Introducing Nuanced: a structured context layer for AI coding tools

AI coding tools can boost developers productivity tremendously. In this interesting session you get to know the underlying models and explore how their usage is changing the way software is built. What are the benefits and the pitfalls, the security and legal risks and how to mitigate them, best practices for prompt engineering for efficient code generation and current AI coding tools pros and cons. Worth watching! https://lnkd.in/ergg_Kbp

📢 New from The AI Gaze In this week’s AI Gaze Spotlight, we discussed with Ifihanagbara Olusheye, a Software & Machine Learning Engineer, to explore “The Future of Programming in the Age of AI.” We discussed: 🧠 How AI tools are changing the way we code ⚙ What skills developers need to stay ahead 🤝 Why human creativity still matters in an automated future ✨ The future of programming isn’t less human, it’s more human than ever. 👉 Read the full conversation here: https://lnkd.in/ecpMjcMH

A must-read conversation with Ifihanagbara Olusheye on The Future of Programming in the Age of AI. You still have the chance to check it out 👇 https://lnkd.in/eTD6qSb6

A worthy follow-up to Peter Ramsey's amazing Lovable case study. Again.. not saying all AI usage for coding is bad... but ... there is still a lot of unused AI-generated apps and websites people create (also wasting tons of environmental resources). Vibe coding is mostly not adding any value to your skill set. Usage of AI coding tools to make improvement to existing code by skilled developers is good... but.. does not seem to be the case for most usage. AI Slop (in code form)!! The risks here are much larger than the AI-generated images or videos (which have their own can of worms!) #vibecoding #ai #thinkbeforeuse

Google DeepMind just created a benchmarking system to measure the vibey-ness for AI coding 🧑🏻💻 Most code benchmarks only test if it works. Vibe Checker an even better question: does it read like something a real developer would write? It uses a system called VeriCode, built around 30 measurable behavior rule categories to score how well LLMs follow human-like coding conventions. While leading models handle functional tests well, their performance dropped below 50% when asked to follow multiple instructions for clarity, documentation, and proper structure. It’s a small but important shift in how we think about model evaluation, from functional correctness to behavioral alignment in production scenarios. Paper: https://lnkd.in/gM6XQARz

Stop asking AI coding agents to fix one function. Give them the whole story. Here's what I keep seeing: teams use AI coding agents like Claude Code, Cursor, or Devin like this— "Write this function." "Now fix the import." "Now handle the edge case." "Now add logging." Five iterations later: spaghetti code. Each patch worked in isolation, but the AI agent never understood what it was building. It's like asking Picasso to paint a masterpiece one square inch at a time. You don't get a masterpiece. You get a mess. Learn how to fix this: https://lnkd.in/gTB4tpzG I respond 'test' - and I'll send you the prompting guide

Anthropic brings Claude Code to the web, giving developers browser access to powerful AI coding tools. 𝗙𝗼𝗿 𝗺𝗼𝗿𝗲 𝗱𝗲𝘁𝗮𝗶𝗹𝘀 𝘃𝗶𝘀𝗶𝘁 ➜ https://lnkd.in/erJ24YsS

🚨 Here's my conversation with Isaac Flath about AI-assisted coding. We discuss accountability, the role of AI in modern tooling, and free resources to get started with taking AI seriously. https://lnkd.in/esgcBxYh Use code "BAS" to get 35% off the AI Assisted Coding Course by Isaac Flath and Eleanor Berger

Why Most AI Coding Fails (and How to Fix It Step-by-Step) I used to overload coding agents with details, thinking more context meant better results. It doesn’t. Too little context confuses them, but too much buries them. The real skill is learning where the balance is. In this video, I show how to reach that balance using Context Engineering. Link in the first comment!

A bigger idea: progress in AI coding isn’t about replacing developers — it’s about designing better context, feedback loops, and interfaces so humans and models can think together.🎥 Watch the full session on YouTube: https://lnkd.in/ee-kTtwU