Artificial Intelligence (AI) is a rapidly evolving field that encompasses the development of algorithms and systems capable of performing tasks that typically require human intelligence. This includes problem-solving, understanding natural language, and learning from experience. As AI technology advances, various approaches such as role prompting and multi-agent systems are being explored to enhance the effectiveness and efficiency of AI applications. Role prompting allows AI to adopt specific personas, improving the relevance and quality of its outputs. Meanwhile, multi-agent systems enable collaboration among AI agents, leading to more sophisticated problem-solving capabilities and innovative solutions across diverse domains.

A Guide to Async Patterns in API Design

 ByteByteGo Newsletter

In this article, we will look at each of these patterns in detail, along with their advantages.

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The Model Is Not Your Product. The Harness Is.

 Towards AI

Harness engineering, and why it is becoming the most underrated skill in tech. Two teams. Same problem. Same model. Same Anthropic or OpenAI API key. Same documentation. The same internet full of tut...

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Mastering CLAUDE.md: 10 Proven Ways to Reduce Claude Code Drift

 Towards AI

Why Claude Code guesses instead of executes and how to turn a single markdown file into a deterministic behavioral contract. Continue reading on Towards AI

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Vibe Coders are Doing You a Favor

 Towards AI

Everyone is complaining about them. You should be taking notes. Continue reading on Towards AI

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Quiz: Context Managers and Using Python's with Statement

 Real Python

Check what you know about Python's with statement and context managers, from built-ins like open() and threading.Lock to writing your own.

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Role Prompting: How to Assign Personas to Get Expert Results — Prompt to Profit · Day 3 of 30

 Towards AI

Imagine having a world-class copywriter, a seasoned CFO, a veteran therapist, and a razor-sharp strategist all on speed dial — available any time, for any project, at no extra cost. That’s not a fanta...

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How to Build a Multi-Agent Research Assistant in Python

 MachineLearningMastery.com

I have been experimenting with the OpenAI Agents SDK, and it has quickly become one of my favorite ways to build agentic AI applications.

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The Sequence Opinion #864: Every AI Agent Needs a Computer

 TheSequence

The raise of agentic sandboxes.

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I Tested antirez's ds4 on 18 Tasks — His One-File C Engine Runs a 284B Model on a MacBook and…

 Towards AI

For the last week I have been running a 284-billion-parameter model on a laptop. Continue reading on Towards AI

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Google I/O 2026:Antigravity CLI and Flash 3.5 — Hype or Reality

 Towards AI

I upgraded immediately to test the new multi-agent workflows. At first glance, it is a very nice model. Flash is surprisingly good at agentic coding. It is officially a lightweight model, but it compe...

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Modular System Prompts: How I Build Agents That Adapt to Every Session

 Towards AI

The dynamic system prompt isn’t a layer. It’s a compiler. And Anthropic’s own leaked code proves it. The Confession In Context Engineering: What I Changed in My Agents, I introduced the dynamic syste...

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Launching python-oracledb 4.0:

 Oracle Developers

Launching python-oracledb 4.0: Oracle Deep Data Security, Enhanced Message Queuing and Cloud Native Authentication support Another great release of python-oracledb supports your use of Python and Ora...

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