and Manifest handles the rest. You can then set manually your routing if needed.

For those who haven't tried Manifest, it's a free and open-source LLM router that sends each request to the cheapest model that can handle it.

Hello! Call me sanya! Me and my Friend (vadimosolo) making a game platform like roblox: Lybrix, but we dont have any money or so much time and we need a help. We need a: hmlt programmer, Modeler or Artist, engineer (help with a game, software: godot). For more info here discord (Owner:vadimosoloisreal) (Co Owner: sanya2278_)

Quick context: last November I burned 2 months and 11 submissions getting HUMAN_AGENT approved for our Meta app. Earlier this month I submitted whatsapp_business_messaging and whatsapp_business_management together and both got approved on the first try.

Sharing the full breakdown because I would have killed for this post 6 months ago.

The two permissions + what each actually unlocks

- whatsapp_business_messaging — send/receive via Cloud API, interactive buttons, template sends, mark-as-read, media download.

- whatsapp_business_management — Embedded Signup completion (webhook subscribe + phone number /register), template CRUD (/{WABA_ID}/message_templates).

You almost certainly need both. Embedded Signup does not actually activate the number without whatsapp_business_management calling /register.

Description structure that worked

Both permission descriptions used the same 6-section skeleton:

1. HOW WE USE THIS PERMISSION - numbered list of specific API endpoints + what each does
2. AUTOMATED WORKFLOW - narrative walkthrough of a real customer conversation, start to finish
3. WHY THIS PERMISSION IS NECESSARY - bullet list of things you literally cannot do without it
4. HOW IT ADDS VALUE - who benefits, what outcome
5. COMPLIANCE - 24h window enforcement, opt-out handling, multi-tenant isolation, data storage
6. TECHNICAL IMPLEMENTATION - file names, actual endpoints, how the flow routes

The TECHNICAL IMPLEMENTATION section is the one most devs skip and I think it carries a lot of weight. Naming real files (WhatsAppAPI.php,  WhatsAppHandler.php), real tables (meta_messages), and saying "the 24h window is calculated from MAX(created_at) of inbound messages" reads like a real engineer wrote it, not a marketing dept.

Screencasts: no captions, no voiceover

Both videos were silent screen recordings. Our portal (ChatGenius) is in English and the UI is self-explanatory, so we let the flow tell the story. Zero narration. Both videos approved without complaint.

Video 1: whatsapp_business_management

1. Start from dashboard (WhatsApp already disconnected beforehand)
2. Connect section → click Connect WhatsApp
3. Full Embedded Signup popup: select WABA, select phone number, grant permissions, finish
4. Show connected status
5. Navigate to WhatsApp Templates
6. New Template → name (order_follow_up), category (UTILITY), language, header, body with {{customer_name}} and {{order_number}}, example values
7. Submit for Review
8. Template appears with PENDING badge

Video 2: whatsapp_business_messaging

1. Start from dashboard
2. Full Embedded Signup flow through to completion (showed the whole thing again, even though it was in video 1)
3. Account connected
4. Navigate to Conversations
5. Open WhatsApp in a new window, ChatGenius inbox showing behind, message the connected business number
6. Message arrives in inbox, AI auto-replies in real time
7. Couple more back-and-forth messages, showing AI handling each and realtime messages coming in
8. Open the conversation thread, full message history with timestamps

 

That's it. No annotations, no pointer highlights, no voiceover. 

Disconnected-before-recording is the #1 thing

I disconnected the WhatsApp account before recording so the reviewer sees the full Embedded Signup from scratch. This was the single biggest unlock for HUMAN_AGENT after 10 rejections - if the reviewer cannot see the complete OAuth/connect flow, they reject. Same principle applies here.

One weird thing I noticed

For IG/FB permissions, Meta lets you write custom reviewer instructions ("steps to reproduce"). For these two WhatsApp permissions, I could not find that field during submission. Either Meta reused prior app review instructions, or they do not collect them for these specific perms. My detailed description + screencast was all I submitted.

If anyone knows definitively, drop a comment.

TL;DR for first-try approval:

1. Submit both perms together with matching descriptions
2. 6-section structure, with real file names/endpoints in Technical Implementation
3. Disconnect everything before recording - show a fresh Embedded Signup
4. Silent screen recording is fine if your portal is in English and the UI is clear
5. Show the full journey: connect → use feature → show result in your platform (actual customer experience)

Happy to share the actual description text I submitted if anyone is mid-review. Good luck out there.