Improving AI with Model-Breaking Tasks

Frontier models don’t improve on easy problems. They improve when the tasks break them. In this case study, we delivered model-breaking coding tasks across multiple programming languages to help a leading AI lab expose real failure modes, strengthen reasoning, and push performance beyond benchmarks. This is what post-training looks like when rigor matters. Read the case study →https://bit.ly/49z3Biu

🚨 Why New Programming Languages Are Failing 🚨 Every year we see new languages promising: ✔️ Cleaner syntax ✔️ Better performance Yet most of them disappear. Because syntax doesn’t win — ecosystems do. Libraries, tooling, community, and job demand decide which languages survive in the real world. I’ve shared a deeper breakdown in my latest blog 👇 🔗 https://lnkd.in/g6267t_P Which language do you think will still matter 10 years from now? 👇 #programming #developers #tech #softwareengineering #coding

From USV's year end wrap up: "Coding agents are doing to source code what compilers did to machine code: push the code below the interaction surface". [Fred Wilson] spent fifteen years working tirelessly to get computer science classes into the NYC public school system and the hardest part was teaching kids new languages that they needed to master to instruct machines. Now they just need one of many coding assistants and an understanding of how to do the stitching. That is a skill we still need to teach, but it is an easier skill to teach and the results come more quickly. Like Instagram made everyone a photographer, AI will make everyone a coder. "

English: The New Coding Language The bottleneck in software development is no longer syntax. With AI's advanced reasoning, English is becoming the primary programming language, allowing creators to build complex apps simply by articulating goals. #Coding #SoftwareDevelopment #GenerativeAI

Fascinating post by @karpathy on the ongoing refactor of software engineering. Prompts, context, memory, and MCP now feel like core abstractions. I’ve seen this shift firsthand while building a stock analysis agent—only a fraction of the work was traditional coding; most of it went into orchestrating context and teaching the system what actually matters. What interesting AI projects are you building to master this shift? #AgenticAI #Programming #codingfuture

AI converts code between programming languages with powerful efficiency, making language barriers a thing of the past. Read more: https://lnkd.in/dtaXkjVE #aitools #artificialintelligence

A well-structured prompt is no longer a nice to have, it’s the new programming language of the AI era. The people who understand roles, constraints, context, and output design are already outperforming those who only write code. In today’s landscape, a great prompter can genuinely become more valuable than a great coder because clarity now builds what syntax once did. #PromptEngineering #MindsetShift #AIContentStrategy

Why Programming Is About Thinking, Not TypingProgramming is not about writing as much code as possible, but about problem-solving and logical thinking. Good programmers spend more time analyzing problems than typing code. Writing clean, maintainable code is more valuable than writing clever solutions. Learning this mindset accelerates understanding any programming language. Developing this skill strengthens both logical reasoning and creativity. #ProgrammingMindset #CodingLife #ProblemSolving

Coding agents represent the next layer of abstraction in programming. We started with binary, then moved to assembly so humans could actually read what they were writing. C came next, shifting focus from how the machine works to what we want it to do. Java abstracted away memory and threading so developers could think at the system level instead of the hardware level. Now, Ai tools remove the need to manually write syntax at all. At every transition, there were voices claiming this wasn’t “real programming” anymore. At every jump in abstraction, people warned that engineers would become obsolete. Yet history shows the opposite: each leap expanded what software could do and increased the demand for people who know how to build it. Higher abstraction didn’t end engineering. It multiplied its impact.

💻 Coding looks complex until you understand the symbols behind it Every programming language relies on symbols that define logic, structure, and flow. Mastering them early makes coding cleaner and faster. 🔣 Essential Coding Symbols: 🧩 { } Curly Braces – Code blocks & scopes 🔘 ( ) Brackets – Functions & conditions 🧱 [ ] Square Brackets – Arrays & indexing ➖ = Equals – Assignment 🔍 == Double Equals – Comparison ⛔ ; Semicolon – Statement termination 📝 ' ' / " " – Strings & text values #️⃣ # Hash – Comments & directives 📌 Understanding symbols = fewer bugs + better readability. #CodingBasics #ProgrammingFundamentals #LearnProgramming #DeveloperTips #CodeNewbie #SoftwareDevelopment