Programming & AI Tips 💡
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Programming & AI: Tips 💡 Articles 📕 AI & LLMs 👾 Design, Architecture, Principles ✅ 🇳🇱 Contact: @MoienTajik
Ko'proq ko'rsatishMamlakat belgilanmaganTexnologiyalar & Aralashmalar2 784
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Programming & AI Tips 💡 (@programmingtip) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 46 630 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 2 784-o'rinni egallagan.
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Obunachilar
-3924 soatlar
-1567 kun
-43930 kun
Postlar arxiv
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.NET 11 performance work is landing across the stack 🔥
Microsoft published the running list of performance improvements headed for .NET 11. This is not one magic runtime switch. The work spans the runtime, JIT, libraries, and tooling paths that show up in normal application code.
Use the post as a migration checklist:
• Find code that is CPU-bound, allocation-heavy, or called per request.
• Run your benchmarks on the .NET 11 SDK, not a synthetic microbenchmark only.
• Check p50 and p99 latency, allocations, startup, and throughput separately.
The best upgrade wins are boring: existing C# gets faster with fewer code changes. But measure your service. A JIT win can disappear behind JSON, EF queries, network calls, or a container CPU limit.
[ Blog ] :
https://devblogs.microsoft.com/dotnet/performance-improvements-in-net-11/
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#dotnet #csharp #Performance #dotnet11
@ProgrammingTip
46 630
Make coding agents earn the green check 💡
Do not end an agent task with "implement this." End it with a command that can fail.
For a .NET repo, that might be
dotnet test, a focused test project, a formatter check, or a small reproduction script. Tell the agent which command to run, what output to inspect, and what it should do if the command fails.
A good task contract has three parts:
• Change: the files or behavior to update.
• Proof: the exact command or test case.
• Stop condition: what needs human review instead of another retry.
This also makes PR review faster. You get a diff plus evidence, not a confident paragraph saying the fix should work.
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#AI #dotnet #Testing
@ProgrammingTip46 630
GPT-6 Astra is OpenAI's new work model 🚀
OpenAI shipped GPT-6 Astra. They are calling it the next generation in intelligence for work.
Not a research teaser. A work model. Expect the name in agent stacks and coding tools.
Why you care:
✅ New flagship name to put on your eval harness
✅ Pitched for workplace tasks, not playground chat
✅ If you pin model ids in config, read this before you swap anything
Start with the official writeup. Then decide if your coding agents still belong on last week's snapshot. I would not change production on a blog title alone. Run your own traces.
[ Read More ] :
https://openai.com/index/gpt-6-astra-next-generation-work
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#AI #LLM #OpenAI
@ProgrammingTip
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Agents API is in public beta 🚀
OpenAI put the Agents API in public beta. Cloud agents with the Codex harness, managed sessions, tools, and either a hosted sandbox or one you bring yourself.
What shipped:
✅ Codex harness, not a chat-completions wrapper you have to babysit
✅ Managed sessions and tools in the API
✅ Hosted sandboxes, or bring your own
Public beta, so expect sharp edges. If you ship coding agents or anything that needs a real environment, this is the post to read. Not another model card. Call it if you are done stitching sessions, tools, and a VM by hand.
[ Read More ] :
https://openai.com/index/introducing-the-agents-api/
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#AI #LLM #Agents
@ProgrammingTip
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GPT-Live-1 is in the OpenAI API 🚀
OpenAI put GPT-Live-1 in the API. Out of preview. You can call it.
Same full-duplex voice ChatGPT already uses. It listens and talks at the same time, then hands reasoning and tools to a backend model or agent.
What shipped:
✅ Full-duplex voice sessions you can wire into an app
✅ Pair it with whatever backend model, tools, or agent you already run
✅ Built for interruption and overlap, not a turn-detector kludge
You keep your existing model for thinking. GPT-Live-1 is the ears and mouth.
If you ship voice agents, this is the post. Not the GPT-6 Astra work page.
[ Read More ] :
https://openai.com/index/introducing-gpt-live-1-in-the-api
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#AI #API #LLM
@ProgrammingTip
46 630
Anthropic just introduced Claude Fable 5 and Claude Mythos 5 🚀
The interesting part:
Fable 5 and Mythos 5 are basically the same underlying model, but with different access and safety layers.
✅ Claude Fable 5 is the version available for general users. Anthropic says it is their most capable generally available model so far, especially for:
• Software Engineering
• Long-running agentic tasks
• Vision-based work
• Knowledge work
• Scientific reasoning
• Long-context workflows
One example they shared is pretty wild:
Stripe tested it on a 50M-line Ruby codebase, and it completed a migration in one day that would normally take a team more than two months. 🤯
But because the model is much stronger, Anthropic is adding stricter safeguards.
For risky areas like cybersecurity, biology/chemistry, and model distillation, some requests will automatically fall back to Claude Opus 4.8 instead of Fable 5. ⚠️
Claude Mythos 5 is the restricted version, mainly for trusted Cyber defenders, infrastructure providers, and later selected biology researchers. It has some safeguards lifted depending on the access program.
Pricing is 💸:
• $10 / 1M input tokens
• $50 / 1M output tokens
[ Read More ] : https://www.anthropic.com/news/claude-fable-5-mythos-5
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#AI #Claude #LLM
@ProgrammingTip
46 630
Cursor agents can now control their own computers 👾
Cursor introduced cloud agents that can control their own computers (VMs) and build software end-to-end.
Instead of just generating code, agents can now:
✅ Run full dev environments in isolated cloud machines
✅ Test features, fix issues, and validate results
✅ Record videos / screenshots / logs as proof
✅ Create merge-ready PRs automatically
At Cursor, 30% of merged PRs are already created by these autonomous agents.
This changes the developer role:
👉 Less micro-coding, more direction, review, and decision-making.
The long-term vision is “self-driving codebases”: agents that ship features, manage rollouts, and monitor production. 🚀
[ Read More ] : https://cursor.com/blog/agent-computer-use
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#AI #Cursor
@ProgrammingTip
46 630
🚀 .NET 10 is here! 🔥
The successor to .NET 9 is now out — and it’s a Long-Term Support (LTS) release, supported for the next 3 years.
👉 [ Learn what’s new ] :
https://learn.microsoft.com/en-us/dotnet/core/whats-new/dotnet-10/overview
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#dotnet #csharp #aspnetcore #maui
@ProgrammingTip
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🚀 OpenAI just dropped Sora 2 — and it’s insane.
Every frame of the video you’ll see is fully generated by AI. No cameras, no actors, no sets. Just prompts → video!
〰️〰️〰️〰️〰️〰️
#AI #OpenAI #Sora
@ProgrammingTip
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Preparing for the .NET 10 GC 🔥
In .NET 9 DATAS (Dynamic Adaptation To Application Sizes) got enabled by default, but .NET 9 is not an LTS release, so for many people they will be getting DATAS for the first time when they upgrade to .NET 10.
What does “application size” mean exactly? This is the LDS (Live Data Size) from GC’s point of view, meaning that if we did the most aggressive GC possible, this is how much memory your application uses. Another way to look at it is this is your long lived data + whatever inflight data you have when a GC occurs.
The goal for DATAS is that you no longer need to do various configurations to try to achieve a heap size proportional to your application usage. The 2 main cases we target with DATAS are -
1) Bursty workloads running in memory constraint environments. DATAS aims to retract the heap size back when the application doesn’t require as much memory and grow it when the app requires more. This is especially important for apps running in containers with memory limits.
2) Small workloads using Server GC — for example, if someone wants to try out a small asp.net core app to see what the experience is like in .NET, DATAS aims provide a heap size much more inline with what the small app actually needs.
[ Article ] : https://maoni0.medium.com/preparing-for-the-net-10-gc-88718b261ef2
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#dotnet #gc
@ProgrammingTip
46 630
Announcing ChromeDevTools MCP! 🔥
Connect your AI coding agent to Chrome's powerful automation & debugging capabilities with ease.
Key features:
✅ Reliable automation: It can programmatically handle clicks, form fills, dialogs, and page navigation with ease.
✅ Performance insights: Go beyond simple audits. Instruct your agent to record a performance trace and extract actionable insights to optimize your web apps.
✅ Advanced debugging: Empower your AI to analyze network requests, list console messages, take screenshots, and even evaluate scripts in the browser context.
✅ Browser emulation: Easily test different conditions by emulating CPU slowdowns, network throttling, or various screen sizes.
Works well with modern web apps and believe this will unlock new workflows for automated testing, AI-driven debugging, and interactive web development.
[ Blog ] : https://developer.chrome.com/blog/chrome-devtools-mcp
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#AI #LLM #MCP
@ProgrammingTip
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GitHub MCP Registry: The fastest way to discover MCP Servers 🔝
If you’ve tried connecting AI agents to your development tools, you know the pain: MCP servers scattered across numerous registries, random repos, buried in community threads — making discovery slow and full of friction without a central place to go. Meanwhile, MCP server creators are worn out from publishing to multiple places and answering the same setup questions again and again.
The GitHub MCP Registry launches as your new home base for discovering MCP servers. Whether you’re building with GitHub Copilot, agents, or any AI tool that speaks MCP, this is the place to find what you need. With GitHub already home to most MCP servers, the MCP Registry makes them dramatically easier to discover, explore, and use — helping developers find the right tools faster and contribute to a more open, interoperable ecosystem. ✔️
[ GitHub MCP Registry ] : https://github.com/mcp
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#LLM #AI #MCP #GitHub
@ProgrammingTip
46 630
Jetbrains Grazie: AI writing companion for people in tech 🚀
If you spend more time writing documentation, commit messages, blog posts or support tickets than you’d like, JetBrains just launched something you’ll want to try: Grazie.
It’s an AI writing assistant built for people in tech, helping make all those non-code texts better, faster.
🔍 What Does Grazie Do?
• Instant proofreading (grammar, spelling, punctuation, style)
• Inline text completion
• Summarization
• Translation across several languages
• Rephrasing / tone correction / synonymization
• AI-Chat
🛠 Where It Works & Pricing
• Plugin for JetBrains IDEs
• Browser extension for Chromium-based browsers
• Google Docs, Sheets, Gmail
• GitHub
• Slack
• And many more ...
[ Download ] : https://www.jetbrains.com/grazie
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#AI #Jetbrains #GrammarAI
@ProgrammingTip
46 630
🖼 Gemini’s Nano Banana
Google just introduced Nano Banana, a new image-editing feature powered by Imagen 4. 🍌
🔹 Merge multiple photos seamlessly
🔹 Apply style & texture transfers
🔹 Edit backgrounds and objects with natural prompts
🔹 Generate high-quality visuals in seconds
Why it matters:
For developers and designers, Nano Banana is a fast way to prototype visuals, explore UI ideas, and experiment creatively without heavy tools.
You can use Nano Banana directly inside Gemini. 🚀
[ Read More ] : https://gemini.google/overview/image-generation
〰️〰️〰️〰️〰️〰️
#AI #Gemini #Google
@ProgrammingTip
46 630
The Hidden Cost of DateTime.Now in .NET 🕰
You're Using DateTime.Now — and It's Breaking Your Code … ❌
Let's be honest: We've all written this:
if (DateTime.Now > token.Expiry)
{
return Unauthorized();
}46 630
💡 Tip
Before expecting an LLM to handle a complex task, use this litmus test:
Could a human expert — who knows all relevant general knowledge by heart — complete the task in a single go without backtracking, editing, or note-taking?
If not, the prompt may exceed what’s reasonable for an LLM today.
📘 From Prompt Engineering for LLMs: The Art and Science of Building Large Language Model–Based Applications
〰️〰️〰️〰️〰️〰️
#AI #LLM #PromptEngineering
@ProgrammingTip
46 630
💡 Tip
Before expecting an LLM to handle a complex task, use this litmus test:
Could a human expert — who knows all relevant general knowledge by heart — complete the task in a single go without backtracking, editing, or note-taking?
If not, the prompt may exceed what’s reasonable for an LLM today.
📘 From Prompt Engineering for LLMs: The Art and Science of Building Large Language Model–Based Applications
〰️〰️〰️〰️〰️〰️
#AI #LLM #PromptEngineering
@ProgrammingTip
46 630
Cursor can now make to-do lists, search PRs, and queue messages 👾
[ Blog ] : https://cursor.com/changelog/1-2
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#AI #Agents #Cursor
@ProgrammingTip
46 630
How to use MCP in n8n to scale AI automation? 🤔
We break down exactly what n8n and MCP are and demonstrate why using them together is a game-changer for automating tasks that require AI interaction. Combining the flexibility of n8n's visual automation with the power of MCP (Model Context Protocol) allows you to build incredibly sophisticated, AI-driven processes.
This tutorial is your complete guide to setting up n8n and MCP on a secure and reliable Hostinger VPS.
In this video, you'll learn ✅:
• What n8n is and how it simplifies workflow automation
• What MCP is and why it's key for AI agents
• The benefits of using n8n and MCP together for standardized AI automation
• How to install n8n on a Hostinger VPS
• Setting up the MCP Server Trigger within your n8n instance
• Configuring MCP Client Tools for AI interaction
• Building a practical n8n workflow that utilizes MCP to connect to external services
• How to test and launch your new AI-powered workflow
💡 Use code PROGRAMMINGTIPS to get an extra 10% OFF your Hostinger VPS plan:
👉 https://www.hostg.xyz/SHHOl
📺 [ Watch the tutorial ] : https://www.youtube.com/watch?v=p5B1XHbe3lg
