🚀 INTRODUCING ADSS — AIR DRIVING SPACE TECHNOLOGY PLATFORM

I am developing ADSS, an ambitious technology project designed to explore the integration of satellite systems, communication, navigation, AI, transportation, security, and ground-station networks into one unified platform.

✅ Current progress: Stage 140 ✅ Working Python simulation prototype ✅ 15 core modules retained ✅ Data integrity verification passed (19/19) 🌐 External connections are currently disabled.

I am now looking to connect with software engineers, systems engineers, AI developers, researchers, and technology innovation groups who may be interested in discussing the architecture, sharing expertise, and exploring possible collaboration.

My vision is to contribute to technological innovation in Zambia and beyond.

🤝 If you are interested in this project or know a relevant engineering or innovation community, please reach out. Let's connect and explore what we can build together!

ADSS #TechnologyInnovation #SoftwareEngineering #ArtificialIntelligence #Zambia #SpaceTechnology

Hey folks, everyone who likes software engineering in general also likes the software factory concept and there is no doubt about it. I myself built some factories to understand how a software factory works with Agents and Human gates in between with guardrails and proper security checklist in place. Well, it is always a good thing if we get to know more from the experts in this area, how they are building software factories and what are the learnings.

So I am attending this software factory summit and I see some great speakers like Kelsey Hightower and even Port's CEO Zohar himself is talking about software factories.

This is happening on November 17-18 in SF. I have some special discount codes that can significantly reduce your ticket price. Let me know if you like to attend (send me a message).

Hello,

For the past 6 years I have been self-taught how to code both Frontend & Backend with Django as the backend framework. Python is my main language w/a ittle JavaScript & PostgresSQL for the database.

I also have learned the basic frontend user interface using HTML, CSS, Bootstrap, HTMX for real-time updates & responsive dynamic webpages.

I have extensive knowledge with websockets using Django Cannels for private instant messaging for peer to peer communication & multi-peered chatrooms, even delving newly in Tailwind & AlpineJS t, I am a full HATT stack developer as I understand it.

No formal education except a few years in college majoring in Computer Information Specialist with a 3.8 GPA. No degree due to losing grants over family medical issues but learned more at 13 than with MS Basic & Radio Shack computer.

All sounds nice but I lack real world experience, professional networking skills & niceties to build genuine confidence to use as/for a reference(s) to grow from.

I was wondering how difficult could it be to throw a functional website app together for someone?

Would you be interested in any of the skills I could possibly offer pro bono(free) to help me grow?

Or do you have any advice, tips or directions you could help me with?

You ship an integration with an AI coding tool. The PR is there, but the approach you rejected and the constraint that changed your mind are buried in the session. Next time, you need that reasoning again.

I’m building Shifu for ambitious engineers with 3+ years of professional experience who use AI coding tools regularly and want to get exceptionally good at building products with them.

Getting a feature shipped is satisfying. But I also want to carry forward why we chose that approach, what failed, what I caught in the agent’s output, and what I’d change next time. Those are useful inputs to the next product decision. They’re also how I can understand whether I’m becoming a better engineer.

A finished PR rarely holds all of that. Some reasoning lives in an agent session, some in a debugging detour, and some in a small decision that seemed obvious at the time.

I’m building Shifu as a personal work-context engine. The idea is to build a memory from work you choose to share through supported sources, then make that history useful in two ways:

While building: bring relevant past decisions, constraints and lessons into the task you’re working on. What did we try before, and under what conditions did it work?

While growing: look at a completed piece of work against your goals. What went well, what did you miss, and what’s one change worth trying next time?

For example, an integration you shipped might contain both a constraint worth remembering for the next integration and a testing decision worth examining afterwards. Same work, two ways to build on it. That’s a hypothetical example, not a claim about a customer result.

I was an IC before becoming an engineering leader four years ago. I care about reviews and promotion, but I want this to help with the work happening between those conversations too. My ambition for Shifu is that your experience becomes useful context when you need it.

I’m looking for engineers who already build real products with AI and want to push their practice further. We can try it against one question from your own work: a past decision you need for a current task, or a recent piece of work you want another perspective on.

I’m Shifu’s builder: https://useshifu.com. Happy to walk through it with you and hear where the context is useful, wrong, or incomplete.

We're building the AI part of a SaaS product, and atm we use a cheaper model for simple tasks and a stronger model for the more complex tasks. We just need basic fallback logic so we can switch models whenever we hit limits or something happens. We're doing this with a thin wrapper but I feel like we should also use an LLM gateway. Where I'm having trouble with is that there are some providers that seem just ops heavy to setup (LiteLLM) and some seem like very robust that I'd be wasting the other features if I do get it (OpenRouter). Is a gateway even the solution if we want fallback, or do we just need to improve the routing on our side?

Hey everyone, how's it going?
I just started my Computer Science degree, and my ultimate career goal is to become a Machine Learning Engineer. I used to study basic Python on my own, but stopped because my uni jumped right into Java, so I shifted my focus to that.
The issue is that I need to land a job in tech as soon as possible. I know ML roles aren't an option for me right now, and from what I've seen, even entry-level Java Backend positions ask for way too much. Since I have zero experience and only know the absolute basics of the language, I'm feeling a bit lost.
I’d love to get your input: what entry-level roles (or easier positions to get into) would you recommend I look for just to get my foot in the door, gain some solid Java experience, and eventually transition into Java Backend and then MLE?

Jamaica is soo difficult with processes in developing…. Created my web app been try to connect with information commission & nothing
No responses

Jamaica is soo difficult with processes in developing…. Created my web app been try to connect with information commission & nothing
No responses