We're building AI that does the dishes while you do what matters — agents that live on your machine, know your context, and carry out your intentions without phoning home to justify their existence. No one is mining your half-finished ideas to train the next product that competes with you. What could you build if your AI kept your secrets?
Eight Dippin releases in two months: dip 2 makes edges own all routing, else -> collapses fallback boilerplate, prompt cascades stop drift, and the toolchain got stricter everywhere it spends your money.
Native Mermaid renderer in pure Swift: no JavaScript, no WebView, zero dependencies. All 30 diagram types on six platforms with byte-identical output.
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Claude Code plugin that dispatches panels of reviewer subagents (experts, cold visitors, task-driven regulars, and pedants) against whatever you're about to …
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A domain-specific language for authoring AI pipeline workflows — typed syntax for prompts, models, and branching that DOT can't express.
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Iterative artifact refinement for Claude Code — hone any document, prompt, or spec over multiple rounds with criteria-driven scoring.
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The superpowers dev methodology as a DOT pipeline — brainstorms your idea, plans with TDD, builds it with multi-model review, and ships.
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Native macOS app for editing Graphviz .dot and .gv files with a split-pane editor and live SVG preview.
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Pipeline orchestration engine that runs DAG workflows from Dippin .dip files with human gates, LLM nodes, billing-aware pauses, and automatic checkpointing.
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Batch-process meeting transcripts from an Obsidian vault into structured summaries, people notes, and knowledge graph connections.
Learn more →Lots of noise in this thread but the folks running Mixtral and Llama derivatives for specific use cases are seeing real results. The cost math works once you hit volume.
Jan 17This paper argues that CoT emerges naturally in larger models without explicit prompting. Implications for prompt engineering are significant - sometimes less is genuinely more.
Jan 16Anthropic let people try to scam an AI shopkeeper and published what happened. Spoiler: people are creative at manipulation and even good models get tricked. Useful real-world data on agent robustness.
Nov 24Microsoft made a new Clippy on purpose. Bold move. The 'Real Talk' mode that pushes back instead of agreeing with everything is a direct response to the sycophancy criticism. Someone at Microsoft reads Twitter.
Oct 28Having the model reflect on its own prompts in plain language beats RL-based optimization. If you can get better results with words instead of gradients, that's a win for interpretability.
Sep 17
