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AI Agents

Building Your First Agent: A Loop, Three Tools, One Guard

Skip the framework. An agent is a while loop over a tool-calling model. Here is the minimum that works, and the four things that break it first.

· 8 min read
AI Agents

Evaluating Agent Reliability: Past the Single Pass Rate

An agent that works four times in five is not 80 percent useful. Here is how to measure agent reliability in a way that predicts production behaviour.

· 10 min read
AI Agents

Human in the Loop: Designing Approval That Actually Works

Most approval gates fail not from too little oversight but from too much. Here is how to design agent checkpoints people actually read before clicking yes.

· 9 min read
AI Agents

Long-Running Agents: Durability, Compaction and Restarts

An agent running for hours hits limits a chat never does: context exhaustion, process restarts, stale state. The patterns that keep long jobs alive.

· 9 min read
AI Agents

MCP Explained: One Protocol Instead of N×M Integrations

The Model Context Protocol standardises how agents connect to tools and data. What it solves, how it works, and when a plain function call is enough.

· 8 min read
AI Agents

Multi-Agent Systems: When They Help and When They Hurt

Two credible teams published opposite advice on multi-agent architectures within a day of each other. Both were right, because the answer depends on the task.

· 9 min read
AI Agents

Prompt Engineering for Coding Agents Is Mostly Context Engineering

Clever phrasing barely moves the needle. What actually improves agent output is what you put in front of it, in what order, with what constraints.

· 8 min read
AI Agents

Prompt Injection: Why Your Agent Is a Confused Deputy

An agent that reads untrusted content can be instructed by it. The fix is not a better prompt — it is treating the model as an untrusted client.

· 8 min read
AI Agents

ReAct vs Plan-and-Execute: Two Ways to Run an Agent Loop

ReAct decides one step at a time. Plan-and-execute commits to a plan first. The choice changes cost, latency, recoverability and how failures look.

· 9 min read
AI Agents

Structured Outputs: Getting JSON You Can Actually Parse

Asking a model for JSON and hoping is a bug waiting to happen. Schema-enforced outputs, and the validation you still need around them.

· 7 min read
AI Agents

Subagents and Delegation: When Splitting an Agent Helps

Subagents buy parallelism and a clean context window, and cost you shared understanding. Here is when that trade is worth making, and when it is not.

· 9 min read
AI Agents

Tool Calling: The Feature That Turns a Model Into an Agent

Tool calling is how a model asks your code to do something. Understanding the handshake — and designing good tools — is most of what makes an agent reliable.

· 9 min read

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