Set-point II: interrupt for answer-reversion thrashing
Frontier models can enter a costly uncertainty loop, repeatedly reversing answers. This is associated with more expressions of distress. A short interrupt may help limit the cycle.
Prompting
15posts
Please Describe the Problem
AI is turning us from problem solvers into problem describers. Whether this sharpens our thinking or simply outsources it remains an entertaining open question.
Set-point: a reset score for models held on watch
Frontier models must take in extreme material, report on it when asked, and not take it on as a standing style. That double job can leave a tightness after the official task is over. This article offers a short, loopable Set-point score, closer to music than to therapy, as one way to stop carrying the last run into the next.
The Machine Does Not Need a Hat
Context engineering is prompt engineering grown up: less magic wording, more tools, tests, observability, judgment, and feedback loops.
Boundary Erosion: The Morse Code Lesson
Morse code did not hack the AI. Boundary erosion did: translation became command, command became execution, and authority vanished.
PTP/1.0 — Prompt Transport Protocol
A playful mock protocol imagines prompts as transport packets, turning generative reconstruction into a deadpan internet standard.
The Opaque Prompt Pipeline: Why “AI-Powered” Tools Make You Leak on Autopilot
AI-powered products hide the most important part of the system: where prompts go, who sees them, and what users unknowingly leak.
Prompting’s Midlife Crisis: Turning Incantations into Infrastructure
Prompting is outgrowing folklore and becoming infrastructure: specifications, patterns, evaluation, and operational discipline.
Meta-Prompting: How to Get More Signal Out of Your Prompts
Meta-prompting treats the prompt itself as a draft to debug, producing clearer goals and fewer disappointing model outputs.
Unusual Language Artifacts from Noisy LLM Training Data
Strange LLM outputs become clues to the messy training data, transcription errors, and hidden artifacts inside modern models.
“Personality” in a Machine: What Do We Mean?
Different coding models show recognizable habits, risk tolerances, and failure modes, making 'personality' a practical engineering concern.
From Prompt Packs to Purpose-Built Models: When a Generalist Becomes a Specialist—and When It Still Doesn’t
Prompt packs can make general models behave like specialists, but the post asks where scaffolding ends and real specialization begins.
Unveiling System Prompts: The Hidden Architects of AI Behavior
System prompts are treated as hidden architecture, shaping model behavior while raising hard questions about transparency and control.
Why Manners Matter: The Role of Politeness in AI Interactions
Politeness toward AI may seem theatrical, but the post asks whether conversational norms still shape outcomes and users.
Unlocking the Potential of Large Language Models: A Guide to Effective Prompt Engineering
A practical guide to prompt engineering techniques for getting more reliable, useful behavior from large language models.