Blog
Agentjacking: The New Prompt-Injection Attack Hiding in Your Error Logs
A June 2026 disclosure shows attackers hiding prompt injection inside fake error reports — a source coding agents read constantly, automatically, and almost never review raw. Here's how agentjacking works and how to gate it.
Why Gemini 3.5 Pro Got Delayed: The Real Cost of Long-Horizon Agent Tasks
Sundar Pichai promised Gemini 3.5 Pro for June 2026. It slipped to July because enterprise testers flagged excessive token burn on long agentic tasks. Simply explained: why that's a genuinely hard engineering problem, and why delaying to fix it was the right call.
The Agent Leap: Why 73% of Workplaces Now Run AI Agents (Up From 34%)
Workplace AI adoption more than doubled in a year, from 34% to 73%. The interesting part isn't the stat — it's the gap between having adopted an agent and actually getting value from one.
Repo-Level AI Agents: How Coding Assistants Learned to Reason Across a Whole Codebase
Autocomplete finishes your line. A repo-level agent reads the project, follows the dependency trail, and edits five files that have never been open in the same tab. Simply explained: how that actually works, and why it isn't magic.
Your AI Agent Just Got Fired: Why Agentic AI Still Can't Handle Real Business
The demo worked perfectly. The agent browsed the web, sent emails, called APIs. Then you put it near an actual business process and it fell apart in under an hour. Here is why that keeps happening.
The Real Cost of AI Agents: Security, Prompt Injection, and Trust
Every component in your agent stack either spends trust or earns it. Once you see the attack surface through that lens, the defenses become obvious — and so do the gaps.
LangChain Cheatsheet: The Complete Reference
Every LangChain primitive — chains, prompts, memory, retrievers, agents, tools, and LCEL — with copy-paste examples in one scannable reference.
LangGraph Cheatsheet: The Complete Reference
Every LangGraph primitive — StateGraph, nodes, edges, conditional routing, memory, human-in-the-loop, and multi-agent patterns — with copy-paste examples in one scannable reference.
MCP Hit 97 Million Installs — Here's Why It's the TCP/IP of AI Agents
TCP/IP didn't win because it was the best protocol. It won because it became the layer everyone agreed to forget about. That's what MCP is doing — and 97 million installs is the 'debate is over' number.
From Prompt Engineer to Agent Architect: The Career Shift Happening Right Now
The job description changed. The title didn't. Here's the diff.
Terraform + MCP + AI Agents: The New Infrastructure Stack Nobody's Talking About
Three technologies you already use. One pattern nobody has named yet. Here is the stack that makes AI agents safe to run against real cloud infrastructure — and the one line you must not let the agent cross.
MCP and Agentic AI Have Crossed the Infrastructure Threshold
MCP has 97 million monthly SDK downloads, governance under the Linux Foundation, and first-class support from every major AI vendor. That is not a popular open-source project. That is infrastructure. Here is what that transition actually changes for developers building AI systems.
Agentic AI: The Next Big Shift
AI assistants answer questions. Agents complete missions. A deep dive into the architecture, failure modes, and production patterns behind the shift from single-shot LLM calls to autonomous multi-step systems.
Agent Reliability Blueprint: SLOs, Guardrails, and Human Override
A practical architecture for shipping autonomous AI agents safely in production, from SLOs and circuit breakers to escalation ladders.