Developer productivity isn’t just about creating more code, faster. It's about engineering faster and smarter with codebase context and quality. Great dev teams scale by keeping standards high, reducing tech debt, and helping junior devs contribute meaningfully to complex systems. Hear more from Nnenna Ndukwe about how codebase context and multi-agent workflows turn rapid output into maintainable, production-ready software. 👉 https://lnkd.in/eFxhPnkk
How to boost dev productivity with codebase context and multi-agent workflows
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AI tools are revolutionizing software development by automating repetitive tasks, refactoring bloated code, and identifying bugs in real-time. Developers can now generate well-structured code from plain language prompts, saving hours of manual effort....
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AI tools are revolutionizing software development by automating repetitive tasks, refactoring bloated code, and identifying bugs in real-time. Developers can now generate well-structured code from plain language prompts, saving hours of manual effort....
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I get the same question almost daily: what’s different about Augment Code compared to all the other AI coding products? From the outside looking in, the space is crowded. It’s hard to understand which companies have longevity. New competitors and LLMs popping up weekly. 0-5M in days, 0-100M in months… The answer has a number of dimensions to it: - We’re singularly focused on Enterprise software engineers, not vibe coders working on 0-1 projects. - We invested 2+ years in stealth solving the hardest problem first - providing real time context understanding of codebases at massive scale and complexity. As codebase complexity increases, our differentiation shines. - Self-serve isn’t about the revenue. It isn’t our intended profit center. It’s where developers around the world can experience our context engine and realize the potential in codebases where other products fail. - We believe the majority of AI’s impact in software engineering will occur outside of the IDE. This is why we didn’t fork an IDE. We built infrastructure to meet organizations where they are today, and evolve with them as they drive automation across the full SDLC using our platform. Augment is unequivocally the best product for professional software developers. Our win rate is 80%+ in the field. And more importantly, we’re building long term business relationships to help our customers transform their engineering culture and processes. Visit https://lnkd.in/gPysZips to learn more.
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As engineers it is critical that we differentiate between 0 to 1 AI coding tools used by enthusiasts, which generate AI slop and tech debt, versus professional tools like Augment Code that you can actually rely on to ship production code in a large, messy million file codebase. This distinction doesn’t get enough attention in the question “is AI all a hype?”. Once you start using a professional AI coding tools like Augment daily and it cuts your onboarding time from 3 months to 3 weeks, it’s hard to deny that it’s going to transform software engineering more than any developer tool in the last couple of decades.
I get the same question almost daily: what’s different about Augment Code compared to all the other AI coding products? From the outside looking in, the space is crowded. It’s hard to understand which companies have longevity. New competitors and LLMs popping up weekly. 0-5M in days, 0-100M in months… The answer has a number of dimensions to it: - We’re singularly focused on Enterprise software engineers, not vibe coders working on 0-1 projects. - We invested 2+ years in stealth solving the hardest problem first - providing real time context understanding of codebases at massive scale and complexity. As codebase complexity increases, our differentiation shines. - Self-serve isn’t about the revenue. It isn’t our intended profit center. It’s where developers around the world can experience our context engine and realize the potential in codebases where other products fail. - We believe the majority of AI’s impact in software engineering will occur outside of the IDE. This is why we didn’t fork an IDE. We built infrastructure to meet organizations where they are today, and evolve with them as they drive automation across the full SDLC using our platform. Augment is unequivocally the best product for professional software developers. Our win rate is 80%+ in the field. And more importantly, we’re building long term business relationships to help our customers transform their engineering culture and processes. Visit https://lnkd.in/gPysZips to learn more.
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There's a massive yet quiet shift occurring in software development thanks to Agentic Coding (a.k.a. Vibe Coding with Engineering Discipline). Massive because, for the first time in my entire 20+ year career the job of software engineers is radically changing. And changing for the better. A LOT better, in fact. Quiet because only a small fraction of the industry (including devs!) has caught on. One of the many implications in this shift has to do with a topic near and dear to my heart: the size and shape of software teams. We've known for a while that small, high performing, cross-disciplinary squads are the way to go. The rise of Agentic Coding means teams can get even smaller (tiny, even!) and can drive an order of magnitude (in the quite literal sense) more productivity. Check it out! https://lnkd.in/gPGxsW2H
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💻 Code Review Best Practices Code reviews aren’t about perfection — they’re about progress, collaboration, and learning. Here are 7 simple rules I follow when reviewing code: 1️⃣ Be respectful 2️⃣ Focus on the code 3️⃣ Prioritize issues 4️⃣ Check integration 5️⃣ Give clear feedback 6️⃣ Resolve conflicts 7️⃣ Review promptly ⚡ Remember: great code reviews build strong teams. —— 👋 PS – Want instant reviews inside your terminal? CodeRabbit CLI helps catch bugs, detect AI mistakes, and hand context back to coding agents like Claude Code or Cursor for auto-fixes. Stay in flow: code, review, and commit without leaving the terminal. ♻ Repost if you want to make code reviews better for developers. #CodeReview #SoftwareEngineering #DeveloperExperience #CleanCode #DevOps #AItools #CodeQuality #Collaboration #Productivity
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1 Minute Reads | Catching A Vibe "Vibe coding" is rewriting software development. Instead of writing code, developers simply describe what they want, and AI generates it. Turning anyone into a technical founder. Recent standouts include: - Lovable: $1B ARR in 12 months - Replit: $2.8M to $150M ARR in under a year - Anything: $2M ARR in two weeks But there are a few things I am watching in the space. I believe there remains significant progress to be made before nontechnical users can reliably create products that are ready for deployment. Also, while early adopters are excited to experiment with new products retention metrics over the next 6-12 months will provide insight into the long term winners. The companies solving deployment complexity (databases, payments, authentication) will separate from the prompt-to-prototype crowd. Here is where I see the democratization of technical skill. Let me know your favorite platform or app built on one of these systems.
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I feel that this should not need to be said...but in today's software development culture, it does... ➡️ Please do not stack rank your developers. It's tempting to want to do this, especially when the boom of AI promises to do more with less. So you want to know...who's doing more...and who's doing less? But instead of getting an accurate picture, you will get: ✅ everyone gaming the metrics ✅ knowledge hoarding instead of performance improvement ✅ an exodus of the best developers who leave for companies that treat them better Read more about why it doesn't work and what to do instead. https://lnkd.in/eXfHsiKA
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Developers thrive on tools that power daily workflows. But what happens when AI steps in to reshape software development? The shift is here. See what it means: https://shorturl.at/UZ6u3
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AI-developed software can go all the way to production. I’ve got live apps people pay for and use. But AI Software Engineering isn’t business as usual. It changes everything: the speed, the skills, and even the size of the team. What used to take fifteen people can now be done by two or three. Rapid prototyping and user testing happen in days, not weeks. Monetization can start almost immediately. The trade-off? It’s easy to skip proper planning early on, which can cause headaches later. As roles blur, DevOps leaning into software engineering, small teams doing the work of large ones. Learning from experienced builders, system architects, and engineers is more valuable than ever. We’re in the middle of a big shift. Move fast, stay thoughtful. What’s your take?
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