#aiengineering

🤖 Ready to go deeper into AI Agents? Explore AI Engineer Agentic Track: The Complete Agent & MCP Course on Udemy. 🚀 Build real-world projects and explore OpenAI Agents SDK, CrewAI, LangGraph, AutoGen & MCP. 💻🔥 https://www.dolvee.com/2026/09/ai-agentic-track-mcp.html #AgenticAI #AIAgents #AIEngineering

🚀 Building Stoic — an AI Search & Answer Platform

Stoic is an AI-powered search and answer platform I’m building to turn documents, web content, images, and other information into useful, grounded answers. It uses RAG, embeddings, semantic search, and vector databases to retrieve relevant context before generating an answer. The backend is built with Python and FastAPI, with Supabase + pgvector for vector storage and similarity search. I’m also experimenting with LLM model routing, streaming responses, multimodal processing, and LLM-as-a-judge evaluation. The goal is to make AI search more reliable by focusing not only on generation, but also on retrieval quality and evaluation. I’m building Stoic as a hands-on learning project and continuously improving the architecture, performance, and user experience. If you're interested in AI engineering, RAG, LLMs, semantic search, or building AI products, I’d love to connect and hear your thoughts. 🤝

🔗 Try Stoic: https://stoic-app.vercel.app 💻 GitHub: https://github.com/Rakesh051204/cloud9-frontend

#AI #GenerativeAI #LLM #RAG #MachineLearning #AIEngineering #Python #BuildInPublic

I keep coming back to one idea: Every repository should carry its own memory. Git shows what changed, but not the decisions that never became code. A week later, a fresh agent can have the same bad idea again. Keep the Why puts that reasoning next to the code. https://keepthewhy.com #CodingAgents #AgentMemory #AIEngineering #OpenSource #SoftwareEngineering #DevTools #ContextEngineering #Git

Title: P6: Main principles of programming and AI Engineering. http s:/ /w ww.sei.cmu. edu/documents/582/2019_019_001_634648.pdf http s:/ /www.turingcollege .com/playbooks/ai-engineering-guidebook ⚰ #dailyreport #aiengineering #principles #aiprinciples #programming

Title: P3: Main principles of programming and AI Engineering.

SOLID "Interface Segregation Principle": (relevant now with AI) Such shrunken interfaces are also called role interfaces. ISP is intended to keep a system decoupled and thus easier to refactor.

Carnegie Mellon Institute:

1. Problem Suitability – Use AI only when needed, keep solutions simple. #dailyreport #aiengineering #principles #aiprinciples #programming

Title: P1: Main principles of programming and AI Engineering.

• Outcome-Oriented Principle - not model benchmarks, real impact.
• Clarity & Structure Principle - reliability
• Iterative Decomposition Principle - step-by-step for error reduction and modularity.
• Grounding-First Principle - Base answers on trusted external or retrieved sources
• Data Hygiene & Provenance - one bad source poisons results long-term #dailyreport #aiengineering #principles #aiprinciples #programming

Title: P2: Main principles of programming and AI Engineering.

• Red-Team & Adversarial Checks – Systematically
• Modular Composability - for upgrading independently
• Cost-Latency-Quality Trade-offs - route, cache, compress, and batch to control costs and meet SLAs.
• Observability & Traceability
• Human-in-the-Loop Feedback
• Ethical-by-Design - Guardrails from Day 0 #dailyreport #aiengineering #principles #aiprinciples #programming

Someone “cleaned up” the workaround. The code looked simpler. Then the production bug came back. That strange delay was not just ugly code. It carried knowledge: The upstream API could replay the same order unless the request was handled carefully. But the reason existed only in someone’s head. Keep the Why is an agent skill that captures this kind of rationale as a natural by-product of development and stores it as versioned Markdown inside the project. So before the next developer or agent removes the workaround, they can see: • why it exists • what was already tried • what could break • what must change before it can safely be removed Legacy does not begin when code gets old. It begins when the reason disappears. Free and open source: https://keepthewhy.com/ What “ugly” workaround in your codebase is actually carrying important knowledge? #OpenSource #AIEngineering #DeveloperTools #SoftwareEngineering #CodingAgents #ContextEngineering #TechnicalDebt #Documentation

I thought AI coding agents had a memory problem. The repository had a memory problem! A new agent session, another developer, or a different machine can all open the same codebase. They get the code, tests, and Git history. But they do not automatically inherit the conversations, rejected approaches, incident learnings, or constraints that shaped the implementation. Keep the Why is an agent skill that captures this reasoning as a natural by-product of development. It stores the relevant context as versioned Markdown inside the project, making it directly available to every developer and agent working with the same repository. So the understanding travels with the code - across sessions, developers, agents, and systems. Free and open source. One install command. About two minutes to set up. No runtime dependencies. No MCP server required. https://keepthewhy.com Do you consider a project portable if the code can be cloned, but its reasoning cannot? #OpenSource #AIEngineering

I have, twice now, been rejected from "AI Engineering" roles because the person interviewing me knew radically less about the technology than I do and was incapable of understanding my answer or even asking a question appropriate to the domain. #AI #AIEngineering

#aiengineering #aimistake #selftaught #learnaihttps://medium.com/@tradewithshrestha/the-hidden-reason-self-taught-data-scientists-are-failing-technical-interviews-in-2026-53f8e6199a0b

El lado del mal - AI Engineering Bootcamp: Basta de hacer tutoriales y construye tu propio asistente con IA en producción https://www.elladodelmal.com/2026/07/ai-engineering-bootcamp-basta-de-hacer.html #AIEngineering #BootCamp #AI #IA #InteligenciaArtificial #Ingenieria

#aiengineering #aiagent #aibestpractice #airisk While the shift toward ephemeral workloads and Kubernetes has already pushed infrastructure beyond the reach of perimeter security, agentic AI introduces an even deeper layer of complexity: unpredictability. https://www.infoworld.com/article/4190134/why-agentic-systems-need-microsegmentation.html

#aiengineering #airisk #feedbackloophttps://pub.towardsai.net/model-collapse-is-coming-for-ai-search-and-nobodys-talking-about-it-fb4348ebd54d