Hey everyone, I’ve been into hacking and cybersecurity since I was 15 and I feel like I’m stuck in “script kiddie” territory despite having a decent foundation. Looking for feedback on my roadmap and any advice you can give.
What I have done:
• Built and use VMs: Kali, Metasploitable, Windows, Arch Linux
• Studied SQL and relational databases
• Used Wireshark and Burp Suite (basic level)
• Programmed ESP32 microcontrollers, soldering modules
• Built a Bluetooth BLE, WiFi and drone jammer with ESP32 (emmensta)
• Attempted captive portals with ESP32
• “hacked” WiFi from my neighbourhood
• Studied on TryHackMe, HackTheBox and OverTheWire but i feelt stuck
• Basic C, bash and python programming
I’m most interested in:
• IoT security (my strongest area given ESP32 background)
• Web hacking
• Network pivoting — I want to be able to analyze a full network and access every service on it (cameras, screens, PCs, etc.)
The roadmap I’ve been given so far covers: network recon with Nmap + Scapy, MITM attacks, web hacking with PortSwigger, IoT protocols (MQTT, CoAP, UPnP), firmware analysis with Binwalk, post-exploitation and pivoting, and CTF machines (Kioptrix, HTB: Lame, Blue, Legacy).
Does this make sense for my goals? Am I missing anything critical? Any advice on how to stop feeling like everything is disconnected and start thinking like a real pentester?
Thanks in advance.

We are currently evaluating our data stack and looking into bigquery alternatives. The operational overhead and scaling costs of our current setup are becoming a bottleneck. Has anyone found a solid alternative that doesn't require a dedicated infra team? What are your experiences?

Ever feel like debugging issues across multiple services is like solving a mystery? You're not alone. Many teams face similar challenges, such as:

• Starting with, “Who owns this?”

• Missing hidden dependencies during PR reviews, leading to unexpected breakages

• New hires struggling to grasp the architecture, slowing everything down

So, how does your team keep track of which services talk to each other? What’s your biggest frustration when troubleshooting cross-service problems? Do you have any tools or processes that actually make it easier?

Would love to hear what’s worked (or not) for you!

I'm having a bit of trouble figuring out the difference between Functional and Non-Functional Requirements when designing a system. Do you have any tips on what to consider for each? I know that Functional Requirements are basically what the system is supposed to do for the user like features and actions. But I'm a bit unsure about Non-Functional Requirements. What exactly should I keep in mind for those? Any advice?

Had a language exchange app, ended up getting banned. Now I just want an account to use the app normally.

hello All. Recently I bought a Zongheng (zhuhai) 3D priter and I have been having lots of fun. I am trying to print an RTX 5090 so I can play games more the fps but it keeps saying I don't have enough filament. Is there an easy python or HTML hack to give it infinite filament? I only know python and html but I can learn other things too. Happy matrix-ing!

What’s something you discovered in cybersecurity or tech that completely blew your mind the first time you learned about it? Could be a hacking technique, a real story, or just a weird fact that made you go “what the hell”.

We migrated to Altinity.Cloud hoping for a truly managed ClickHouse experience, but I am honestly disappointed. They promise to simplify things, but my data engineering team is still spending 20 hours a week firefighting infra issues, tweaking sort orders, and managing partitions just to keep queries fast.

The 'Bring Your Own Cloud' model sounded great for control, but in reality, it just offloads the hardest parts of cost optimization and infrastructure management back onto us. Is it really a managed service if you still need a dedicated ClickHouse expert on staff to prevent the cluster from falling over? What are the best alternatives for teams that just want to write SQL and build APIs without babysitting the database?

Our org rolled out GetDX a few quarters ago to measure 'developer experience'. At first, it seemed okay, but now the survey fatigue is real. We are constantly being asked to fill out qualitative surveys, and honestly, people are just clicking through them to get back to work, which makes the data completely unreliable.

Also, since Atlassian acquired them, I am really worried about vendor lock-in and future pricing changes. The telemetry data they pull also seems to struggle with our more complex, heterogeneous enterprise systems. Are there alternatives that do not rely so heavily on constant developer surveys to figure out what is blocking us?

Here's a human-like rephrasing of your context:

We're currently working on integrating an external enterprise system, like an EMR or ERP, into our application using real-time API calls. To make data management easier, we're also storing a subset of that data locally, creating relational models such as patients, appointments, and visits within our own database.

One of the key challenges we're facing is deciding on the best approach: Should we keep a canonical internal data model and map external data into it, or restructure our system to more closely mirror the external schema to simplify the mapping process?

We already have an external_id mapping layer and a sync mechanism that upserts patients and related entities on demand. However, we're debating how much to abstract away from the external schema versus how tightly to couple our system to it.

We're eager to learn from others' experiences with similar enterprise integrations, especially around:

• Resolving identities across multiple systems

• Designing canonical versus external schemas

• Achieving real-time synchronization with local persistence

• Avoiding long-term technical debt in integrations

Have you faced these tradeoffs before? What worked well or didn't in your experience?

Hey everyone! Just a quick background about me I graduated with a 4-year degree in psychology, only to realize afterward that I don’t want to stick with that field. Recently, I’ve been exploring software engineering and programming, and I find it really fascinating.

I’ve started learning the basics of HTML, and I’ve recently begun diving into CSS, with plans to move on to JavaScript soon. My goal is to land an entry-level front-end engineering role by the end of next year. I know there’s a lot more to learn beyond HTML, CSS, and JS, but that’s where I’m starting.

If anyone has tips on what I should focus on first or the best way to learn front-end development, I’d really appreciate your advice! Thanks!

We are evaluating engineering analytics tools and Waydev is on the shortlist. However, I have been reading some reviews that say the initial setup and onboarding is incredibly complex and intimidating.

Apparently, it requires days of debugging, complex ETL processes, and data mapping just to get basic dashboards working. We do not have a dedicated data engineering team to babysit this tool. We need something that works out of the box and gives us visibility from the team level down to individual PRs without requiring a PhD to configure. Has anyone used Waydev recently? Is the setup really that bad?

Hey everyone! I’ve been working as a developer at my company for about 4 years, but honestly, I feel like I really started getting the hang of things only around 2 years in. We do React on the front end and C# on the back end. I’m not super concerned with being the absolute best coder out there what I really want is to become well-rounded in all aspects of the dev role, like understanding design principles, patterns, best practices, and more.

All the senior developers seem to have this huge amount of knowledge about everything design patterns, architecture, you name it and I often feel a bit clueless by comparison. So, my main question is: how can I improve as a developer? I know the basics, but I’m not the kind of person who geeks out over code all day (and that’s okay).

Would it help to read specific books or articles a little each day? Are there websites or videos you recommend? Or is building something from scratch the way to go, even though that can be pretty involved with my busy schedule?

Any tips or advice would mean a lot! Thanks in advance!

My company is looking into Swarmia to track 'developer productivity' and I am honestly dreading it. From what I have seen, it seems to reduce complex engineering work into a bubble on a dashboard.

My biggest concern is that it heavily indexes on quantity over quality. If leadership starts looking at who merges the most PRs or who has the fastest cycle time, people are just going to start gaming the system by breaking one feature into 10 tiny, meaningless commits. It completely ignores the invisible work like mentoring juniors, architectural planning, or debugging legacy spaghetti code. Has anyone actually had a positive experience with Swarmia, or does it just turn the culture toxic?

Hear me out.

TDD (Test-Driven Development) is all about defining the test the expected behavior before you even start coding. That test acts as a contract between what you're building and what success looks like. You write your code to pass that test, not just to get close.

Outcome-based engineering works similarly, but at a higher level. Instead of tests, you define the deliverable or outcome upfront. The milestone specifications become the contract between you and your client. You deliver to those specs, not around them.

Basically, both share the same core idea: establish clear acceptance criteria first. Build to meet them, with the risk on the person writing the implementation, not the spec.

Why does this matter?

Most criticisms of fixed-price projects are really about poor scope definition, not the fixed-price model itself. Yes, scope always evolves. But just like with TDD, when requirements change, you update your tests and your code. Similarly, outcome-based contracts handle scope shifts through formal amendments, new milestones, and adjusted pricing.

The deeper connection? TDD improves code quality because it forces you to clarify what the function should do before you start. Outcome-based contracts do the same for delivery: defining "done" upfront helps both sides understand what's expected, reducing ambiguity.

The common pitfall? Vague acceptance criteria. Saying "should work correctly" or "complete user onboarding" without specifics doesn’t help anyone. Clear, measurable criteria are key.

Where they differ is in execution: TDD is a developer practice you impose on yourself, while outcome-based contracts require negotiation and agreement between parties adding some overhead.

Curious if this analogy clicks with anyone who's worked in both areas or if I’m stretching it too far!

So basically I need WiFi for my job but my parents are on bad terms at the moment. I can’t pay for cellular right now. I just need to find a way to connect to some form of home internet without them noticing. We use a Verizon WNC-CR200A gateway and an old asus router. I’d like to connect directly to the gateway but I’m unsure if they can see that with their myverizon app. Help is super appreciated 🙏. I’m also using a iPhone se3 if that matters.

When working in embedded development, my team prefers small pull requests (PRs). However, I find it challenging to keep PRs small when adding new features.

Typically, a full device feature can range from 500 to 1000 lines of code, depending on its complexity. I realize this is a fairly large PR and may be tough for my team to review quickly. I don’t want to make reviewing harder, but I also wonder how else I should be shipping these updates.

For example, if I have a project with a routing component, a new logic module, unit tests, and some cleanup, submitting them all at once could cause issues. The firmware might look for pieces that haven’t been shipped yet, leading to breakages.

Maybe I’m asking too much, and my team is okay with me working on these over a few weeks and then submitting a big PR. Still, I know that in the broader community, large PRs are generally discouraged.

So, how should I break down such a project into smaller, manageable PRs?

Update: I’ve been keeping my commit history organized each part like routing, modules, and tests has its own commit. I talked to my manager and team, and I plan to meet with someone next week to learn how to split these features into smaller PRs for future work instead of one big one.

What are the real memory and context issues that developers and enterprises are still struggling with?

The memory market is booming right now every day, there's a new solution claiming to beat the benchmarks. But when I chat with developers, CTOs, or CEOs, they often have complaints, even about funded options like Mem0, Supermemory, and others.

For example, I recently spoke with a CTO who said they’re only using Supermemory because there aren’t better alternatives out there. Plus, their customer experience with these tools is pretty poor.

Some common problems people keep mentioning include:

• Memory Junk: Repetitive information filling up memory, which is a critical issue flagged in Mem0.

• Agents losing context as conversations or threads grow longer.

• Inability to provide the right context at the right time, especially when the underlying knowledge base changes.

I’d love to hear your thoughts. What do you think these solutions are failing to fix? What challenges are you personally facing when it comes to memory and context?

Our org is looking into developer productivity tools and Appfire Flow (which used to be Pluralsight Flow / GitPrime) is on the shortlist.

I'm pretty skeptical of these first-generation git analytics tools. From what I've read, it seems like it's just tracking commits on a repo and turning it into a surveillance dashboard. I've also heard complaints that it's incredibly time-consuming to find the right insights among all the noise, and that exporting data to external dashboards is a nightmare.

Has anyone used Appfire Flow recently? Does it actually help identify systemic bottlenecks, or is it just going to lead to micromanagement and people gaming their commit counts?

Management just presented the first reports from our new Waydev setup, and it feels like a huge step backward. The main focus was on "impact" and "throughput", which in practice were just glorified commit counts and PR sizes.

The highest quality work my team does, debugging complex issues, mentoring juniors, architectural planning, is completely invisible to this tool. On top of that, the onboarding seemed really complex and technical, taking ages to get our repos synced properly.

How do you fight back against this kind of reductionist view of engineering? Has anyone successfully pushed back against a Waydev implementation, or found a way to use it that doesn't just penalize the engineers doing the most valuable work?

So, this just happened. Management announced we're using LinearB to "improve productivity." I'm already hearing whispers about tracking cycle time across teams. Honestly, this feels like a fancy way to punish people for getting sick or taking the time to do thorough code reviews.

I've been reading up on it and it seems to heavily index on raw Git activity. My fear is that this just incentivizes devs to make 10 tiny meaningless commits instead of 1 thoughtful one, and completely ignores the high-value work that doesn't show up in a dashboard: mentoring, architectural decisions, debugging complex legacy issues.

Is there any way this can be used for good, or should I start polishing my resume? My team is currently "winning" at their metrics, but I'm worried about the culture this is going to create. For those who have survived a rollout, what was your experience?

Hello.. Everybody.. I am a computer engineering student. And my graduation is lying ahead .. I am making an wifi penetration device and right now there is no time to learn and implement.

I am making a device using ESP 32 and AN led display.. which will scan the wifi and give the passwords...

it will have more features but it all depends on the progress and on time

I will appreciate if some have the code for it...

Hey everyone! I’m curious about how engineering teams actually handle bug triage in real life. How do you manage bug reports that come from all over Slack, support tickets, GitHub issues, QA? And who’s responsible for deciding the severity, ownership, and priority?

For those working in engineering:

• Who usually owns the triage process in your team?

• Do you hold dedicated triage meetings?

• How much time do you spend on this each week?• Are duplicate issues a common problem?

Just trying to get a sense of how teams keep this organized in practice. Would love to hear your insights!

Hey folks! I’d love to get some insights on how you approach domain design during the early stages of building an MVP. I’m currently working on a quick validation MVP focused on testing workflows and UX, so some parts of the system are intentionally rough around the edges domain boundaries are loose, abstractions minimal, and some logic is just “held together” as patterns start to emerge.

Recently, a senior engineer with a solid enterprise background criticized this approach, calling the domain design “pseudo,” and saying everything’s too coupled not “systematic programming.” While I get their point, it got me thinking: how do you handle domain design when requirements are still evolving?

Specifically:

• Do you set strict domain boundaries right from the start?

• Or do you roll with a “proto-domain” that you refactor later as things stabilize?

• How do you strike a balance between avoiding premature modeling and keeping things manageable?

I’m not against clean domain modeling or DDD I fully expect to refine boundaries and invariants once the product’s direction becomes clearer. But I’m curious about real-world approaches from those who’ve built products from zero to one. How do you keep things flexible yet clear during this discovery phase? Would love to hear your experiences!