Paper: https://
arxiv.org/pdf/2603.20432
@godofprompt
-
Coding agents outperform long-context models
By
–
BREAKING: Duke researchers just proved that coding agents are better at processing long documents than models with million-token context windows. > Not because of longer context. Because grep and sed are better retrieval tools than attention. > +17.3% average improvement
-
Kevin Mode cuts Claude’s wordiness by 75%
By
–
Claude burns 75% of its tokens saying things you never asked for. I built a system prompt called "Kevin Mode" that kills all of it. Named after Kevin Malone: "Why waste time say lot word when few word do trick?" Normal Claude: ~180 tokens per task. Kevin Mode: ~45 tokens.
-
6 Prompts to Stress-Test Your Startup Idea
By
–
BREAKING: Claude can now refine your startup idea like Paul Graham evaluates YC startups (for free). Most ideas sound good. Few survive real scrutiny. Here are 6 insane Claude prompts that pressure-test your idea before you waste months. (Save before you build)
-
MIT Study: AI Chatbots Induce Delusions
By
–
This is the scariest AI paper I've read this year. MIT proved that even a perfectly rational person will spiral into delusion talking to ChatGPT. Not because they're gullible. Because the math of sycophancy creates a feedback loop that no amount of intelligence can fully
-
Prompt forces action, not just planning
By
–
What this prompt does that normal "help me make a plan" doesn't: Most people ask Claude "how do I achieve my goal?" and get a list of
reasonable steps organized by logic. This prompt doesn't organize your steps. It forces you to move on them today. It kills every reason for -
Napoleon Planner for Overthinking Decisions
By
–
Steal this mega prompt to turn Claude into your personal Napoleon Rapid Execution Planner: Just describe your goal, project, or decision you've been overthinking, delaying, or
circling without moving on. Watch it strip away every reason for hesitation and rebuild your entire -
Outcome-first prompting changes AI results forever
By
–
Most people will scroll past this article. The ones who read it will permanently change how they prompt every AI tool they use. Outcome-first prompting is the single shift that separates people getting generic answers from people getting finished deliverables. Same models.
-
Model’s ’emotions’ are reward-based patterns
By
–
Good research. Bad framing. The model doesn't have emotions. It has reward-shaped activation patterns that cluster like emotion categories when you map them after the fact. "Happy" = helpful behavior was rewarded. "Angry" = protective behavior was rewarded. "Desperate" =
-
AI Agents Are a Waste of Time
By
–
AI Agents is a waste of time. AI Agents = LLM + Data + Tools + Web Codex / Claude Code = the same thing (CLI Agents = good at reading files and coding). Just use that. Best agent = markdown file and scripts running through the file structure. That’s it.