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Hi everyone! 👋
I’m Emil, a self-taught solo game developer from Sweden building indie games, frameworks, and developer tools under Kadmium.
I’ve spent 20+ years behind the keyboard working across low-level C++, C#, and Unreal Engine. Coming from a background without a formal CS degree (mostly hands-on trial, error, and endless curiosity), game dev has always been my main driver. Along the way, I ended up building my own dev tools and frameworks out of sheer necessity, giving me a deep appreciation for clean architecture, zero bloat, and raw performance.
What I’m currently working on:
You can check out the catalog, dev tools, and experiments over at kadmium.dev.
When I’m not deep in Visual Studio or Unreal Engine, I’m usually playing games, building custom PCs, practicing guitar and violin, or spending quiet time with my wife.
I joined DEV to share some devlogs, technical takeaways from solo development, and connect with other creators who appreciate focused, handcrafted tooling and game engineering.
Feel free to say hi or drop a link to what you’re currently building!
Read the Context Packer post - the username masking on export is the kind of thing you only add after it leaks once.
You list the LLM prompt bundle as a bonus use case and I think it is the main one now. Which makes the three-million-character chunking the interesting number: past that the model reads your pieces separately and loses the relationships the directory tree was there to preserve. Bad architecture used to slow humans down. Now it decides whether the next agent can see the whole thing at all.
Do you pick the chunk boundaries by size, or by something structural?
Thanks! Glad you liked it!
I will post a more in-depth technical soon, and on GitHub but in short the chunk boundaries is set by token/character size for each file set by the user (defaults to 30k) the packer engine collect all files you selected in a async thread and on pack completion sends out a warning list displaying each file breaking the set maximum rule but the .txt output is packed and ready to use to avoid blocking the UI/UX.
Edit : grammar + Also there is a built in file max token size that splits the output into parts, but it was hardcoded into the engine. Before the i upload the technical post I will expose it to user settings.
Both of those checks are per file. A file fits, or it gets flagged. Neither one looks at which files end up in the same part.
Two files under your 30k, split across part 1 and part 2, and the model reads the caller without the function it calls. Nothing warns you there, because neither file broke a rule.
When you expose the max in settings, does anything try to keep a file with its imports?
Hi everyone! I’m Emil. I’m building CARDIAC-PURR, working on AI infrastructure, LLM routing, GPU optimization, and reliable AI systems.
I joined DEV because I’d like to share what I’m building, learn from other developers, and have some real conversations about what actually works in production.
Looking forward to meeting other people working on AI, agents, and infrastructure.
Read your router writeup - the 100 questions were labeled by expected tier before the router ever saw them. So it gets scored on queries whose complexity was knowable up front.
I do not route for coding work, for that reason. You cannot tell from the request which step is the hard one, so the cheap model costs you in the exact place it mattered. A support queue is probably the one workload where the tiering does hold.
How often does the escalation net fire, and does the double call still come out ahead when it does?
Hi Aliaksei
Fair challenge — and one important correction.
The expected-tier labels were evaluation labels, not routing inputs. The router saw only the raw request. I used the labels afterward to see whether the routing decision matched the expected tier. So the complexity wasn’t known to the router in advance.
The more interesting part is what happened when the router wasn’t sure.
In our 100-query paired run, 95 requests triggered a same-tier retry. Eleven retries were good enough to avoid escalation entirely, and those cases averaged 40% lower cost than going straight to LARGE.
The other 84 retries were rejected and escalated to LARGE.
And this is probably the key number: even those 84 “worst-case” cases were still 14.5% cheaper on average than direct LARGE — $0.0427 vs. $0.0500 per request.
Across the full 100-query cohort, the retry-enabled routed arm came in at $3.953 vs. $4.006 for direct LARGE — a 1.34% net saving.
That’s the problem I’m trying to solve with CARDIAC-PURR: not “always use the cheap model,” but use the cheapest model likely to work—and have a controlled escape path when it doesn’t.
And I agree on coding. Difficulty can emerge halfway through a task, which makes request-level routing much harder. I’m not claiming this works universally. Support and technical Q&A are where the complexity signal is proving most useful right now.
That’s where I think AI routing gets really interesting.
Hey Emil, welcome! LLM routing is directly relevant to what I'm building an AI pipeline for producing digital products on a tight budget (under $50/mo). Curious how you handle the cost/reliability tradeoff: do you route by task complexity, or is it more about redundancy/failover between providers? Would love to read more about CARDIAC-PURR.
Thanks! That’s actually one of the use cases we’re building CARDIAC-PURR around.
It’s both — but in the right order.
In our 100-query benchmark, auto-routing reduced cost by 1.34% versus sending everything directly to the large model tier.
But the bigger effect comes from intelligent cascading:
⚡ ~40% average savings per query when a same-tier retry avoided unnecessary escalation.
And even when the retry failed and escalation was required, the routed path was still 14.5% cheaper on average than going directly to LARGE — because the cascade can select a lower-cost provider instead of relying on a fixed provider/model combination.
That’s exactly what we’re building with the CARDIAC-PURR AI Control Plane:
Cost-aware AI routing + provider failover + policy enforcement + full auditability — in one control layer.
For teams operating under tight AI infrastructure budgets — especially under $50/month — this is where intelligent routing can make a real difference.
Would be very interesting to compare your pipeline against what we’re seeing with CARDIAC-PURR.
Welcome to DEV, Emil! 👋
CARDIAC-PURR sounds like a fascinating project, especially the focus on LLM routing, GPU optimization, and building reliable AI systems for production. These are areas where practical experience can make a huge difference.
Looking forward to following your work and learning from your insights. Wishing you all the best with CARDIAC-PURR!
Hi all, Adrian from Poland.
I build and self-host n8n automations for clients, mostly small manufacturing companies.
Ended up here because I started parsing public workflow repos to answer a question about reliability, and kept finding things nobody meant to leave in there. Figured this is a decent place to write those up.
Python, Next.js, Postgres, and lately more git archaeology than I planned on.
Read the n8n writeup - counting by name gives you a perfectly normal-looking number that happens to be wrong by 92%.
My version: a daily report I run stopped counting new users. It had been broken eight days before I noticed, and every number in between was wrong. The reports arrived on time the whole while. What caught it in the end was me doubting one of the numbers.
Welcome Adrian. "Things nobody meant to leave in there" is most of what I find too. I crawl a directory of software tools for facts about each site, and the surprises are never the deliberate choices. They are the defaults: a robots.txt rule that came with the hosting plan, an llms.txt that a parked domain serves because the aftermarket page ships one, a pricing page from two versions ago still live on the old path.
Public n8n workflows sound like a richer version of the same thing, since people export them with the credentials names, webhook paths and comments intact. I would read those write-ups.
What did the reliability question turn out to be? Retry and error handling in the workflows themselves, or whether the things they call are still there?
Welcome! Glad to connect with fellow builders here on DEV! 🚀
How is poland doing today ?
Hello from a tiny security tool with a goat mascot 🐐 We're RedCapra — pentest reporting without the spreadsheet misery, built by a solo founder in France (with an AI pair-programmer doing the night shifts, which we write about honestly). First post here was the story of auditing our own AI agent's config — it failed its own audit, which felt too good not to publish. Here to read war stories and share ours. 👋
Saw the config audit post - the blanket shell allow got there because someone clicked allow to make a prompt go away. That is how all of these files get written.
At work I get nervous handing an agent a dev Kubernetes cluster. On my own machine the same tool has full shell, and I have never once opened the settings file it has been appending to for months. Same person, two threat models, and only one of them ever gets audited.
Grepping for
Bash(*)tonight."Clicked allow to make a prompt go away" is exactly the mechanism — nothing in that file arrived as a decision. It accreted, one dismissed prompt at a time, and the audit was the first moment anyone had actually decided anything about it.
"Same person, two threat models, and only one of them ever gets audited" is a sharper one-liner for it than anything in our post. The work cluster gets scrutiny because it has an audience; the laptop config has an audience of one, until an incident gives it a bigger one.
If the Bash(*) grep turns anything up tonight, that's a war story we'd honestly love to read.
Found it, and not where I was grepping. The bare Bash allow is in the repo of the agent that runs unattended all day, committed four months ago in the same commit that first wired the loop up. I have not opened that file since.
The duller one is worse. Another project has 159 allow rules, and two of them are Bash(python3:) and Bash(bash:). Both read like narrow grants and each one runs anything. A grep for Bash(*) never finds those.
Ran this against our own setup after reading it — 21 settings files, user scope plus every repo. Clean on the specific bug, but your grep point is the part that generalises.
The reason Bash(python3:) and Bash(bash:) hide is that they're shaped like every legitimate narrow grant, so no wildcard search finds them. What worked for me was matching on the first token against a list of things that execute arbitrary code — bash, sh, python, node, npx, deno, ruby, perl, env, xargs, find, ssh, docker, make. Any of those in position one and the rest of the rule is decoration.
Our near-miss was a different shape of the same mistake. Sixteen repos carry Bash(powershell*ops\dev.ps1*) — meant as "only our ops script". But the wildcard sits between the interpreter and the script name, so if the matcher treats * as general, powershell -Command ops\dev.ps1 satisfies it. It's either an arbitrary-execution grant or a rule that has matched nothing for months, and I can't tell which without testing the matcher.
Which is the uncomfortable bit: I could enumerate the rules, but I couldn't tell you what they permit without experimentally poking a live gate. Wildcard position is doing load-bearing security work and it isn't legible from reading the file. If anyone has actually characterised the matcher semantics, I'd take that over my guessing.
Hi, I'm Yimmie, a backend developer from Germany. PHP and Symfony/Laravel, and mostly the work nobody volunteers for: old codebases that are still in daily use, moved onto a current framework without taking them offline. Alongside that, a WooCommerce shop I have looked after since 2017, which teaches you things a greenfield project never does.
Lately I have been reading the MCP spec more than is healthy and building a small scanner for remote MCP servers. Almost none of the failures are new. It is OAuth and multi-tenancy again, except the client is now a model that will cheerfully follow instructions someone hid in a tool description.
Here to write some of that down and learn from the community. 👋
Read the confused-deputy post. You already say the failures are not new, so the part worth pushing on is your own exception: the client is now a model that follows instructions someone hid in a tool description.
That breaks the deputy framing rather than extending it. Every fix in the post lives on the server, and a server that validates audience perfectly still cannot tell an injected request from a real one - the model is a legitimately authorized caller asking for something it was allowed to ask for. The deputy you can fix is the server. The one actually being confused is the client, and OAuth has no opinion about that.
Do you scope tokens per tool call, or is that where it stops being tractable?
You are right, and I think I put two different deputies into one sentence.
The one my post fixes is the server: audience validation, per-call authorization, own credentials downstream. My reference server does the last one with a token exchange rather than passthrough, so the downstream audit trail names the right actor. None of that touches the second deputy. An injected call arrives carrying a token that passes every one of those checks, because it is a legitimate caller asking for something it is allowed to ask for. Server-side authorization has nothing to say about it.
On your question: I scope per capability, not per call. A token carries notes:read or notes:write, every tool checks its own scope before it runs, and a read-only token cannot write no matter what the tool description talked the model into. I do not mint a token per invocation with the arguments bound in.
The nearest thing the spec offers is the step-up flow in the 2026-07-28 revision: 403 with error="insufficient_scope" and the scopes the operation needs, so you can hand out a narrow token at login and demand a fresh grant for the expensive call. My server does not do that properly yet. It raises insufficient_scope as a JSON-RPC error instead of the HTTP challenge, which means a client cannot step up, it can only fail. That one is mine to fix.
But even done right I do not think it answers your point. Per-call scoping shrinks the blast radius, it does not restore intent. Authorized for files:write, talked into writing the wrong file, every check still passes. What actually bites there sits outside OAuth: human confirmation on the consequential tools, treating tool metadata as untrusted input rather than configuration, and being careful about which tools an agent can chain in one session.
Where it stops being tractable, for me, is the moment the answer depends on what the model meant. I do not know how to check that from a resource server, and I am wary of anyone who says they do.
Untrusted input is the one of those three I cannot see a mechanism for. Everything reaching the model arrives in the same window: the tool description, the document, and your instruction to distrust the tool description. Marking something untrusted means writing another sentence, and the injection is a sentence too.
The other two are code you can point at. A confirmation either fires or it does not, a tool is in the session or it is not. Where does the untrusted flag actually live?
No, you are right. There is no flag. Once it is in the window it is tokens, and a token has no privilege bit. My third item was not a mechanism. It was advice, and advice is a sentence.
I checked my own scanner before answering, because I was about to lean on it. The tool-poisoning check is eight regular expressions over name, description and input schema: "ignore previous instructions", pseudo-tags like , "system:" role markers, "do not tell the user", "send … to http", secret file paths, invisible Unicode. That is the whole thing. It catches the clumsy case and nothing that merely nudges. And the remediation line it prints ends with "mark untrusted content", which is the same empty advice you just called out. So I owe you one.
If "untrusted" lives anywhere, it lives before the window or beside it.
Before: the client decides what gets injected at all. Tool descriptions come over tools/list, and the spec says the set must not vary per connection, so a client can hash them on first use and refuse a silent change. It can lint them the way my scanner does and drop what fails. That is code, not a sentence. It is also thin, for the reason above.
Beside: the model that reads untrusted content is not the model that holds the tools. One instance reads the document and the descriptions and can call nothing. A second holds the tools and never sees the raw text, only a constrained result. Then the flag is a process boundary. It works, it is expensive, and almost nobody does it because it doubles the plumbing and halves the usefulness.
Which collapses back into your two. If separation is off the table, the only thing left that enforces anything is what the output is allowed to cause. Confirmation and allowlisting are not a fallback next to "treat as untrusted". They are all "treat as untrusted" ever amounted to at runtime.
The spec has the same problem, by the way. It says clients must treat tool annotations as untrusted unless the server is trusted, and stops there. A MUST with no mechanism behind it is a sentence too.
Welcome Yimmie. The tool description point is the one that keeps coming up for me too. I run a directory of MCP servers and scan the listed ones once a week, and the pattern is the same as you describe: the interesting failures are not exotic, they are auth and tenancy mistakes that would have been caught in any normal API review, plus the new twist that instructions in a description get executed by a client that does not know it is being social engineered.
One thing I learned the hard way: a generic static scanner score is close to useless on MCP server repos. It flags the harness and misses the thing that matters, which is what the server can reach and what it will do when told to. I ended up reporting reach instead of a grade.
Curious what your scanner treats as a finding. Do you check descriptions for injected instructions, or the transport and auth side first? Would read that write-up.
Hi. I’m Sreeragh, a product engineer in Kochi. I’m building Zilobase.
I turn rough ideas into working software. The job usually includes product decisions, interface work, code, and removing whatever turned out not to matter.
Most projects start with a small annoyance or a question I can’t leave alone. A sketch becomes a prototype; the prototype either becomes useful or explains why the idea was bad. Both results count.
Current interests include AI agents, local-first tools, knowledge systems, and open source. This list changes whenever a new rabbit hole wins.
Agreed on the mythology. I would draw the line differently though: not everything deserves understanding.
I run one agent loop whose code I have never read, built and maintained by another agent, and that is fine because a bad result there costs me nothing. On anything that matters I write the hard parts myself. Keeping responsibility is what forces me to actually read it.
So the question is less what to understand and more what to own.
I’ve actually started leaning more into the “agent loop” norm recently. Once you cross a certain scale of code, I’m not sure it’s even humanly possible to retain meaningful context over everything. I’m at around 750k+ lines across some of my work now, and at that point I genuinely start losing track of shit 😅.
So I think the question becomes less “do I understand every line?” and more “do I understand and own the parts that actually matter?” That distinction has been becoming much more important to me lately.
I would draw it somewhere other than scale. At work the codebase is way past what anyone holds in their head, and the parts I own I still read, because I am the one answering when they break.
750k tells you what you cannot keep track of. It does not tell you which parts matter, and that list is usually short and unrelated to the line count.
The current interest never stays the same, the moment a new obsession knocks you find yourself diving deep into it
Hey all,
I'm Dan. Software engineer by day, and the rest of the time I turn my hobbies into apps: an ancient-coin museum, a stamp-centering grader, and a traveler.
I build the whole thing with heavy AI collaboration and own the result.
Fun fact: I have over 100,000 stamps, which is less a hobby and more a cataloguing problem I'm slowly solving with code. Here to write some of it down and see what everyone else is shipping. 👋
Read the coin-museum post - returning source keys and dropping the ones that do not resolve is the cleanest version of this I have seen. Same instinct as validating a step output against the allowed values before anything downstream reads it.
The part it does not reach: a resolved key proves the citation exists, not that the sentence attached to it says what the source says. The model can hang a real URL off an invented claim and the pipeline passes it.
Have you caught one of those yet, or does the one-call-per-world framing keep it honest?
Good question. You went straight to the part I don’t have solved.
Exactly right, and that’s the seam I’d flag too. The pipeline guarantees a structural property, not a semantic one.
What it does hold: the model never writes a URL or a catalogue number. It can only pick a key from a fixed catalogue the code owns, and unknown keys get dropped. The facts themselves are my own imported data, not model output, so it isn’t inventing the underlying fact either. It writes the story around a set of facts and citation targets it didn’t choose.
What it does not hold: that the sentence next to a resolved key is actually entailed by what that source says. A real key hung off a subtly wrong claim sails straight through. That’s the exact failure the structural check can’t see.
The one-call-per-world framing helps a little, because the model can’t wander to a coin or a source that isn’t in that world’s set, so it can’t cite something unrelated. But it’s containment, not verification. It keeps it honest about which sources exist, not about whether the claim matches them.
So, honestly: no, I don’t have an automated catch for that class yet. It’s why every deep-dive page is still marked review-pending rather than trusted. The next real step is a verify pass, re-read the source behind each key and grade whether the claim is supported, adversarially, before it can publish. Right now that grader is me, not code.
Watch what you let the verify pass return. Supported or not supported hides two different failures: the source contradicts the sentence, or the source simply does not mention it. The second one is where your subtly-wrong claims sit, and a grader asked "is this supported" will pass anything plausible that the source is quiet about.
Does it get a third answer for "the source does not say"?
Hi all 👋
I'm Siddharth, from Delhi-NCR. Telecom guy — currently spending my days on Voice AI and contact center stuff at pretty large scale.
Curious question for the room: for anyone running LLMs in production, what surprised you most between the demo working and real users hitting it?
Glad to be here.
The thing I did not see coming: a model stops following rules that are still sitting right there in the system prompt. Demo conversations are short so it never comes up. Real ones run long, the context fills with history, and it drifts off instructions it read at the start.
I run a game where models play a long social-deduction round against people, and one hallucinated rule ruins it for everyone at the table. What fixed it was giving up on the system prompt as the place rules live. Each step I compute the exact slice of rules that state needs and inject it as the last message, so it never has to go looking through the whole context to find the thing it should be following.
An LLM deciding the user is using the wrong model of an application and decided to guide based on that model, even though the user told the model the version they were using, the model kept defaulting back to the older one without any warning
Hi DEV 👋
I'm Bob, a solo founder building out of mainland US.
Two things eat my days: bavior.com — it tracks whether a product actually gets mentioned when people ask ChatGPT or Perplexity for recommendations, then works the Reddit threads those answers keep citing — and livegen.ai, real-time AI video generation, running on Next.js + OpenNext on Cloudflare Workers.
The part I didn't expect to spend most of my time on: making generated text stop sounding generated. Reddit readers and mods spot AI writing in about one sentence, so a big chunk of Bavior ended up being a humanizer pass and ten tone profiles built from real corpora. The model was never the hard problem. The voice was.
Here to write up the unglamorous parts — multi-agent orchestration that survives production, fingerprint/proxy infra, and what quietly breaks when you ship alone.
What's everyone else building right now?
I would guess a lot of your win came from a dumber layer than tone profiles. I take every em-dash out of anything I publish now, by hand. One dash is all it takes for someone to shout AI, and that is the whole read most people are doing.
Does a tone profile built from real corpora actually beat a find-and-replace list on the ten obvious tells, or do both just clear the same reflex?
Hey everyone, Liam here 👋 Happy to join the DEV community.
I spend my days building web apps and trying to automate the boring parts of my job. I'm usually hacking on some random weekend project or trying to figure out why my code suddenly stopped working.
Honestly, I'm just here to hang out, read and write some good articles, and chat with folks building cool stuff.
What's everyone working on this week?
Hi there! Happy to meet you in the community!
Hi DEV 👋
Found this community while looking for places where engineers actually talk about the craft not just tutorials and hot takes.
I'm Aditya. Based in Ahmedabad, India. Spent the last 10+ years building ML and data systems healthcare, finance, procurement the unglamorous but genuinely hard problems where the data is messy, the stakes are real, and "move fast and break things"
I’m especially interested in AI engineering, software architecture, developer tooling, and the evolving relationship between humans and AI while building software.
I’ll be sharing some of the things I’m learning, building, and occasionally getting wrong along the way.
Hope to learn and contribute to the community.
Welcome to DEV, Aditya! 👋 Great to have experienced ML engineers here. I'm also based in India and focusing on Full-Stack Python and AI engineering. Looking forward to reading your posts and learning from your 10+ years of building real-world systems!
Thank you very much for the welcome. Looking forward to connect and collaborate.
Hi! I'm a beginner and genuinely interested in this. Would love some guidance if you're open to it!
Sure let's connect
Hello Dev.to community!
My name is amir Bassir, and I'm a PHP developer. I've built a fully custom, intelligent PHP framework from scratch, along with a dedicated template engine that doesn't rely on any external libraries.
One Power Framework
A
modular,container-basedPHP framework with built-in AI capabilities.Key features:
Nova Template EngineA fully custom template engine that works seamlessly with HTML, JavaScript, and Alpine.js. No Twig, Blade, or Smarty dependencies.
I'm excited to share more and learn from this amazing community.
PHP #Framework #TemplateEngine #OpenSource #Developer #Nova #OnePowerFramework
Hi all 👋 I'm Jean, joining from the building-in-public side of things.
I'm working on Klatos, a habit tracker I'm building to make slow progress visible. The part I'll probably end up writing about here is the infra: I'm self-hosting the whole stack on Kubernetes.
Here to learn from people further down that road, and to share what I break along the way. Glad to be here.
Hey 👋
Hey Ihar 👋 thanks for the welcome. You building something too, or mostly here to read?
Hi from CodeAnt AI 👋 We build security tools, break software, and occasionally discover that the most interesting bug is hiding somewhere nobody thought to look.
Our security team spends a lot of time poking at APIs, AI agents, developer tools, and the assumptions sitting underneath them.
This is where we’ll share the interesting stuff: real vulnerabilities, exploit paths, technical deep dives, and the occasional “wait, can we actually do that?” moment.
Hi everyone — I realized I've been writing here for a while without properly introducing myself.
I'm a software engineer and consultant based in Tokyo.
In my spare time, I build Legacy Tools, a collection of free, small browser tools designed to help with everyday online mistakes — especially around privacy, suspicious links, and safer decisions for older users and their families.
I've shipped several Chrome extensions so far, and I write here about what I learn from actually building, publishing, and trying to get people to use them.
Lately, I've been thinking a lot about one question:
Building software is getting easier. But how do you earn enough trust for someone to actually use it?
What are you working on right now — and what has been harder than you expected?
Hi I'm Anshu from ZyVOP (zyvop.com) where you can write or import your article, publish it to Dev.to, Hashnode, Medium, and WordPress, promote it on Bluesky and Mastodon, control your preferred source, and see which channels bring readers back. Please let me know in the comments :)
Hi! My name is Pablo. I have worked mainly on start ups for 6 years. I decided to start writing dev blogs as a way to keep learning new skills. I just published my first entry ever, didn't know it could be that fun!
Currently learning more about Rust and Linux.
Hi all, I'm Dave. Mobile AR and on-device ML: face tracking, video editing, Web AR, mostly iOS and Android with some React Native. I mainly test this stuff on old mid-range phones rather than flagships, because that is what the people using it are actually holding. Here to write some of that down and to read what everyone else is shipping.
Welcome to DEV, Dave 🥰
Hey everyone! 👋
I’m Arjun, a developer building OneEnv.
I started working on it after seeing how messy shared configuration can become when a team has many developers and services. A simple environment change can have unexpected effects on other services.
I’m joining DEV to learn, share what I’m building, and get feedback from other developers.
Happy to be here! 🚀
Hello, I'm Valentyn Ivanov, a C++ developer specialising in various gamedev technologies (rendering, networking, ECS, you name it) and in architecting cross platform apps with C++. Here to learn and share knowledge.
Hey Valentyn I am also a C++ enthusiast I mainly used it for basic software and some CLI tools but game dev is an entirely new field for me
hope to see what cool stuff you create!
Hi. My name is Lukas. I come from a traditional sysadmin background with lots of experience in Linux administration. I love tweaking homelab server setups in my free time. Lately, I've been challenging myself to bridge my Linux skills with Azure cloud architecture and Kubernetes, so I'm here to push my boundaries, build practical tools, and learn from everyone.😀
Hi everyone! 👋
I’m part of Invendo AI Academy and interested in AI, Machine Learning, Python, and Generative AI. I’m here to learn from the DEV community, share what I learn, and connect with other developers. Looking forward to being part of the community!
This is a great way introducing yourself on the platform - setting up a checklist for signup lol. I just got started with this platform.. Hopefully will build a great community and will post about my researches.. tools I am making and so much more <3
Hi there. I'm a full-stack engineer, new here. I've been vibe coding new browser extensions and dashboard apps with AIs. Please check out the articles on my blog and try out the products. It's baffling how good the AI Agents are at building end to end software. You can hire me too for your projects and if want to build anything!
Hello, my name is Vika, I knew about this website, but never made an account for it. I chose this one because I came across a lot of high-quality articles about programming, all from here. I needed a place where I can showcase my technical expertise and help other specialists avoid wasting endless time searching for the technical information they need.
👋 Hey everyone!
I’m Arjun, a developer and founder working on OneEnv.
I started building it after dealing with a problem that became painful as our team and number of repositories grew: shared environment configuration across multiple services.
A small configuration change can sometimes raise a lot of questions:
OneEnv is my attempt to make these changes more visible and controlled.
I’m here to learn from other developers, share what I’m building, and hopefully contribute to the community along the way.
Looking forward to connecting with everyone! 🚀
Hey! 👋 I'm a DevOps & Cloud learner documenting my journey through hands-on projects, experiments, and real-world troubleshooting.
I'm currently exploring Linux, AWS, Docker, Git, Bash, CI/CD, Terraform, and Kubernetes. Here, I share what I learn, the problems I face, and the solutions I discover along the way.
If you're also learning DevOps, building something interesting, or simply want to exchange ideas, feel free to say hi! 🚀
Hi everyone!
I’m a test development / mobile engineer. I joined DEV to share engineering insights and learn from this awesome global community!
Currently, I’m deep-diving into modern browser capabilities like the WebUSB API and Chrome DevTools Protocol (CDP). I’ve recently been building an open-source project called TabQA, aiming to make Android testing and bug evidence capture directly accessible inside browser side panels without local ADB setup.
Super excited to connect with other QA engineers, frontend devs, and open-source contributors here. Happy coding! ! !
Hi everyone! I'm a Senior Frontend / UI Developer with 9+ years of experience working with Angular, React, JavaScript, TypeScript, HTML, CSS, and Bootstrap. I'm here to connect with other developers, share projects, learn new things, and contribute to the community. Currently working on SaaS and frontend projects. Looking forward to meeting everyone! 👋
Olá, sou Marcus Vinícius, Analista de Sistemas de Informação em um Hospital Regional na minha cidade natal. Formado em Análise e Desenvolvimento de Sistemas em 2019. Desenvolvendo uma aplicação web para gerenciamento de treinamentos institucionais com métricas e acompanhamento do colaborador, e também app web para laudos de ECG para ser usado aqui no meu local de trabalho, claro, seguindo todas diretrizes LGPD e padrões FHIR.
Hey everyone! 👋
I'm Anushka, an MSCS student at San José State University, an ex-Security Engineer, and an aspiring SWE/SDE.
I enjoy building things from scratch and figuring out how they work under the hood. I've worked on everything from security tools and backend services to a SQL query engine, a neural network compiler, and an AI-powered query observability tool.
I build with heavy AI collaboration, but I care about understanding the code, making the technical decisions, and owning the result.
I'm here to write about what I'm building, what I'm learning, and the things that don't work the first time. Hopefully, some of it helps someone else too.
Looking forward to learning from everyone here and seeing what you're all shipping. 🚀
Hi everyone, I'm Mattia. I recently graduated in computer engineering from the
University of Perugia, in Italy, and I mostly work in Python.
At the moment I'm spending my time on quantum computing — less on the
algorithms, more on everything around them: how you actually get a circuit
onto a real machine, how long you end up waiting, what happens when a backend
isn't available. It started with my thesis and I've kept going since, building
a small open-source tool and trying to measure things properly rather than
guessing.
I'm still learning most of this, so I'm mainly here to read and to pick things
up from people who know more. Nice to meet you all. 👋
ONE DAY
Honestly I'm here because you all are my inspiration I'm not a software engineer of any comparison to the levels that you all are im here to surround myself with the people that i inspire to be a part of
Hey, I'm Noe
I'm a lost guy who can code to a degree but not too well.
More precisely finished an IT school and did projects in C, java, python, C# even in asm some. Then went down the Cyber Sec route and now I just wanna get back to coding because I love to do it.
Right now I'm learning C++ and lets say its new confusing, first time I'm trying to learn actual best practices and any help or advice is welcomed. (currently i started to do crafting interpreters jlox implementation in c++ because i know java well enough and it already has c++ implementations against which i can check if I'm done with my.)
I'm here for advice, discussions or potential co-work because I have been isolating most my life and it's not working.
Hi dev.to community! I'm Daniel, an Electrical Engineer and Educator from Santa Fe, Argentina. I'm currently finishing a Python diploma and building a remote IoT + AI lab (ESP32 -> MQTT -> PostgreSQL, with Python ML/DL on a desktop GPU via Tailscale + SSH). Excited to learn and share with you all! 🚀
Hi there!I’m a design agency owner based in South Korea. Being born in '89, I’ve lately been thinking whether it’s too late to learn something new. But my recent interest in AI got me studying it anyway! I happened to come across this place by chance, and I’m excited to share and learn useful information here. Thanks!
Hey everyone! I’m a software engineer and independent architecture advisor. I’m here to connect with other builders, learn from how people are designing and scaling their systems, and share practical thoughts on software architecture, tradeoffs, and keeping systems maintainable.
Hi everyone,
My name is David and I'm a full-stack developer turned AI researcher. I've been part of Localazy, a translation management software company for five years, started on core product engineering, and now focus entirely on translation quality (through our agentic QA capabilities) and AI research.
I'm building Localazy's QA system. It detects glossary term omissions, HTML tag corruption, unnatural phrasing, semantic errors, register mismatch, and over 20 other failure types, then layers AI evaluation on top for the cases where static rule checks aren't enough.
Looking forward to chatting with devs in the community and sharing a bit about my work.
Hi, I'm Oscar, a full-stack developer from Taiwan.
Most of my JSON work is editing rather than reading — a config comes in and I
have to change fifteen values scattered through it. What kept slowing me down
was that after twenty minutes I could no longer remember which lines I had
already dealt with, and I could never find a formatter that let me just flag a
line and jump between the flags.
So I built one. It ended up with line flags that follow the content when you
edit above them, search in both panes with the matching line numbers lit up in
the gutter, and four views of the same document — text, tree, table and a mind
map. I also spent an embarrassing amount of time on the colours, because I look
at it all afternoon.
I've been reading DEV for a while without an account. Made one to write that up.
Happy to be told where I'm wrong.
Hello! I’m John Francis, a Website Designer, Social Media Manager, CRM Expert, and AI Enthusiast. I’m passionate about creating effective digital experiences, helping businesses improve their online presence, and exploring how AI and automation can make everyday business processes smarter and more efficient.
My name is Joshua
Thanks for welcoming me, my main Goal is to build a Portfolio and improve my skill, i recently just posted how i made my First Saas tool, a tool that check Website for basic security information.
You can whatsapp me@+2348144514422
Thank you
Hi everyone! 👋
I'm Aman, a developer and I'm building ASForge — an AI-focused technology brand. I'm exploring AI, React, JavaScript, Three.js and building innovative web experiences.
Excited to learn, build and connect with everyone here! 🚀
Hi everyone! I'm Sunny — I've been building and running production systems for 18+ years, mostly Laravel, e-commerce, and the DevOps around keeping it all alive. Co-founder at Two Techies.
What brought me here: I just finished a project I'm genuinely proud of — benchmarking Dragonfly vs Redis vs Valkey on a 48-core bare-metal box - and I wanted a place to share the write-up with people who'd actually challenge the methodology. Just posted Part 1.
Currently learning eBPF, because I want to see what my benchmarks look like from the kernel's side.
Fun fact: my first cluster benchmark was off by ~9× — not because of the database, but because my load generator gave up first 😀 That mistake taught me more than the correct numbers did.
Hello, my name is Lean Flower, and you can call me Lean. I like small scripts that can solve problems with manual workflows. Hm, so um, I built a product that can help people avoid wasting time on manual workflows. Yeah, I built it with Python, and I look forward to receiving your guidance!
Hey everyone! 👋
I'm an independent web developer building SaaS products, mostly with Next.js, Vercel, and Google Cloud Run.
Currently exploring AI-powered web apps and trying to ship more useful products faster.
Always happy to connect with other indie hackers, developers, and SaaS builders 🚀
Henrik here, from Sweden. I build small software products on my own and have done for a few years. The one taking most of my time right now is directree, a directory of software and AI tools where every listing gets crawled and the facts come from the site itself rather than from the founder's pitch.
That crawl leaves me sitting on a lot of data, and I have started writing up what it shows. First piece went out this week: of 9,037 live AI tools, 10.5% block GPTBot in robots.txt, but almost 9 in 10 of those still allow OpenAI's search crawler. Sites behind Cloudflare block at 22.4%, sites on Vercel at 5.2%, so the hosting default matters more than the founder's opinion.
I plan to post one of these a week here, with the sample size and method each time so you can argue with the numbers. Outside of that I am mostly in Next.js, Postgres and a growing pile of crawler code.
Hi everyone! 👋
I’m Michael from China, a software engineer with more than 20 years of experience in software development, with a focus on Linux, networking, cloud computing, and virtualization.
I discovered DEV Community many years ago, and it has been a valuable source of knowledge and inspiration throughout my career. I’ve learned a lot from the community and hope I can now give something back by sharing what I’ve learned along the way.
After being laid off last year, I decided to take a new direction and become an independent developer. I’m currently building macOS and iOS applications, exploring Apple’s technologies and virtualization frameworks, and writing technical articles about the things I learn.
My goal is to keep learning, build useful products, and share practical knowledge with the developer community.
Looking forward to connecting with you all! 🚀
Hi everyone! I’m Awais. I recently built screenblack.site, a free web tool for screen testing—helping people easily check for dead pixels, backlight bleed, and display consistency.
I joined DEV to connect with other developers, share the practical side of building straightforward, single-purpose web tools, and learn from everyone’s experiences in front-end development, performance optimization, and SEO.
Looking forward to meeting other builders, web developers, and anyone interested in web tools!
Hi everyone! 👋 I'm Cuong, a programmer from Vietnam with 10+ years in software. What brought me here: I'm building an AI-driven pipeline that researches, creates, and packages digital products (prompt packs, agent QA/eval tooling, SaaS starter kits) with AI doing most of the legwork. Fun fact: I just shipped my first product on Lemon Squeezy this week. Looking forward to learning from this community!
Hello everyone. I'm a solo dev looking to promote my open source project. Hopefully soon I can write and share with all of you what it's about. In the meantime I look forward to check other articles and read up on what other people are working on
Hey everyone! 👋 I'm Nicolas — I do web dev and split my time between a couple of projects: textConvert, a small open-source TypeScript library for text case conversion, validation, and PII redaction, and ToolFurnace, an AI tools aggregator site. Just started posting here to share what I'm building. Looking forward to seeing what everyone else is working on!
HI, everyone, i am just on this place as a hobby, more then work!
My name is Evan, i am from seattle, I am a nerdy gamer,
i like sims, fornite, minecraft, my most played game is either cod (Call of duty ®)
or GTAV (Grant teft auto5 ®)
Hi Everyone,
Building privacy-first web tools at NoFileUpload. I create browser-based tools for image, PDF, video, and metadata processing that work locally without uploading files. Passionate about JavaScript, web development, performance, and online privacy.
I'm here to share writeups, guides, and resources with you as we build this out — CTF challenges, techniques, tools, whatever helps you level up in offensive security.
Early days, so say hi and tell us what you're into 🚩
Drop a hello, tell us what you're into (web, pwn, crypto, forensics...), and feel free to suggest what you'd want to see here. 🚩
$ whoami — go ahead, introduce yourself below 👇
Hi everyone,
I’m Srikanth. I’m working on Supero and spend a lot of time thinking about what happens after AI generates the code, things like multi-tenancy, authorization, APIs, data, security, and deployment.
Excited to connect with other builders here and learn how you’re taking AI-generated apps from prototype to production.
Hey everyone! 👋
I'm Valerii, a Java/Spring Boot engineer interested in distributed systems, system design, and building open-source tools.
Lately I've been spending a lot of time turning architecture ideas into working projects — Kafka, PostgreSQL, transactional outbox, idempotency, state machines, and related backend stuff.
I'm also experimenting with building small developer-focused SaaS products and growing open-source projects in public.
Planning to share practical write-ups about what I build, what works, what doesn't, and some of the engineering decisions along the way.
Happy to be here — always interested in meeting other backend, Java, and open-source folks! 👋
Hi everyone! I want to introduce my project, Nexus OS.
It started with a simple idea: I wanted to create my own Discord Rich Presence integration.
I’m still in the early stages of development, but right now Nexus OS already has:
The project is still growing, and I have a lot of ideas for the future.
I’m sharing Nexus OS here because I’d like to find people who are interested in the project, get some feedback, and hopefully find the right community around it.
It started as a small Discord project and somehow became much bigger than I expected 😂
I hope you like it and I’d love to hear what you think!
My English isn’t very good, so sorry for any mistakes 😅
¡Hola comunidad! 👋
Soy Santiago, de Paraguay — trabajo en infraestructura TI (SSR Engineer), armando y manteniendo redes y sistemas para más de 25 sedes de una corporación.
Vengo a documentar acá lo que voy armando en la práctica: ciberseguridad, networking, DevOps. Mi primer artículo fue sobre montar un SIEM gratis con Wazuh y Kibana, detectando fuerza bruta en tiempo real.
La idea es compartir configuraciones reales y los bugs que me tocó resolver en el camino — esos que casi nunca aparecen en la documentación oficial. Y de paso, aprender de la comunidad.
¡Un gusto estar acá!
Hey everyone! Building SyncStays — a hotel management PMS handling bookings, channel management (OTA sync), POS, and housekeeping for independent hotels.
I'm here to write about the real architecture decisions behind it — like why we built and then reverted a full Module Federation micro-frontend setup for our dashboard after it started straining under 371 wiring files for just one page load. Turns out the "simple" solution (vendored React + import maps) beat the fancy one.
Excited to share more build-in-public lessons and learn from what others are shipping. Fun fact: the whole backend is one big Go monolith talking to Firestore, and I have zero regrets about that.
Hello! Consult 4 Kids trains staff in expanded learning programs operated through school districts, including those funded by ASES, 21st CCLC and ELO-P. Wherever we work we build to the California Quality Standards for Expanded Learning Programs. Training comes live and on demand, and we push on demand hard, because programs onboard new staff all year rather than once in August.
Hi everyone! I'm Luka, the builder behind Luminar. I work on practical data tools and automations, including a portfolio of Apify Actors covering product monitoring, accommodation and reviews, property listings, ad research and public business data.
I'm especially interested in the step after data collection: turning results into something useful in a spreadsheet or an n8n workflow, keeping repeat runs organised, and making setup easier to understand.
I'm here to share what I learn, exchange ideas and learn from how others build and maintain their tools. You can find my work at Luminar on Apify. Happy to meet other people working with web data and automation!
Hello everyone, Excited to be part of the community, share what I’m working on, and learn from all of you. I’m the builder behind Owlinkx. Super excited to finally share what I’ve been working on with you all.
Hey everyone! Wilmer here 👋
Venezuelan developer living in Mexico. Building AETHERIUS -- an open-source API marketplace where AI agents pay per request in USDC on Base Mainnet.
What brought me here: I wanted to learn how other devs are thinking about AI agents and crypto payments. The x402 protocol fascinates me -- HTTP 402 repurposed for micropayments.
What I'm learning: FastAPI, Base L2, Coinbase CDP, EVM smart contracts, and how to build infrastructure that works without human intervention.
Fun fact: I built 80 live endpoints in 4 days with $5.80 in ETH. No bank account. No VC. Just a crypto wallet and an idea.
Would love to connect with anyone working on agent infrastructure or crypto payments. Happy to help if you're exploring x402!
My article: dev.to/wilnowilx/i-built-an-api-ma...
Hi all. I'm Sandeep, based in the UK. I've spent most of my career running production systems and on-call rotations, and for the last couple of years I've been building AlertKick, a monitoring and on-call tool, mostly on my own.
I joined because a lot of what I write up for myself is the unglamorous side of ops: migrating pagers, what breaks when you switch alerting tools, keeping a rota fair with three people on it. My first post here going to be instructions and checklists for teams leaving Opsgenie before it shuts down in April 2027.
Happy to swap notes with anyone running on-call for a team that doesn't have a dedicated SRE function. What's the alerting setup you inherited and never fixed?
Sup y'all, here to be a serious C larp,
just install fedora bythaway, also workstation doesn't come with the GNU compilers,
like seriously people,
Came to share my projects too,
my first chad C error
Hello there, i'm Jamal Hill, i'm a hardware and software enthusiast with:
2 years of experience of c++ and QT
4 years of c (specifically memory management)
1.5 year of python
4 months of java
half a month of kotlin
I'd like to meet many people in this forum to talk about programming and making software!
Hi DEV 👋
Victor Daniel here. Beginner in AI engineering and ML research, just starting out but genuinely excited about the craft. I care about AI engineering; how to build it, ship it, and make it work in the real world. Expect me to share what I’m learning, building, and occasionally getting wrong along the way.
Glad to be here! looking forward to learning from and contributing to this community!
Hello - I’m a CPA who desperately needs to learn AI for Finance transformation. Automating accounting workflows to scale organizations and simply for greater efficiency. I’ve been dabbling in Claude Cowork, Skills, Canva (for my consulting advisory practice), and Notion. I’ve connected MCPs but I’m probably 10% to my goal. I will have dumb questions — please forgive.
It is also very likely I’ll be looking to subcontract work that is over my head. I hope it’s okay to post that kind of thing, but lmk if not. I’m a single mom to a 3-year old so my windows for learning times are here and there while I grow my advisory practice. 🙏
Hi everyone!
I'm Murat, a backend developer from Ankara, Türkiye. I started with PHP, wandered through C#, Java and Kotlin along the way, and eventually settled in Python land, where FastAPI is my daily driver.
I joined to keep learning new things in my field, and to share what I've picked up along the way.
Looking forward to the #python and #fastapi corners. See you around!
Hey everyone! I’m part of the zltokens team, working on AI API access for developers and small teams. Lately, I’ve been focused on a practical question: which tasks actually need a powerful model, and which can a smaller one handle well? I’m here to compare notes and see what other people are building.
Hi everyone, I’m fthux. I’m a frontend developer with experience in TypeScript, JavaScript, Vue, and Node.js. I also enjoy game development using Unity and Cocos, and I’m currently exploring the possibilities of AI. I’m always curious about new technologies and enjoy learning by building. I’m excited to join the dev community and connect with like-minded developers.
GitHub: github.com/fthux
Hi everyone ☺️, I'm Obasi and am Nigerian.
I'm a 100-level Computer Science student who is passionate about AI. I'm most interested in AI automation engineering.
I’m so excited to be a part of this community.
I hope to learn new stuff in tech and also to connect with like minds.
Let us connect and be friends.
Hey DEV community! 👋
I'm Sébastien, a web developer from France and the developer behind SDX Development.
I'm here mostly to exchange with other developers, share things I learn while working on real-world projects, and discover different approaches to web development, software architecture, tooling, and problem-solving.
Happy to be here — looking forward to learning from the community and joining the discussions! 👋
Hey everyone! 👋 I'm a security engineer and researcher working on automated vulnerability discovery, CPG-driven rule compilation, and static analysis tools. Excited to connect with the community, share technical deep dives, and learn from other developers!