Agentic coding: how I debug WordPress sites now
A three-step way to point an agent at a broken WordPress site: let it read debug.log, make it write a hook-level plan before it edits anything, then iterate on what it ships.
Tag: Agentic Commerce
Why I let my agentic architecture write its own tools
Pre-built agent toolboxes break the moment a client asks something you did not plan for. Here is the plan-code-execute setup I use instead, where the agent writes its own Python, plus the hallucinated CSV that taught me why the analyst step is mandatory.
Multi-agent systems scaling: more agents is not the fix
Adding agents to a weak system mostly adds noise. Notes on DeepMind’s scaling paper: the 17.2x error amplification in uncoordinated swarms, where the four-agent plateau shows up, and the archetypes and centralized orchestrator I use instead.
Few-shot prompting for WordPress code you can ship
Zero-shot prompts make the model guess your coding standards. Feeding it two or three working examples from your own code gets output that matches your prefixes, namespaces and security patterns.
Context engineering beats writing longer prompts
Prompting stops scaling as soon as a task has real edge cases. Here is what the Stanford ACE research found about its generator, reflector and curator loop, where the gains show up, where they do not, and how to keep the same kind of playbook in WordPress.
Your agent picks the wrong tool because of your MCP schema
Agents pick the tool with the longer description, not the right one. What that length bias looks like in a WooCommerce integration, how to keep internal arguments out of the prompt, and why a proxy beats editing someone else’s MCP server.
Agentic AI workflows that survive a failed API call
A client’s research pipeline kept hallucinating specs until we stopped writing one giant prompt. Notes on using IntelliNode’s VibeFlow to compile intent into a task graph, plus the code we run in production.
Why I moved a client’s agent to the NeMo Agent Toolkit
A client’s weekend-built AI agent fell apart the moment real users touched it. Here is what the NeMo Agent Toolkit handled for us that my own custom wrapper could not: YAML config, grounded tools, and a server you get for free.
Effective AI programming is a context problem
An AI coding agent invented table names on a 50k SKU WooCommerce sync until I wrote the schema down for it. Here are the context files I now keep in every project, and why decisions made in meetings need to end up in the repo too.
Agentic AI gives you a dot, not an ROC curve
A health-tech client had 99.8% accuracy on a disease that shows up in 0.2% of patients. Their agent said no to everyone. Here is how I pulled a continuous risk score out of a binary agent so the AUC comparison against their XGBoost model meant something.