Intel Feed

Perplexity trusts GPT-6 Astra with end-to-end systems

Perplexity uses Astra to write communications, change software, and monitor production systems, and checks in much less frequently than with earlier models.

Houthis Used Claude Code to Develop Missile Guidance Software: Anthropic

Chat GPT-6 Astra Prompting Masterclass

GPT-6 Astra is the most capable model OpenAI has ever shipped (for now atleast)Continue reading on Medium »

Prompt Engineering Is Losing the Battle: The Real Problem Is Context

When developers first start building features with Large Language Models (LLMs), the initial fix for every bad output is almost always the…Continue reading on Towards AI »

Testing 0% Interest Lending Against Tokenized Equities

A Beta Intelligence Challenge submission — Superteam EarnContinue reading on Medium »

I Built an Interactive Cat Demo with One Prompt Using GPT‑6 Astra

How a single creative brief became a cursor-following character, a mini-game, and a tiny petting interaction.Continue reading on Generative AI »

Vitest 5 Is Here — and Faster Tests Are Only Half the Story

Cleaner mock history, deliberate flakiness checks, and portable CI reports make this release worth a closer look.Continue reading on Generative AI »

Service Virtualization for Integration Tests: The Setup That Actually Works Long-Term

The availability problem and the accuracy problem look identical from the outside. A test suite that fails intermittently because an…Continue reading on Stackademic »

Why Your ChatGPT Prompts Are Failing and How to Fix Them Instantly

It’s not that the AI is broken. It’s just guessing what you want.Continue reading on Medium »

I Stopped Fearing Python’s Dynamic Typing, Then I Discovered Pydantic

How Pydantic helped me write cleaner, safer, and more maintainable Python code, especially in test automation.Continue reading on Medium »

The Most Used AI Prompts of 2026: An Original Data Report From 537 Templates

Real usage counts from a live prompt library, not a curated best of listContinue reading on Medium »

From Self-Healing to Self-Learning: What Should AI Learn From Every Test Execution?

AI in testing is getting better at reacting.Continue reading on Medium »

Deloitte USI: SDET-II QA Automation interview experience [2026]

Round-1 [Technical]Continue reading on Medium »

Prompt Engineering: It Looks Easy… Until You Need Reliable AI

You can ask an LLM a question in five seconds. But getting it to give you the right answer consistently is a completely different problem.Continue reading on Medium »

LLM Context Engineering: Structured Outputs, Tool Calling & AI Agents

Prerequisites: Prompt Engineering for LLMs: Zero-Shot, Few-Shot, Reasoning, Decomposition & ReActContinue reading on Medium »

Shift-Left Testing Sounds Great. Here’s What It Actually Requires

Shift-left isn’t about testing earlier. It’s about discovering risk earlier — before assumptions become code, defects, and production…Continue reading on Medium »

The Ultimate Blueprint for Prompt Engineering: How to Extract Executive-Level Outputs from AI (Even…

IntroductionContinue reading on Medium »

Your QA Team Is Not Slow. Your Testing Process Is Creating Bottlenecks

Your QA Team Is Not Slow. Your Testing Process Is Creating BottlenecksContinue reading on Medium »

How I Turn One AI Image Into a Reusable Visual Style

Sometimes I create an AI image that works better than I expected, but the thing I want to keep isn’t necessarily the subject.Continue reading on TandA AI Art Library »

Agentic AI in Software Testing: From Test Generation to Verified Execution

How QA teams can use AI agents to plan, execute, and maintain tests — while keeping quality decisions grounded in evidence.Continue reading on Medium »