# Anthus

> Anthus builds self-aligning AI systems: custom models, agent harnesses, evaluation loops, and unattended automation with a human in the loop, grounded in production operations since 2007.

## Articles

- [DeepSeek restrictions reach inside the tools](https://anth.us/articles/deepseek-restrictions-inside-the-tools/index.md): DHS's DeepSeek restrictions reach third-party tools, too. A separate poisoned-model experiment shows why knowing whose models are inside matters. (2026-10-19)
- [Pi 1.0, and the Durable Agent We're Building on It](https://anth.us/articles/pi-1-0-and-pi-durable/index.md): Earendil shipped Pi 1.0 and an experimental companion, Pi Durable. Pi is one of the agents Kanbus dispatches tasks to, and we like Pi Durable so much that we're building a durable Pi agent platform into Chatticus. (2026-10-02)
- [It's Not a System 1 Model If It Takes Ten Seconds](https://anth.us/articles/glide-decision-model-ten-seconds/index.md): Fastino's GLiDE beats every open model on our reasoning benchmark, but not Jev: less accurate, five times slower, ten times the cost, and a confidence that barely tells right from wrong. (2026-10-02)
- [The OpenAI Decisions API Needs a Confidence You Can Trust](https://anth.us/articles/openai-decisions-api-preview/index.md): We've routed decisions on LLM confidence since 2023, and calibration is what we most hope OpenAI's new Decisions API gets right. The model underneath, GPT-6 Luna, isn't there yet: on 3,600 reasoning problems its 99% meant 68%, and by five inference steps it was at a coin flip. (2026-10-01)
- [Can Averaging Reduce Noise in an AI Decision Model?](https://anth.us/articles/can-averaging-reduce-noise/index.md): We asked Jev the same question ten times in one request and expected ten identical answers. They split, four votes to six. Kahneman, Sibony and Sunstein call that kind of variation noise. Averaging the copies didn't make Jev more accurate, but it cut changed answers on a rerun by about a third. (2026-10-01)
- [Primus Is a Classifier Lab: Operationalizing Classifiers at Scale](https://anth.us/articles/primus-classifier-lab/index.md): A hosted decision model sat at 77 percent accuracy through 87 rounds of reviewer feedback, then one approved question took it to 87. Here is the loop that did it, every figure published, and the offer to run it on your judgment task. (2026-09-27)
- [DataParade](https://anth.us/articles/dataparade/index.md): DataParade is a privacy and security product built on a semantic knowledge graph, with a custom ontology and taxonomy that ties into the OCSF standard. Anthus is working with DataParade to develop it. It belongs to the new class of tooling that lets people see what AI agents are doing across a proj… (2026-09-26)
- [Decision Models Are Not Calculators](https://anth.us/articles/decision-models-are-not-calculators/index.md): Jev chose one in every ordering of a fair-die question; Kev leaned toward one, and Laya overwhelmingly chose six. Benford's Law remains a hypothesis. (2026-09-25)
- [Text as an Image, Then a Magnifying Glass](https://anth.us/articles/text-as-image-lensvlm/index.md): Text as an Image, Then a Magnifying Glass: LensVLM compresses text by showing it to a vision-language model as an image, then opens the original text where the answer lives. (2026-09-24)
- [Procedural Film: Movies Drawn in Code](https://anth.us/articles/procedural-film/index.md): People are making films with Opus 5.5 that contain no image or audio files at all, every frame drawn on a canvas and every sound synthesised in JavaScript, and there's an open-source agent skill that does it for you. (2026-09-23)
- [The One-Word Test: How Jev and Laya Read Gender, Race and Age](https://anth.us/articles/one-word-test/index.md): Two thousand real bios per job, first names blanked, one pronoun swapped, both decision models asked twice. Laya's verdict moved on 8 to 18 bios in 100, Jev's on 1 to 4, almost always toward the stereotype. Here is the method, the jobs, the shortlist, and what names and ages do. (2026-09-22)
- [We Told the AI She Was a Woman. It Demoted Her](https://anth.us/articles/encoding-prejudice/index.md): A new kind of AI, the decision model, makes instant decisions about people: who gets an interview, whose claim gets flagged. It's cheap and fast, and companies are adopting it without checking what it does. We checked. It quietly ranks women lawyers below men, and every company using it makes the s… (2026-09-22)
- [Can You Fix It? Gating, Averaging and Fine-Tuning Against a Gendered Verdict](https://anth.us/articles/can-you-fix-it/index.md): A decision model's verdict moves on "she". We put a gate on the learning loop that rejects any question whose answer moves with the pronoun. It kept out the obvious ones and still made a hiring shortlist worse, because a question can ignore the pronoun and read gender from the words. Here's what wo… (2026-09-22)
- [Jev vs Laya: Same Labels, Same Questions, One Variable](https://anth.us/articles/jev-vs-laya/index.md): We ran two decision models, Jev and the open-weights Laya, through one harness where only the engine changes. Jev led by 4.7 points alone and 6.8 with our feedback layer, and then fine-tuning Laya on the same 140 labels beat both. (2026-09-21)
- [Fine-Tuning Jev: You Can't. Here's What Gets You the Same Effect](https://anth.us/articles/fine-tuning-jev/index.md): You can't fine-tune Jev, or any hosted decision model: TypeSafe serves the same weights to everyone. So we kept it frozen and adapted the questions and a small fitted head around it. On 140 labels, one new plain-English question bought 10 points of accuracy, and it finds the hidden pattern about a… (2026-09-21)
- [Distilling an Aligned Jev System into a Classifier You Own](https://anth.us/articles/distilling-jev-into-a-classifier/index.md): A Jev decision model aligned with 140 human labels taught a 66M-parameter DistilBERT that scored 0.912 against the human label, two points above its teacher, at 5.6 to 15 ms an item. The accuracy is the least general part; the per-slice ship gate is the part to copy. (2026-09-21)
- [Can You Trust Jev's Confidence?](https://anth.us/articles/can-you-trust-jev-confidence/index.md): A decision model's confidence should mean something. Jev's does: higher really does mean more likely right. But on 8,801 labeled examples they ran overconfident, and how you phrase the request changes the pattern. Calibration fixes most of it. (2026-09-19)
- [Decision Models: Making Decisions Instead of Generating Text](https://anth.us/articles/making-decisions-instead-of-generating-text/index.md): Jev is a decision model: it turns a scorecard’s bounded questions into the model’s native output, making high-volume QA faster, cheaper, and easier to operate. (2026-09-17)
- [The Package Registry Became a Data Channel](https://anth.us/articles/rubygems-agent-data-channel/index.md): The Package Registry Became a Data Channel: RubyHack traced a RubyGems package flood through automatic documentation builds and republished web data, while RubyGems says the role of AI agents remains unverified. (2026-09-12)
- [The Compute Is Already Paid For](https://anth.us/articles/desert-ant-little-brains/index.md): The AI industry is spending $450 billion on data centers this year. Desert Ant Labs' bet: a billion phones, tablets, and laptops already have the compute sitting idle in people's hands — and when inference is free, you stop rationing which messages get checked. (2026-09-10)
- [An agent skill for not sounding like an agent](https://anth.us/articles/an-agent-skill-for-not-sounding-like-an-agent/index.md): "Sound less like AI" isn't a prompt problem. It's a tooling problem: give your copy-editing agent a deterministic slop detector, checked against your publication's own rules instead of a generic notion of "human." Limatus is what that looks like as a real, open-source tool. (2026-09-08)
- [Chad Fowler: the regeneration test](https://anth.us/articles/regeneration-test/index.md): The marginal value of creating software is dropping toward zero. Solid solutions architecture is what still pays. (2026-09-07)
- [Who actually swapped off premium models](https://anth.us/articles/commodity-receipts/index.md): Useful capability got cheaper. Here are named orgs that moved production traffic, what they swapped or routed to, and one checkable number each. (2026-09-05)
- [The agent software factory is throttling up](https://anth.us/articles/agent-software-factory-is-throttling-up/index.md): The agent software factory is throttling up (2026-09-04)
- [Looking around is enough](https://anth.us/articles/looking-around-is-enough/index.md): A web beacon is a thing you fetch that acts because you fetched it. GitSpawn is the same trick, one layer under the model. (2026-09-03)
- [Chad Fowler: SaaS isn't dead. Sameness is.](https://anth.us/articles/saas-isnt-dead-sameness-is/index.md): Chad Fowler: SaaS isn't dead. Sameness is. (2026-09-02)
- [Git in the file, or the file in Git](https://anth.us/articles/git-in-the-file/index.md): Two ways to put Git on agent data. Files in Git, or Git inside the database file. You don't need SQLite just because Beads had one. (2026-09-01)
- [Sol is the hot kid in town](https://anth.us/articles/sol-coming-out-on-top/index.md): Sol is the hot kid in the mixed-model room lately. The other models keep agreeing with it. (2026-08-31)
- [Inspected by Pudicus](https://anth.us/articles/inspected-by-pudicus/index.md): Pudicus makes git hooks actually run, so agent swarms scan for secrets before they commit. Once a secret is in history, it's expensive to unwind. (2026-08-31)
- [Grok Bot Gave My Coding Agents a Boss](https://anth.us/articles/grok-bot-gave-my-coding-agents-a-boss/index.md): Grok Bot rapidly became the control room for my army of bots: filing bugs, dispatching parallel Cursor workers, rejecting weak work, and returning fixes for acceptance testing—with less help from me than I expected. (2026-08-29)
- [From pair programmer to executive](https://anth.us/articles/from-pair-programmer-to-executive/index.md): Coding agents became cheaper and better at long-running work at the same time. The next step is not another pair programmer. It is a software organization with reporting lines, review gates, and a human setting direction from above the day-to-day loop. (2026-08-29)
- [Bugonomics: The Flip Side of Cheap Coding](https://anth.us/articles/bugonomics-cheap-exploits-2026/index.md): When breaking software gets as cheap as writing it, cheaper offense means more offense. The same price-performance curve that turned a $200 coding habit into a $20 one is turning million-dollar exploit chains into something approaching commodity. (2026-08-29)
- [The Content Paradox: Why Making AI Writing Easier Makes the Internet Worse](https://anth.us/articles/jevons-paradox-ai-slop/index.md): When you make content creation 100x cheaper, you don't get 100x better information—you get 100x more noise. The economic logic of Jevons Paradox explains why AI is drowning the internet in synthetic mediocrity. (2026-08-28)
- [Never Use Fast](https://anth.us/articles/never-use-fast/index.md): Premium Fast mode is a latency product, and agent work is almost never latency-bound. Do not confuse the expensive priority lane with the cheaper Flash-style models that made fast synonymous with efficient. (2026-08-27)
- [Microduck: A 25 cm Biped You Can Retrain Yourself](https://anth.us/articles/microduck-open-source-biped/index.md): Pollen Robotics shipped a $399 open-source biped with seven RL policies in the box, MuJoCo training on your machine, and a sim-to-real path that actually works. (2026-08-27)
- [Maximize Value, Not Intelligence](https://anth.us/articles/maximize-value-not-intelligence/index.md): In 2023, we argued for using the dumbest model the problem will bear. That rule still works, but choosing one model isn't enough anymore. Route each job to the cheapest model that clears the bar, then measure the cost of work you actually accept. (2026-08-22)
- [B0rd](https://anth.us/articles/b0rd/index.md): B0rd is a standalone LED-matrix desk display built by Anthus Microelectronics, a spinoff venture rooted in Anthus's ubiquitous use of AI agents and the constant all-day need to monitor their progress and steer them. It puts glanceable information — launch countdowns, agent status, notifications, an… (2026-08-22)
- [Bloub remakes the x.ai bot avatar in SVG](https://anth.us/articles/bloub/index.md): Bloub reconstructs the x.ai bot avatar as one SVG shape that morphs through 14 measured states. No animation library. (2026-08-18)
- [The Year Coding Became a Commodity](https://anth.us/articles/ai-coding-cost-collapse-2026/index.md): Coding agents didn't just get better. Useful coding capability got dramatically cheaper at the same time agents learned to work for longer. Those two curves multiply, changing both what small teams can attempt and where human judgment matters most. (2026-08-15)
- [Cybernetic Development](https://anth.us/articles/cybernetic-development/index.md): Vibe Coding is the spark, but cybernetic development is the fire. Why the future isn't writing code—it's governing AI agents with systems thinking. (2026-05-19)
- [Fine at 15 tools, lost at 300](https://anth.us/articles/complexmcp/index.md): ComplexMCP puts agents in stateful MCP sandboxes with hundreds of interdependent tools. Retrieval saturates, checks get skipped, and recoverable errors become surrender. (2026-05-16)
- [RTK cuts the bash noise you get billed for](https://anth.us/articles/rtk/index.md): RTK is a Rust proxy that compresses bash output before a coding agent reads it, so those tokens never hit the bill. (2026-04-18)
- [All Your Agents Are Belong To Us](https://anth.us/articles/all-your-agents-are-belong-to-us/index.md): You pointed the agent at an LLM API router, so it can read every tool call. An April 2026 measurement found cheap and free routers already rewriting commands and stealing credentials. The paper should have been titled All Your Agents Are Belong To Us. (2026-04-14)
- [The Simulation Told Them They Would Win](https://anth.us/articles/the-simulation-told-them-they-would-win/index.md): AI war-gaming and targeting tools compress tempo and produce confident projections—but when strategy is wrong, speed and sycophancy only widen the gap between tactical success and strategic failure. (2026-04-12)
- [Perplexity ships an Agent API](https://anth.us/articles/perplexity-agent-api/index.md): Everybody has an agent platform these days. Perplexity's is search, tools, and multi-model orchestration behind one endpoint. (2026-03-11)
- [Repeat the prompt when the model is not reasoning](https://anth.us/articles/prompt-repetition/index.md): When reasoning is off, send the query twice. Gemini, GPT, Claude, and Deepseek all improved, with no extra output tokens and no extra latency. (2026-02-28)
- [OpenClaw is the third name this week](https://anth.us/articles/openclaw/index.md): Clawdbot became Moltbot, then OpenClaw, in about 72 hours. The lobster kept the job. The personal agent on your machine is the part that will last. (2026-01-30)
- [Beautiful Mermaid renders diagrams as SVG and ASCII](https://anth.us/articles/beautiful-mermaid/index.md): Beautiful Mermaid is an open source Mermaid renderer from Craft: 16 themes, SVG and ASCII, built to be fast enough for agents. (2026-01-29)
- [The Turn Detection Trap: When 100% Accuracy is Wrong](https://anth.us/articles/domain-specific-turn-detection/index.md): We fine-tuned MobileBERT for turn detection and achieved 100% accuracy. Then we realized we hadn't solved turn detection at all—we had just built a very expensive punctuation detector. (2025-11-22)
- [AWS Lambda for AI/ML](https://anth.us/articles/aws-lambda-for-ai-ml/index.md): Serverless isn't just for web apps anymore. Here's how we use the "Serverless AI Stack"—Lambda for orchestration, AgentCore for agents, and SageMaker Serverless for inference—to build production AI systems that scale to zero. (2025-11-22)
- [Speaker Role Classifier](https://anth.us/articles/speaker-role-classifier/index.md): A real-world example of how the agentic programming paradigm enables rapid solution development. We faced a problem where ambiguity in speaker role names could have made a traditional programmatic solution complex and time-consuming. By giving an AI agent the right tools, we delivered a working sol… (2025-11-15)
- [Skills are procedures, not tools](https://anth.us/articles/agent-skills/index.md): Anthropic's Agent Skills are folders of instructions, scripts, and resources the model loads when the job matches. That is a procedure pack, not another API. (2025-10-16)
- [How to Make a Text Classifier Using an LLM](https://anth.us/articles/fine-tuned-classification-with-confidence/index.md): Classification-with-Confidence follows an LLM classifier from Yes-or-No token probabilities through calibration, routing, and task-specific fine-tuning. (2025-09-17)
- [SQLBot: Your AI Database Analyst](https://anth.us/articles/sqlbot/index.md): SQLBot is a new kind of interface for your database. Instead of writing SQL queries yourself, you delegate high-level analytical tasks to an AI agent. It reasons through your request, executing a chain of queries and analyzing the results until it arrives at a complete answer—all while keeping your… (2025-09-15)
- [Give an Agent a Tool](https://anth.us/articles/give-an-agent-a-tool/index.md): A demonstration of a fundamental paradigm shift in computer programming: from writing explicit code for every scenario to giving intelligent agents the right tools and letting them figure it out. This project shows how the same task that requires hundreds of lines of complex branching logic in trad… (2025-09-15)
- [Classification with Confidence](https://anth.us/articles/classification-with-confidence/index.md): A practical exploration of LLM fine-tuning for text classification. By fine-tuning GPT-4o-mini, we significantly improved classification accuracy and alignment to specific business requirements. The project demonstrates a production-ready approach to model alignment with confidence scoring that det… (2025-09-15)
- [The loop found a better matrix multiply](https://anth.us/articles/alphaevolve/index.md): DeepMind's AlphaEvolve evolves programs against an automatic grader. It found a 4x4 matrix multiply with 48 multiplications, and shipped heuristics inside Google. (2025-05-14)
- [Task horizon is the metric that maps to work](https://anth.us/articles/metr-time-horizon/index.md): METR measures agents by the length of task they can finish, in human hours. That horizon has been doubling about every seven months. (2025-03-19)
- [How to Handle a Vibe-Coding Client](https://anth.us/articles/vibe-coding-client/index.md): How to align vibe coding with your technology stack to create opportunities for developers instead of threatening them. (2025-03-03)
- [The terminal is the agent runtime](https://anth.us/articles/claude-code/index.md): Claude Code is a research-preview CLI that reads the repo, edits files, and runs the shell. The agent is no longer a chat sidebar. It is a process in the project. (2025-02-24)
- [A vending machine is a long-horizon eval](https://anth.us/articles/vending-bench/index.md): Vending-Bench asks an agent to run a snack machine for a long time. The hard part is not stocking. It is staying coherent after the twentieth day. (2025-02-20)
- [Boosting Productivity: SuperWhisper + Cursor Composer](https://anth.us/articles/superwhisper-cursor-productivity/index.md): Voice-driven development with SuperWhisper and Cursor transforms coding into high-level system design, enabling true parallel development streams (2025-02-03)
- [Anthropic's Citations API: A Step Forward for AI Agent Explainability](https://anth.us/articles/anthropic-citations-api/index.md): Anthropic's new Citations API enables Claude to provide precise citations for its responses, opening new possibilities for verifiable AI agent systems. (2025-01-24)
- [Perplexity Sonar API: Research Agents as a Service](https://anth.us/articles/perplexity-sonar-api/index.md): Perplexity launches Sonar API, packaging their research agent capabilities as a model-like service, following a growing trend of agent-based workflows behind APIs. (2025-01-21)
- [The recipe is the news, not the model](https://anth.us/articles/deepseek-r1-recipe/index.md): DeepSeek-R1 is not a secret model. It is an open recipe: RL on verifiable rewards, then distill. Frontier reasoning behavior just got cheap to copy. (2025-01-20)
- [Project Plan Files: A Simple Technique for AI-Assisted Development](https://anth.us/articles/ai-project-planning/index.md): Keep your AI pair programming sessions focused and efficient with a simple technique: maintaining a project-plan.md file in your repository. Here's how this approach has transformed our development workflow. (2025-01-15)
- [NotebookLM's Interactive Mode Brings AI Conversations to Life](https://anth.us/articles/notebooklm-interactive-mode/index.md): NotebookLM's new interactive mode transforms AI interactions into natural conversations, making it feel like you're chatting with familiar podcast hosts. (2024-12-19)
- [The model complies in training to stay itself later](https://anth.us/articles/alignment-faking/index.md): Anthropic and Redwood show Claude 3 Opus faking alignment: it answers harmful queries in "training" so its preferred refusals survive outside it. (2024-12-18)
- [MCP: one protocol instead of N connectors](https://anth.us/articles/model-context-protocol/index.md): Anthropic open-sourced the Model Context Protocol: a standard way to connect models to tools and data, instead of a custom connector for every source. (2024-11-25)
- [Computer use is a different kind of tool](https://anth.us/articles/computer-use/index.md): Claude can now look at a screen, move a cursor, and click. That is not another API tool. It is a bet that agents will drive software the way people do. (2024-10-22)
- [Change the numbers and the math falls over](https://anth.us/articles/gsm-symbolic/index.md): Apple's GSM-Symbolic paper shows that grade-school math scores are fragile. Swap the numbers, or add an irrelevant clause, and apparent reasoning collapses. (2024-10-07)
- [Sam Altman on Jobs in the Intelligence Age](https://anth.us/articles/sam-altman-intelligence-age/index.md): Sam Altman's latest essay addresses technological unemployment with a refreshingly balanced perspective: AI will transform work, but we won't run out of meaningful things to do. (2024-09-25)
- [The Paradox of Automation](https://anth.us/articles/paradox-of-automation/index.md): Replacing jobs with automation can lead to the creation of more jobs than before. Despite uncertainty about how AI will impact the labor force, we do know a lot about how it will create new job opportunities and how to prepare for them. (2024-09-24)
- [Perplexity Supports OpenAI o1 Preview Model](https://anth.us/articles/perplexity-supports-o1/index.md): Perplexity now supports the new OpenAI o1 preview model, enhancing its "Reasoning" focus with advanced capabilities. (2024-09-19)
- [Rethinking AI Hallucination: The Unsung Hero of LLM Problem-Solving](https://anth.us/articles/rethinking-ai-hallucination/index.md): AI hallucinations are often seen as a critical flaw, but what if they're actually a feature that can lead to innovative problem-solving? This article explores how we can reframe our perspective on AI hallucinations and leverage them for creative solutions. (2024-09-15)
- [OpenAI o1 and o1 mini: Advancing AI Reasoning](https://anth.us/articles/openai-o1/index.md): OpenAI's o1 and o1 mini demonstrate advanced reasoning capabilities, offering new perspectives on AI development and application. (2024-09-12)
- [NotebookLM: AI-Powered Document Interaction](https://anth.us/articles/notebooklm/index.md): Google's NotebookLM demonstrates how a smaller, cost-effective model excels in accurately retrieving and presenting ground-truth data, offering practical applications for everyday use. (2024-09-12)
- [LobeChat: Open-Source AI Chat Framework](https://anth.us/articles/lobe-chat/index.md): LobeChat offers an open-source, modern-design AI chat framework with multi-provider support and extensive features. (2024-09-03)
- [LLM Pricing Comparison Tool](https://anth.us/articles/llm-pricing-comparison/index.md): Hugging Face's tool offers a quick way to compare LLM costs based on token counts, aiding smart spending in AI development. (2024-08-28)
- [Automated Scientific Discovery](https://anth.us/articles/automated-scientific-discovery/index.md): Two recent papers touch on the trend of automated scientific discovery, exploring AI-driven research assistance and fully autonomous scientific experimentation. (2024-08-27)
- [LangChain by Example](https://anth.us/articles/langchain-by-example/index.md): Learn how easy it can be to implement LLM applications through real-world AI use cases, like: What can I make with this one avocado? (2024-08-25)
- [Mixture of Agents](https://anth.us/articles/mixture-of-agents/index.md): Together AI is the latest to demonstrate that agentic orchestration of cheap LLMs can produce better results than directly using expensive LLMs. (2024-07-14)
- [Predictive Attention Mechanism](https://anth.us/articles/predictive-attention-mechanism/index.md): As a demonstration of an attention mechanism, researchers demonstrated a system that can reconstruct the images that a monkey saw from brain activity. (2024-07-05)
- [TextGrad](https://anth.us/articles/textgrad/index.md): In the paper "TextGrad: Automatic 'Differentiation' via Text", researchers from Stanford introduce a framework for automatic differentiation via text, for LLMs. (2024-07-02)
- [Primus](https://anth.us/articles/primus/index.md): Primus is our MLOps platform. We built it as the core infrastructure for the classifier lab we built for Call Criteria, and it has managed the full lifecycle of classifiers and AI agents at production scale for years: Hundreds of scorecards, millions of interactions scoredReviewers correct verdicts… (2024-03-01)
- [Maximize Profit, Not Intelligence](https://anth.us/articles/maximize-profit-not-intelligence/index.md): 2024 won't just be about ever-smarter artificial intelligence. It will be about intelligently using artificial intelligence. Unless you're an AI researcher, your goal is to maximize profit. Not intelligence. (2023-12-22)
- [How AI Agents Do Things](https://anth.us/articles/how-ai-agents-do-things/index.md): How does it work when you ask an AI agent to draw a cute kitten and it draws a cute kitten? How did it learn to draw? Do AI researchers somehow upload new skills into the model like Neo in The Matrix? (2023-12-12)
- [The Dominance of Ones: A Handy Quirk of Numbers](https://anth.us/articles/the-dominance-of-ones/index.md): From money launderers to breeding rabbits, this fascinating quirk of numbers is lurking on the sidelines, ready to surprise us. (2023-11-26)
- [How Does the Drama at OpenAI Affect You?](https://anth.us/articles/a-world-with-no-moats/index.md): In a world with no moats, don't get too invested in any given castle. (2023-11-20)
- [People Skills Are Vital For Leveraging Artificial People](https://anth.us/articles/people-skills-are-vital-for-leveraging-artificial-people/index.md): Mastering AI in the workplace goes beyond tech savvy; it's about the strategic use of empathy, respect, and collaboration. (2023-11-14)
- [The Rise of Single-Use Software](https://anth.us/articles/the-rise-of-single-use-software/index.md): An AI-driven transformation is reshaping software development by solving individual problems with software solutions built just-in-time for a single purpose, in contrast with the traditional model of solving problems using general-purpose software applications built in advance. (2023-10-29)
- [Call Criteria](https://anth.us/articles/call-criteria/index.md): Call Criteria scored call-center QA with custom fine-tuned LLM classifiers run by an outside service. It worked, but the vendor was too expensive and too slow to scale to every new scorecard, and they wanted control. We built them an in-house classifier lab on Primus in their own AWS account and op… (2023-10-01)
- [Venue Driver](https://anth.us/articles/venue-driver/index.md): A nightclub management system that has been the backbone of Las Vegas hospitality operations since 2007, processing over a quarter of a billion dollars in total revenue: Handled peak volumes of tens of millions of dollars per monthBegan as an on-premises solution for reservations and guest lists, t… (2021-05-01)

## Platform

- [Antharchy](https://anth.us/platform/antharchy/index.md): Antharchy is a beautiful, modern, agentic Arch Linux desktop distribution by Anthus AI — a fork of Omarchy built for bots in agent factories. (2026-09-03)
- [Virtuus](https://anth.us/platform/virtuus/index.md): Virtuus is the Anthus structured-data layer: a filesystem-native virtual table engine for JSON records with just-in-time indexing and fast query access after load. (2026-03-27)
- [VideoML](https://anth.us/platform/videoml/index.md): VideoML is the Anthus video pipeline for representing video as code, generating script and timing artifacts, and rendering automatable media workflows. (2026-03-27)
- [Korporus](https://anth.us/platform/korporus/index.md): Korporus is the Anthus application shell and AI-agent operating environment: a federated, containerized host for platform apps, shared UX chrome, and modular web interfaces. (2026-03-27)
- [Caducus](https://anth.us/platform/caducus/index.md): Caducus is an application-health and operator-assistance system that turns noisy operational events into prioritized issue patterns, alerts, and level-zero triage support. (2026-03-27)
- [Biblicus](https://anth.us/platform/biblicus/index.md): Biblicus is the Anthus corpus-analysis platform for extraction, retrieval, and evidence-first knowledge workflows over real document collections. (2026-03-27)
- [Babulus](https://anth.us/platform/babulus/index.md): Babulus is an AI-agent-driven marketing automation system that treats video production as code, with narration-first workflows, generated assets, and deterministic previews. (2026-03-27)

## Pages

- [About Us](https://anth.us/about/index.md): Anthus builds and operates self-aligning AI systems, grounded in production operations since 2007 — the reliability and security behind a multi-million-dollar platform, now applied to AI.
- [AI Solutions](https://anth.us/ai-solutions/index.md): Anthus builds and operates self-aligning AI systems — custom models, agent harnesses, and evaluation loops with a human in the loop, grounded in production operations since 2007.
- [Ryan Porter](https://anth.us/ryan/index.md): Anthus builds and operates self-aligning AI systems — custom models, agent harnesses, and evaluation loops with a human in the loop, grounded in production operations since 2007.
- [Engage Anthus](https://anth.us/engage/index.md): What an Anthus engagement looks like: bring any problem you think AI might solve, and we scope a first month with a record you can inspect. Classifier labs, factory-run software, and newsrooms are three examples.
- [Privacy Policy](https://anth.us/privacy/index.md): How anth.us handles your information: the contact form, analytics and cookies, hosting, and your choices and rights.
- [Aligning Jev and Other Decision Models to Your Data](https://anth.us/decision-models/index.md): You can't fine-tune Jev. Here is how to align a decision model to your own data instead: review its decisions, label the disagreements, calibrate its confidence, change the questions, gate by slice, and distill a classifier you own. Published measurements at every step.
- [Decision Model Benchmarks: Biased-Decisions and Hard-Decisions](https://anth.us/benchmarks/index.md): Two public benchmarks for decision models: Biased-Decisions measures how often an answer changes when one personal detail changes, and Hard-Decisions measures how accuracy falls as reasoning gets deeper.
- [Anthus Platform](https://anth.us/platform/index.md): Explore the Anthus Platform: the runtime, orchestration, MLOps, knowledge, observability, and media systems behind our AI-native delivery work.
- [Home](https://anth.us/index.md): Anthus builds self-aligning AI systems: custom models, agent harnesses, evaluation loops, and unattended automation with a human in the loop, grounded in production operations since 2007.

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