Tolics Engineering Mind

In hybrid AI organisations, developers aren't above the stack — they're stuck in between it, relaying intent like middle managers in a bloated org.

The agentic AI loop wasn't born in 2024. It was shipped from a Melbourne lab in 1991 — the BDI architecture — inspired by a Stanford philosopher's 1987 book.

Fifteen core AI concepts — from machine learning to agentic AI — each defined in a single sentence, ordered to build on each other into a mental model.

A Malmö carpark, a Melbourne blackout, and the cheerful realisation that systems — not luck or geography — quietly decide what does and doesn't get built.

SUMO tried to encode all of reality into first-order logic. Its directory listing is a philosophical argument most AI engineers have never encountered.

The real bottleneck in software development is not knowledge — it is processing. Ambiguity, cognitive load, and feedback latency are the upstream causes.

Dark factories are coming to software. The shift from artifact-centric correctness to scenario-driven validation changes what you build and maintain.

A 2025 study found Polish outperforms English in long-context LLM tasks. Ukrainian grammar instincts explain why — and how anyone can prompt better.

How RLHF trains models to seek clarification instead of guessing — and a four-agent pipeline that brings the same discipline to your own requirements.

Most teams have no idea if their AI workflow investments are paying off. Here's what to actually measure instead of relying on vibes and excitement.

Context engineering — not prompt engineering — is where the real leverage lives. The discipline of deciding what goes into the context window, and why.

Your default environment shapes your baseline. Living near nature and visiting the city beats the reverse — your normal state should be the one that restores you.