Immuta CTO on the risks of vibe coding in software development

Vibe coding is the next step in how generative AI impacts the software development lifecycle. But what are its pros and cons? While it can produce functional prototypes quickly, some question if it can create sophisticated, scalable, and secure applications suitable for enterprise use. This article explores what vibe coding is, what it is not, and how to use it safely in production software. #SoftwareDevelopment #VibeCoding  

"Vibe coding" is frequently overlooked by experienced engineers as a shortcut that leads to technical debt. However, this viewpoint overlooks a significant transformation occurring in our industry. We are entering a new era where AI serves as a disciplined partner to our creative intuition, enabling us to build faster and more innovative than ever before. In my latest article, I explore how this combination of human vision and machine precision is shaping the future of software development.

How Claude Code is transforming software engineering with AI 🚀 Claude Code, Anthropic’s groundbreaking AI-powered coding assistant, has revolutionized how developers build software. Built with an “AI-first” philosophy, this tool writes about 90% of its own TypeScript code and enables rapid prototyping—up to 20 feature prototypes in just 2 days! With features like intelligent filesystem exploration, permission-based local execution, and support for subagents, it’s reshaping the developer experience. Since its public release in May 2025, Claude Code usage has exploded, driving a 67% increase in pull request throughput even as Anthropic doubled its engineering team size. Whether it's speeding up code writing, running tests, or automating reviews, Claude Code is enabling engineers to iterate faster and smarter. This hints at the future of software development—where AI agents are trusted teammates, accelerating innovation while maintaining safety and simplicity. How is your team leveraging AI tools to boost productivity? #AIinSoftware #ClaudeCode #ArtificialIntelligence #SoftwareDevelopment #DevTools #AIAssistedCoding #Innovation #TypeScript #TechTrends #DeveloperExperience #ProductivityBoost #AnthropicAI https://lnkd.in/dm5n2A2g

I just finished tackling a critical challenge in modern software development: building a truly Production-Ready RAG AI Agent. It's easy to create a functional prototype, but building a system with fault tolerance, observability, and scalability is where the real work begins. This project goes beyond a simple chat interface. It utilizes Retrieval-Augmented Generation (RAG) to allow users to interact with large document sets, providing accurate, context-specific answers. Architectural Deep Dive: - Foundation: The agent is powered by Python and features an intuitive front-end developed with Streamlit. - Vector Search Engine: I integrated the Qdrant vector database, a choice that ensures lightning-fast, high-dimensional similarity searches necessary for RAG to perform under load. - Orchestration Layer: Key to its "production-ready" status is the use of Ingest for workflow management. This tool automatically handles: - Reliability: Implementing retries for external LLM calls to prevent service disruptions. - Cost & Stability: Enforcing rate limits and throttling to manage API usage and prevent system overload. - Transparency: Providing end-to-end observability, allowing me to trace every step of the RAG pipeline for immediate performance tuning and debugging. This build was a fantastic exercise in moving past theoretical knowledge and applying best practices to a complex, real-world AI architecture. Take a look at the technical architecture and implementation details: https://lnkd.in/gGr69BPJ

We’re entering a new chapter in development: “vibe coding” — where #AI assisted prompts evolve prototypes into working apps. It’s faster, more intuitive, and more collaborative… but also riddled with new risks. From architectural ambiguity to security gaps and IP uncertainty, this InfoWorld piece dives into both the promise and the pitfalls of #vibecoding. Worth a read if you’re thinking about where software development is headed. #SoftwareEngineering

We’re entering a new chapter in development: “vibe coding” — where #AI assisted prompts evolve prototypes into working apps. It’s faster, more intuitive, and more collaborative… but also riddled with new risks. From architectural ambiguity to security gaps and IP uncertainty, this InfoWorld piece dives into both the promise and the pitfalls of #vibecoding. Worth a read if you’re thinking about where software development is headed. #SoftwareEngineering

We’re entering a new chapter in development: “vibe coding” — where #AI assisted prompts evolve prototypes into working apps. It’s faster, more intuitive, and more collaborative… but also riddled with new risks. From architectural ambiguity to security gaps and IP uncertainty, this InfoWorld piece dives into both the promise and the pitfalls of #vibecoding. Worth a read if you’re thinking about where software development is headed. #SoftwareEngineering

🚀 Claude Code can make you a 10X dev — or have you running in circles. If you’re already a 10X dev, it can push you to 100X. Here’s the cheat sheet I’ve been using to get the most out of it 👇 1. Start with Plan Mode Don’t dive straight into code. Ask Claude to outline a detailed, step-by-step plan first. 2. Review & Iterate on the Plan The first draft is never the best. Challenge it, ask for tradeoffs, refine. Then move to coding. 3. Generate Documentation (.md files) Have Claude write architecture and implementation notes in Markdown. → These become living specs & onboarding docs. 4. Q&A Carefully Claude is best treated like a senior engineer sparring partner. Go back and forth. Ask questions. Don’t just copy-paste. 5. Test Locally Run npm run dev (or your setup) and validate results before shipping. 6. Use Real Errors Feed Claude detailed logs from your terminal or browser console. Don’t just say “it doesn’t work.” Specific errors = faster fixes. 💡 Claude isn’t just autocomplete. Used right, it’s your 100X multiplier: 👉 Faster builds 👉 Smarter debugging 👉 Clearer documentation 👉 Curious: What’s your best tip for coding effectively with AI?

Have you ever built something with AI that worked perfectly… until it didn’t? Jenny Ouyang gets it. After shipping multiple AI-built products, she started seeing the same failures again and again. She noticed it was a pattern. Her latest story breaks down the few classic software engineering practices that prevent 80% of those problems. It’s a must-read for anyone building with AI who’s realizing the old rules didn’t vanish, they just moved. https://lnkd.in/g5-ZfbNe

One of the only insightful read on how to use coding agents. Grounded advice, aligns with my experience and learned about new tools along the way.  https://lnkd.in/gAR2-JgF