Recently, I came across a brilliant idea. I don't need smarter models. I just need more context, faster speeds, and lower costs. This concept is genius. Essentially, I want to be able to run Opus 4.5 with the same speed and price as Grok Code 1.

A real driver isn’t a real driver unless they personally designed and built their own car from raw ore—smelting the steel, forging the engine block, wiring the electronics, and hand-stitching the seats. The absolute most basic part of driving is building the vehicle itself. If

So much pain in the IT sector...

I had been using Claude Opus 4.5 for two weeks and it had proven to be a reliable model for coding. However, when I resumed using Gemini 3.0, I was pleasantly surprised by its performance. It excelled in context gathering and understanding the coding aspect, although its code

I believe OpenAI is in serious trouble. The recent releases—like the agent features in Codex, the teacher's edition, and the Atlas browser—seem to be more about hype than substance. The demos look impressive, but in practice, they fall short. Meanwhile, other companies are

Why doesn’t XAi have useful tools for better integration with IDEs, such as VS Code? 🧐

Since I am working with cyclic invoices, it requires a strong understanding of the tax system and the description of invoices. I believe that providing invoices in English will make the process easier, given the extensive training data available for the model. By the way, I am

Recently, I have been working on an invoice AI processing application. The most impactful aspect was having well-structured and clearly defined model instructions. It was not about the models or AI pipelines, but rather a well-refined prompt.

What is this mysterious model?

Every month, I send invoices to my accountant and track them in a Google Sheet. Then I wait for confirmation that everything's processed, and go back to mark them all as done. It's not a huge task since I don't have many invoices, but it's repetitive and kind of boring. Perfect

F..K!!!

The output

Built a self-healing AI workflow with https://t.co/zFM5VeDHbq 🚀 The Setup: Ask it anything like "What is the sum of all numbers from 1 to 10?" and watch 5 specialized AI agents collaborate through a graph-based workflow The Flow: 🔍 Analyst Agent - breaks down the query into

Our newest AI Agents for Beginners course is here. Learn how to build prod-ready AI agents using the Microsoft Agent Framework (MAF) — plus how it stacks up against Semantic Kernel and AutoGen. You’ll walk away ready to build with MAF (with code samples!), apply it to your own

Why this works: The AgentThread remembers everything: ✅ What tools were called ✅ What they returned ✅ The entire conversation So the second agent can properly format it! ⚠️ Note: There's AgentRunOptions you can pass during RunAsync, but right now it's just an empty

Here's how it looks in code: 1. agentWithTools - does the calculation 2. formattingAgent- does the formatting

I tried multiple workarounds: 1️⃣ Created a format_response plugin tool 2️⃣ Used JSON Mode (less strict, unreliable) 3️⃣ Tried prompt engineering tricks None felt production-ready 😕 Then I thought: what if I use TWO agents? 🎯 Step 1: First agent with Tools → executes

These days, I found something frustrating 😤 Turns out Structured Outputs (json_schema) and Tools (function calling) don't work together in the same OpenAI request! Actually, this is critical if you need to create agents with more logic just for the sake of a demo. Spent way

🔥 Tool calling with https://t.co/zFM5VeDHbq is incredibly powerful! Here's how to build an AI agent that validates AND executes C# code automatically: ## Step 1: Define Your Tools 🛠️ ## Step 2: Register Tools with Agent 🤖 ## Step 3: Let the Agent Work Its Magic ✨ **Key

🔄 Next Steps: Building a complete workflow that connects all agents: → Query Analyst parses user requests → Developer Agent generates code → QA Agent validates & tests → Automated feedback loops From individual agents to autonomous pipeline! 🚀 Full Source Code: