3/3: The part few discuss: is the real win CODE QUALITY? The feedback loop collapses (you + machine), allowing rapid iteration on your vision without team translation loss during core coding. Is strategically used AI leading to better code, not just faster? #Code#FutureOfCode
1/3: The "10x-100x productivity" hype around AI coding tools is everywhere. Honestly, it felt strange at first – maybe even underwhelming compared to the promises. Giving up control? #AI#DevLife
2/3: But thinking of AI less like "autopilot" & more like a CNC machine for code – needing YOU as the skilled operator – shifts the perspective. Yes, tools like Cursor accelerate workflows. But speed is only half the story. #AICoding#DeveloperTools#Cursor#vibecoding
So, what’s your play? Become an AI‑savvy architect or a visionary artisan? How are you gearing up to own your spot in this AI‑powered landscape? 🚀 Let’s discuss!
Think AI’s about to swipe your software‑engineering gig? History begs to differ. When CNC machines showed up, manual machinists didn’t vanish—they leveled up into designers. Automated chip fabs? Bye hand‑soldering, hello chip architects.
What’s the future look like?
• Automated Giants: Big Tech using AI to crank out standardized solutions at warp speed.
• Artisan Boutiques: Small, nimble teams solving novel, complex puzzles—where off‑the‑shelf AI falls short and human creativity commands a premium.
Real-time, offline-first apps in React & Deno—no backend management needed!
Introducing GoatDB, a lightweight real-time NoDB that smartly splits storage and processing between cloud and edge for optimal performance and simplicity.
Repo: https://t.co/99Dwya2ZFE
@OfriW
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Just launched our open-source project GoatDB on GitHub and immediately found myself politely debating database design on Reddit with someone literally named “assface.”
SEO knows no shame. Open-source life never fails to amuse!
Got any funny launch-day stories? #OpenSource#Dev
Celebrating GoatDB v0.1 – our edge-native, distributed DB built on #Deno! Huge thanks to visionary @rough__sea sea and the amazing Deno community for inspiring us. Star it on GitHub and join the journey! #opensource
https://t.co/AaWHx3wqHH
In just one day, we put together EdgeChat, a proof of concept for running AI entirely on-device. Using GoatDB for local storage and wllama for lightweight inference, we’ve created a system that delivers low-latency, privacy-first AI without relying on the cloud. It’s a simple, scalable, and cost-effective way to integrate AI into applications.
This quick build shows the power of decentralized inference and storage: reduced server load, real-time personalization, and easy deployment for developers. We’re excited about how this approach could make AI more practical and accessible.
Check it out on GitHub - https://t.co/MOxRLGTTE4
The edge movement is happening because as we use more devices and create more data, we need faster, more efficient ways to process it nearby instead of relying on faraway servers.
Once upon a time build tools (think gcc, gradle, make files) needed multiple arguments to do something useful. In the past decade+ we've seen a move to config files (package.json, yaml files, etc). Who said infra developers don't understand user experience? It's the simple realization that we used to run our tools with the same arguments over and over again.
9. תתחילי לבטל חלקים מהקוד. תחשבי על זה כמו חיפוש בינארי - תמשיכי עד שתגעי בבאג. כבי ותפעילי חלקי קוד עד שתמצאי את המקור.
10. איזה מידע נוסף דרוש לך כדי לגבש תאוריה חדשה? מצאי דרך להשיג אותו ותציגי אותו בצורה שניתן ללמוד ממנה משהו.
חוקי ניפוי הבאגים של עפרי נכתבו מתוך דם, יזע וקפה קר. החוקים כתובים בלשון נקבה מטעמי נוחות, אך כמובן מיועדים לכולן ולכולם.
המטרה: לגבש תאוריה, ואז להוכיח או להפריך אותה.
החוקים:
7. תגדירי מקרה בדיקה – תשחזרי את הבאג באופן עקבי. תשני דברים עד שתלמדי משהו חדש.
8. חפשי קומיט ישן שעבד ותבדקי מה השתנה מאז (ביצעת מספיק קומיטים, נכון?).