AI/ML Resources

ARC: The Architecture for Reasoning Control

AI apps fail from compounding randomness. Start small, add layered guardrails, and use AI for reasoning but code for execution to keep systems reliable.

May 6, 2026

by Ananth Iyer

· 2,009 Views

Designing Agentic Systems Like Distributed Systems

Agentic systems behave like distributed systems - unpredictable and failure-prone, requiring orchestration, contracts, and strong observability.

May 6, 2026

by Satyam Nikhra

· 2,298 Views

The Hidden Failure Modes of AI Systems (That Traditional Monitoring Misses)

AI systems rarely fail loudly — they degrade silently via drift, bad retrieval, and hallucinations. Detect it with semantic observability, not just infra metrics.

May 6, 2026

by Sayali Patil

· 3,937 Views · 5 Likes

Top JavaScript/TypeScript Gen AI Frameworks for 2026

A practical, in-depth comparison of the top generative AI frameworks in 2026, coming from someone who has built with all of them.

May 6, 2026

by Xavier Portilla Edo

CORE

· 2,661 Views · 2 Likes

Cost-Aware Routing for RAG: Fetch Less, Spend Less, Answer Better

Every query hits the same retrieval depth — whether it needs 0 passages or 10. Here is what that mistake costs, and how cost-aware routing fixes it.

May 6, 2026

by Sanjay Mishra

· 1,476 Views

The Rise of AI Orchestrators

A reusable multi-agent QA framework where specialist agents debate, a judge decides, and software testing becomes an AI-orchestrated lifecycle.

May 6, 2026

by Oleksandr Kryvchenko

· 3,264 Views · 2 Likes

AI in Software Engineering: 3 Critical Mistakes to Avoid (and What to Do Instead)

Learn the mistakes developers make and how to avoid them. Use AI to accelerate development without sacrificing code quality, architecture, and long-term maintainability.

May 6, 2026

by Otavio Santana

CORE

· 1,456 Views

Security in the Age of MCP: Preventing "Hallucinated Privilege"

Prevent prompt injection in AI agents: default to read-only, require human approval for changes, and authenticate every tool call with end-user zero-trust permissions.

May 6, 2026

by Nikita Kothari

· 2,137 Views

Beyond Conversation: Mastering Context with Claude Code Skills and Agents

Stop "talking" to LLMs and start engineering context flows. The shift from chatbot to system component requires moving from monolithic prompts to modular agentic skills.

May 5, 2026

by Ioan Tinca

· 4,872 Views · 4 Likes

Engineering LLMOps: Building Robust CI/CD Pipelines for LLM Applications on Google Cloud

Master LLMOps on GCP by automating prompt evaluation, model deployment, and monitoring with Cloud Build and Vertex AI for robust AI apps.

May 5, 2026

by Jubin Abhishek Soni

CORE

· 1,869 Views

Beyond n8n for Workflow Automation: Agent Graphs as Your Universal Agent Harness

Agent graphs let you visualize multi-agent workflows in LaunchDarkly, monitor node performance, and fix slow agents without redeploying.

May 5, 2026

by Scarlett Attensil

· 1,606 Views · 1 Like

Setting Up Claude Code With Ollama: A Guide

Claude Code is a terminal-based AI coding assistant by Anthropic that can integrate with Ollama for local model inference.

May 5, 2026

by Gunter Rotsaert

CORE

· 3,033 Views · 3 Likes

AI in Software Architecture: Hype, Reality, and the Engineer’s Role

AI won’t replace engineers—it shifts their role. It boosts speed but adds complexity, debt, and review cost. Advantage goes to those who use it critically.

May 5, 2026

by Otavio Santana

CORE

· 2,013 Views · 1 Like

AI Didn't Replace Seniors; It Just Made Them the Bottleneck

The code generation era shipped a paradox: faster output, slower understanding, and a talent pipeline headed for collapse.

May 5, 2026

by Abgar Simonean

· 2,282 Views · 2 Likes

AgentOps: The Next Evolution of DevOps for AI-Driven Systems

Explore AgentOps, the next evolution of DevOps for AI systems, enabling scalable, observable, and safe deployment of autonomous AI agents.

May 4, 2026

by Dennis Helfer

· 1,886 Views

Integrating AI-Driven Decision-Making in Agile Frameworks: A Deep Dive into Real-World Applications and Challenges

AI + Agile boosts workflows via adaptability, retrospectives, and automation. Biggest gains come with human oversight, despite skills gaps and lack of standards.

May 4, 2026

by Abhijit Roy

· 2,258 Views · 2 Likes

Understanding MCP Architecture: LLM + API vs Model Context Protocol

PDF chatbot demo comparing LLM+API vs MCP: direct calls are simple for one app; MCP adds a server layer for tool discovery, reuse, and standardization.

May 1, 2026

by Sanjay Mishra

· 4,638 Views · 3 Likes

Designing a Production-Grade Multi-Agent LLM Architecture for Structured Data Extraction

Find out how a multi-agent LLM system overcomes the unreliability of single-LLM extraction when processing large volumes of documents for structured data.

May 1, 2026

by Haricharan Shivram Suresh Chandra Kumar

· 2,643 Views

From SDLC to ADLC in AI

AI development breaks traditional SDLC rules. Learn why ADLC, outcome-driven iteration, and continuous feedback are key to scaling AI in enterprises.

May 1, 2026

by Adam Mattis

· 1,984 Views

How AI Is Transforming Software Engineering and How Developers Can Take Advantage

AI is transforming software development by increasing speed, but developers still provide the judgment needed to build good software.

April 30, 2026

by Satyam Nikhra

· 2,202 Views

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