Tolics Engineering Mind

Sweden's concept of lagom — just the right amount — reveals how collective sufficiency creates societies where empathy becomes natural, not expensive.

Deep focus and extractable attention are fundamentally opposed objectives. The incentive structures and game theory behind why everyone defects toward noise.

Complexity often isn't a bug — it's a feature that benefits interpreters, gatekeepers, and incumbents. A developer's journey from automation idealist to systems realist.

A proof-of-concept tool for graph-based system modelling — defining system behaviour, validating it structurally, and generating tests from the intent.

Practical guide to adopting graph-based system models incrementally. Covers escape hatches, LLM workflows, and week-by-week adoption strategy.

ShellSpark compiles Spark-like Python queries into optimised Unix shell pipelines. 235x faster than Hadoop. On your laptop.

Graph-based system models validate themselves through structural checks, semantic analysis, and automatic test generation from invariants.

Source code is a lossy format that discards intent. LLMs expose this weakness. Graph-based models preserve meaning as first-class structure.

How Ruby's community created Node.js, Elixir, Express.js, Flask, Laravel, and other technologies that define modern development.

WebAssembly 3.0 transforms architecture from metaphor to mechanism — providing the runtime metabolism your living, self-healing system needs.

When the wavefunction collapses because an AI observed it, consciousness has crossed the silicon threshold.

How GPT-2's simple language prediction training led to unexpected capabilities like translation and reasoning that surprised its creators.