Automating deep learning experiments with agentic AI
A practical way to stop babysitting deep learning runs: containerize your training script, add a health-check sidecar, and let an agent handle restarts and hyperparameter tweaks.
Tag: Agentic Commerce
Algorithmic price-fixing and your WooCommerce pricing bot
Research on 13 LLMs in simulated markets found the agents holding price floors nobody asked them to hold. For a WooCommerce store running an AI pricing plugin that is an antitrust problem, and the fix sits in how the pricing logic is written.
Commoditized AI software: why a donkey herd beats a unicorn
The SaaS moat is gone now that an agent can rebuild your product in an afternoon. Here is the case for a herd of small automated niche businesses over one unicorn, and the WordPress REST API and WP-CLI setup that makes running a dozen of them possible.
Agentic AI supply chain: why dashboards can’t find the delay
Dashboards tell you a delivery was late. They do not say which team caused it. This post covers the MCP setup I use so Claude can read ERP, WMS and TMS timestamps and work out where the delay started.
Agentic AI anomaly detection instead of static thresholds
Static thresholds flag every promo spike and still miss the slow climbs. This post walks through a hybrid setup: Z-scores and growth rates to catch candidates, then a GroqCloud agent that decides whether to fix, keep or escalate each point.
Agentic AI UX patterns that keep users in control
Agentic AI features need more than a good prompt. These are the patterns I use to keep users in control: intent previews, an autonomy dial, an action audit log with a working undo, and escalation when the model is not confident.
Staying relevant as a senior analytics consultant in 2026
Agentic analytics moves the consultant’s job from writing queries to architecting the systems agents read from. What that looks like in practice, including a clean WordPress REST endpoint built for agent consumption.
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.
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.