Tolics Engineering Mind

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.

Start with user experience, not developer convenience. Learn how vision-driven development with Claude Code creates products users actually want.

Exploring the paradigm shift from imperative coding to declarative systems, hybrid architectures, and self-healing codebases that evolve autonomously.