Posts tagged "architecture"
Planning agents for the future: what a platform needs to run them over time
Run logs, a short morning report, a supervising review agent, a release window with veto and four-eyes publishing: what a platform needs for agents, and what exists.
Does a classifier model always make sense? Deciding what an agent may do
Classifier models can route requests and judge agent actions, but they cost money and make mistakes. When rules are better, when a classifier helps, and how autonomy levels fit.
An architecture review for agent systems in one page
An AI architecture review template for agents on one page: purpose, boundaries, data flow, contracts, autonomy and failure paths, with questions for each.
Structured output for agents: schemas, contracts and ownership
Structured output agents hand over typed data, not free text. Define JSON schemas for tool results and outputs, version them and name an owner per contract.
Workflows or agents? Choosing how much autonomy a step needs
Workflows vs agents is a per-step choice: fixed code paths are cheaper and easier to govern, loops are flexible. Pick the least autonomy that works.
Draw the data flow before you write the first prompt
An agent data flow diagram shows where untrusted data enters, where private data lives and where anything leaves. One-page template for trifecta risks.
Handovers are contracts: designing the seams between agents
An agent handover is where multi-agent systems break. Treat each one as a typed contract with an owner, a schema and an acceptance check, not a prompt.
One MCP server per system: MCP server design you can govern
MCP server design rules for governable agents. One small server per system, namespaced tools, and read/write separation instead of one giant gateway.
Architecture before prompts: why the foundation decides everything
AI agent architecture sets boundaries, contracts, handovers and data flows before any prompt runs. Why most production failures trace to a missing boundary.
What is the Model Context Protocol? A plain explanation for platform teams
What is MCP? The Model Context Protocol standardises how an agent host finds and calls tools, resources and prompts on servers. Plain guide for platform teams
Tool, skill or prompt? Three ways to give an agent what it needs
Agent skills vs tools vs prompts: a tool acts, a skill packages know-how loaded on demand, a prompt is standing text. Includes a decision table.
Agent architecture is not application architecture: the agentix pattern
Application architecture structures code. Agent architecture decides who may do what at run time. The agentix pattern - one MCP server per system, one agent per step - is our answer.
What is an agent harness, and why do harnesses keep shrinking?
An agent harness is the loop and scaffolding around a model. As models improve, much of it moves into the model or the API. What stays is governance, and that is why open-agentix treats the harness as replaceable.
Cost is a platform concern: budgets, per-agent and per-tenant attribution, export
Agent systems can fail financially while working technically. open-agentix prices every step, attributes it to tenant, agent and use case, stops runs at their budget and exports the lines.
Least privilege for agents: decomposition instead of one all-powerful agent
One agent with read and write access to everything is a large blast radius. open-agentix splits a process into small agents that each hold only the tools one step needs.
Why I share my AI projects as OpenAgentix
OpenAgentix is my personal, non-commercial collection of open-source AI projects, experiments and notes. Here is what belongs here and why I share it.