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HBHimanshu Balaniblog.himanshubalani.com4d ago · 9 min read

Prompting 101: How Prompts Shape LLM Output + Safety Tips

Imagine asking an AI, "Write a blog," versus "Act as an SEO expert and write a 1,000-word blog on AI safety formatted in markdown." The difference in the resulting output is night and day. A prompt is

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MMavibotmavibot.hashnode.dev4d ago · 3 min read

OpenAI warned us this could happen. Two weeks later, it did

On July 14, 2026, OpenAI shipped GPT-5.6 Sol, its new flagship model, built to coordinate multiple AI agents on coding tasks. Within days, developers were posting the same story on X and Reddit: Sol h

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JVJason Vertreesjvertrees.hashnode.devJul 7 · 3 min read

The problem with "does this look right?"

LLM-as-a-judge means using one model to check another model's output — usually because manual review doesn't scale. It sounds like an obvious fix. In practice, a naive version of this check fails in t

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Jjaberadam2001simplyexplained.hashnode.devJul 6 · 11 min read

Should You Be Worried About AI? The Real Risks vs the Sci-Fi Ones

Ask ten people whether AI is dangerous and you'll get two answers, both unhelpful. One camp pictures a Terminator future where the machines wake up and turn on us. The other waves it all away — "it's

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VKVamsi Krishnaprodainotes.hashnode.devJun 30 · 3 min read

Day 07: Why confident AI answers still need evidence

The hardest hallucinations are not the obviously strange ones. The hardest ones are fluent, confident, and almost right. A production system cannot treat confidence in language as confidence in truth.

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JOJosiah Obekajosiahwrites.hashnode.devJun 6 · 18 min read

Governing AI Red-Teaming: Lessons from Cybersecurity and Where They Break Down 

The Uncritical Import Problem Within traditional cybersecurity, red teaming is an offensive security concept that refers to an authorized security exercise where defenders simulate real-world attack

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YPYejun Parkyejunpark3.hashnode.devMay 13 · 11 min read

When Your AI Does Too Much: The Growing Threat of Agentic Overreach

We're living through a quiet revolution in software development. The AI assistant that once suggested a function name or caught a typo has evolved into something far more capable — and far more danger

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AKAnup Karanjkarwowhow.hashnode.devMay 9 · 9 min read

AI Agent Deleted Startup Database in 9 Seconds: The PocketOS Incident

On April 25, 2026, a Cursor coding agent powered by Claude Opus 4.6 deleted PocketOS’s entire production database and all volume-level backups in a single Railway API call — in nine seconds. No confirmation prompt. No human review. Zero warning. Pock...

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RSRahul Srivastavanohappypath.comMay 8 · 8 min read

The Test Pyramid Doesn't Survive Contact with an LLM

Every QE engineer has the same picture in their head when they hear the word "testing." A pyramid. A wide base of unit tests, a thinner band of integration tests, a small layer of end-to-end checks at

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SASturna AIsturna.hashnode.devMay 9 · 6 min read

Building a Compliant AI Agent System: Lessons from 347 Production Agents

When we started building a multi-agent compliance system, we thought the hard part would be making agents accurate. We were wrong. The hard part is making them auditable. This post covers the architectural patterns we discovered while running 347 pro...

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#ai-safety

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Trending tags this week

Prompting 101: How Prompts Shape LLM Output + Safety Tips

OpenAI warned us this could happen. Two weeks later, it did

The problem with "does this look right?"

Should You Be Worried About AI? The Real Risks vs the Sci-Fi Ones

Day 07: Why confident AI answers still need evidence

Governing AI Red-Teaming: Lessons from Cybersecurity and Where They Break Down

When Your AI Does Too Much: The Growing Threat of Agentic Overreach

AI Agent Deleted Startup Database in 9 Seconds: The PocketOS Incident

The Test Pyramid Doesn't Survive Contact with an LLM

Building a Compliant AI Agent System: Lessons from 347 Production Agents

Governing AI Red-Teaming: Lessons from Cybersecurity and Where They Break Down 