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LMLeena Malhotratechwithleena.hashnode.devMar 25 · 8 min read

Claude Opus 4.6 vs GPT-5 on Multi-Step Reasoning: Where Each One Starts to Fail

Both models handle simple reasoning well. The gap opens when tasks have multiple dependent steps — and the failure type is different for each one. Key Takeaways Neither model dominates multi-step re

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LMLeena Malhotratechwithleena.hashnode.devMar 18 · 11 min read

Debugging AI-Generated Code Across Different Models

The bug was invisible to three different AI models before a human finally spotted it. I had asked Claude Opus 4.6 to write a function that parsed user-uploaded CSV files and extracted email addresses.

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LMLeena Malhotratechwithleena.hashnode.devJan 19 · 6 min read

Why Consensus Matters More Than Confidence in AI Systems

We are building our digital infrastructure on a fault line. The current generation of Large Language Models (LLMs) suffers from a specific, dangerous pathology: they are programmed to be confident, not correct. When you ask an AI a question, it does ...

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LMLeena Malhotratechwithleena.hashnode.devJan 15 · 5 min read

A Production Rule for Handling Model Uncertainty

You are shipping gambling algorithms, not software. I look at the codebases of "AI-native" startups, and I see the same terrifying pattern. A developer makes an API call to an LLM. They get a response. They JSON.parse() it. And they push it to the fr...

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LMLeena Malhotratechwithleena.hashnode.devJan 9 · 4 min read

LLMs Fail Less Randomly Than You Think. The Pattern Is the Problem

We treat Large Language Models (LLMs) like chaos engines. When an LLM hallucinates a library that doesn't exist, or confidently explains a security vulnerability that isn't there, we shrug. "It's just the temperature," we say. "It's the stochastic na...

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LMLeena Malhotratechwithleena.hashnode.devJan 7 · 4 min read

How I Built a Reproducible AI Testing Environment for My Projects

In the world of software development, we are used to deterministic systems. If you write 2 + 2, the code should always result in 4. However, when you start building with top ai models, that predictability vanishes. AI is probabilistic—it's more like ...

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LMLeena Malhotratechwithleena.hashnode.devJan 6 · 6 min read

Inside the Black Box: How Language Models Interpret Developer Prompts

You’ve been asking the wrong question. Every time I open a new thread on Twitter or browse the r/programming subreddit, I see the same debate playing out. Developers are arguing over syntax. They are trading prompt libraries like they used to trade P...

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LMLeena Malhotratechwithleena.hashnode.devDec 30, 2025 · 4 min read

Why I Stopped Trusting AI Outputs and Built Validation Layers Instead

I used to think that the specific AI tool you used didn't matter as much as the prompt you wrote. I believed that if your instructions were clear enough, any high-level model would give you a usable result. I treated AI like a utility—like electricit...

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LMLeena Malhotratechwithleena.hashnode.devDec 29, 2025 · 9 min read

Under the Hood: Why Context Handling Matters More Than Model Size

The AI arms race has become a numbers game. GPT-4 has 1.76 trillion parameters. Claude has 200 billion. Gemini Ultra claims even more. Every model release comes with bigger numbers, flashier benchmarks, and promises of unprecedented capability. And y...

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CACrompt AIcromptaiblog.hashnode.devDec 22, 2025 · 8 min read

SEO in 2025: How Artificial Intelligence Is Changing Rankings

In early 2025, search engine optimization (SEO) feels less like a formula and more like a conversation — one between content creators, users, and increasingly advanced AI systems. I remember in 2018 when ranking well felt like assembling a puzzle of ...

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Trending tags this week

Claude Opus 4.6 vs GPT-5 on Multi-Step Reasoning: Where Each One Starts to Fail

Debugging AI-Generated Code Across Different Models

Why Consensus Matters More Than Confidence in AI Systems

A Production Rule for Handling Model Uncertainty

LLMs Fail Less Randomly Than You Think. The Pattern Is the Problem

How I Built a Reproducible AI Testing Environment for My Projects

Inside the Black Box: How Language Models Interpret Developer Prompts

Why I Stopped Trusting AI Outputs and Built Validation Layers Instead

Under the Hood: Why Context Handling Matters More Than Model Size

SEO in 2025: How Artificial Intelligence Is Changing Rankings