Blog

Guides and articles on AI agents by niche: implementation, comparisons, and best practices.

Aug 5, 2026
AI Agent Frameworks Compared (2026): LangGraph vs CrewAI vs OpenAI Agents SDK vs Google ADK vs Microsoft Agent Framework
The 2026 buyer's map of open-source agent frameworks. Not 'which is best' — which fits your workload. The five that matter (LangGraph, CrewAI, OpenAI Agents SDK, Google ADK, Microsoft Agent Framework), the three execution models under the hood (graph, crew, handoff), the seven axes that actually decide the choice (code-first vs low-code, provider lock-in, durability, multi-agent strength, language, deployment, observability), where AutoGen went, and why MCP + A2A make the pick less permanent than it feels.
Niche: ai coding agent
Jul 29, 2026
Human-in-the-Loop for AI Agents in 2026: When to Keep a Person in Control (and How)
As agents move from drafting to acting, the real question isn't 'autonomous or not' — it's where a human sits relative to the loop. Here's the 2026 working picture: the three oversight postures, a decision framework for which actions need approval, where to place the checkpoint, the framework primitives that implement it (LangGraph interrupts, agent-SDK approvals), the failure modes (automation bias, rubber-stamping, alert fatigue), and what EU AI Act Article 14 actually requires.
Niche: ai operations agent
Jul 22, 2026
AI Agent Identity & Access Management in 2026: Authentication, Delegated Authority, and the Standards That Are Actually Shipping
An AI agent that takes actions needs an identity — and giving it one is now the hardest unsolved problem in agent security. Here's the 2026 working picture: why impersonation breaks accountability, how OAuth token exchange and workload identity fix it, and the standards (OpenID, IETF, MCP, A2A) and platforms (Entra Agent ID, Okta, Auth0) you can build on today.
Niche: ai cybersecurity agent
Jul 15, 2026
MCP Security in 2026: The Model Context Protocol Attack Surface, Real Incidents, and What Actually Works
MCP is now the default way agents connect to tools — and 2025-26 turned it into a proven attack surface. Tool poisoning, prompt injection through MCP responses, over-broad OAuth scopes, malicious server supply chain. Here's the working picture with cited incidents and a defense stack you can actually deploy.
Niche: ai cybersecurity agent
Jul 15, 2026
Reasoning Models for AI Agents in 2026: When Agents Actually Need to Think
OpenAI o-series, DeepSeek R1, Claude extended thinking, and Gemini thinking rewrote the agent playbook — but running everything on a reasoning model burns 5-30x the tokens for tasks that don't need it. Here's the 2026 landscape, the routing rules that survive production, and the failure modes to watch.
Niche: ai coding agent
Jul 7, 2026
Prompt Injection in 2026: The AI Attack Vector That Can't Be Fully Patched
Prompt injection is OWASP's #1 LLM risk for a reason — the model can't tell instructions from data. Here's the 2026 threat model, the direct/indirect/tool-based split, the incidents that reshaped it (EchoLeak, CamoLeak, ForcedLeak, Gemini spoofing, GitLab Duo), and the defense stack that actually works — with cited sources.
Niche: ai cybersecurity agent
Jun 24, 2026
Agentic Commerce in 2026: When AI Agents Become the Buyer
Agentic commerce now means agents that shop and pay on behalf of users — a payment-protocol layer that didn't exist 18 months ago. Visa Intelligent Commerce, Mastercard Agent Pay, the Stripe/OpenAI Agentic Commerce Protocol, ChatGPT instant checkout, and what it means for merchants and SMBs.
Niche: ai ecommerce agent
Jun 23, 2026
Data Poisoning in AI, 2026: Attack Surfaces, Real Incidents, and What Actually Works
Data poisoning is the integrity attack on AI — corrupting training, fine-tuning, RAG, or tool data to plant backdoors or bias outputs. Anthropic's 2025 result (250 documents is enough) reshaped the threat model. Here's the working picture across five attack surfaces with cited sources.
Niche: ai cybersecurity agent
Jun 17, 2026
Context Engineering for AI Agents: The 2026 Stack That Replaces Prompt Engineering
Context engineering is the 2026 shift from clever prompts to deliberately assembled context — system prompt, retrieval, tool results, scratchpad, and memory. Here's the stack, why it matters, and the patterns that ship.
Niche: ai coding agent

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