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Everyone’s talking. We’re building. - No overpromising - No endless meetings - No stealth mode At Codestam, we launch fast, ship real, and let the product speak. Need a team that moves smart + builds real? Let’s skip the talk. Let’s build.

AI isn't the future. It's shipping now. At Codestam, we're not building demos. We're building agents, automations, and systems that run in the wild and deliver results. Real-world AI. Built by builders. For builders.

Daylight powers the screens. Midnights power the breakthroughs. At Codestam, we don’t just write code. We weaponize it. AI agents. Automations. Systems that scale. This isn’t an office. It’s ignition. Not just a workspace. A launchpad.

Understanding the Evolution of AI: From Generative to Agentic Intelligence As AI continues to transform industries, it’s crucial to understand the distinct layers in its evolution: 1. Generative AI At its core, Generative AI (like ChatGPT or Midjou

I remember being 20, eyes shining with curiosity, heart set on building cool apps but lost in a sea of tutorials, languages, frameworks, and endless YouTube courses “I thought the secret was to learn everything” It wasn’t full article : https://medi

Google DeepMind’s CaMeL: A Breakthrough in Stopping AI’s "Prompt Injection" Problem? For years, prompt injection attacks (where hidden instructions trick AI models into bypassing safeguards) have haunted developers. Despite countless fixes, no solut

9 Steps to Build AI Agents from Scratch. I've given a simple step by step explanation. 𝗦𝘁𝗲𝗽 1: 𝗘𝘀𝘁𝗮𝗯𝗹𝗶𝘀𝗵 𝗠𝗶𝘀𝘀𝗶𝗼𝗻 & 𝗥𝗼𝗹𝗲 • Decide what problem the agent will solve. • Figure out who will use it. • Plan how users will interact

Everyone’s suddenly a “Prompt Engineer.” Strip away the fancy titles, the courses, the jargon… and it’s the same thing humans have struggled with for decades: Communicating clearly. Prompt engineering is basically: Say what you want. Say it precise

Simple breakdown of different elements in AI systems today. Extremely easy to understand. Here’s more: 𝗟𝗟𝗠𝘀 → Great at text generation and reasoning, but limited to training data. 𝗥𝗔𝗚 (𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹-𝗔𝘂𝗴𝗺𝗲𝗻𝘁𝗲𝗱 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼