The four places an autonomous agent gets attacked (prompt, tools, memory, and the planning loop) and how to lock down a WordPress and PHP backend with least privilege, schema validation, and reasoning logs.
Manual performance tuning is mostly hypothesis and hope. Agentic loops like pi-autoresearch take a metric and a budget, run the experiments themselves, and keep only the versions that measure better.
Plugging in the OpenAI API is not engineering. Notes on what actually matters when you build LLM features on WordPress: token costs, attention limits, RAG over fine-tuning, and keeping a 30-second API call from taking down PHP-FPM.
Beau Lebens talked about agentic commerce at Stripe Sessions, where AI agents do the shopping. My take on the hard parts: live inventory data, checkout security for bots, and what MCP and the Abilities API actually change.
The data science job has moved. Production AI in 2026 is mostly orchestration: async APIs, vector databases and cost per request. Here is what changes when you start working as an AI architect instead.
LLM summarization pipelines invent facts when the schema demands a value the transcript cannot support. A three-stage design, extraction then synthesis then an audit stage that can only weaken claims, and why empty sections are correct.
Why scenario modelling is mostly about calibrated uncertainty rather than clean predictions, using an English local elections case study and a small PHP class for bootstrapping residuals.
A 2021 vector quantization algorithm called EDEN still outperforms its 2026 successor TurboQuant, and the reason comes down to how each one handles the scale parameter S.
The CSPNet architecture splits feature maps so a lighter CNN does not cost you accuracy. What it fixes in DenseNet, how the two paths work, and the PyTorch code for the bottleneck block.
RAG re-derives everything on every query, so nothing accumulates. This is the Raw and Wiki folder layout, the three control files, and the daily, weekly and monthly jobs I use to keep an AI context layer my agents can read.