Multi-Agent System Design: Moving From Prompts to Contracts
Secure multi-agent handoffs by replacing natural language prompts with Pydantic schemas and deterministic contracts to prevent data leakage and system failure.
Blog
The Agentic Web: Why AI Agents Need a Resume (Arscontexta Skill Graph)
The Arscontexta Skill Graph solves O(n) context bloat in AI agents by replacing massive system prompts with a navigable SKILLS.md folder structure.
Watching every fund filing on Earth, for free
Situational Awareness LP just tripled its book to $13.7B and FinX parsed every position before the document had been on EDGAR for an hour. The pipeline that surfaces those filings the minute they land is ~250 lines of Python, one JSON registry, and a Telegram bot. $0 per month. Point your agent at this article.
The Pilot-to-Production Death March
Five Reddit posts, every major vendor's framework release, and Uber's 1,500-agent data point all converged on one diagnosis: the harness is the constraint, not the LLM.
The Diligence Wall: Anthropic Shipped 10 Finance Agents Into the Carve-Out
Anthropic shipped 10 finance agents 18 days after SR 26-2 carved generative and agentic AI out of model risk. Here is the Day 1 diligence checklist.
The Overtake Underneath: What Bifurcated When Anthropic Passed OpenAI
Anthropic crossed $30B ARR while OpenAI sat at $24B. The model layer bifurcated by buyer surface, and Bain's $2T sector revenue math got harder, not easier.
The Mythos Boomerang
Anthropic's Mythos gating fight became federal AI policy in four weeks. Five labs, CAISI, and an FDA-style executive order changed the regime.
The Procurement Inversion: When Self-Hosting Chinese Weights Becomes the Compliant Choice
DeepSeek V4-Pro shipped MIT-licensed at 1.6T parameters while Anthropic Mythos sits behind White House gating, and enterprise procurement just walked through the open-weight door.
Same Capex, Different Denominators: What Q1 2026 Hyperscaler Earnings Said
Meta, Microsoft, Alphabet, and Amazon all spent like hyperscalers in Q1 2026. The market priced one of them as a thesis bet. Here's why.
The Cognitive Debt Studies Don't Prove What People Think
A close read of the MIT EEG paper, the Microsoft survey, and the METR developer study — what the evidence actually supports about AI agents and human cognition.
The Mythos Gate vs the DeepSeek Door
The White House blocked Anthropic's plan to expand Mythos access on April 30. Six days earlier, DeepSeek shipped 1.6T parameter weights for vulnerability discovery on Hugging Face.
The Design Decisions You're Making Without Knowing It: What Academics Found Inside Claude Code
A research team reverse-engineered Claude Code and found that 1.6% is AI logic and 98.4% is infrastructure. The paper maps every design decision agent builders make implicitly.
Transformer Forecast Collapse: Why More Powerful Models Make Worse Financial Predictions
A formal proof shows that increasing transformer expressivity leads to strictly worse financial predictions under MSE loss. PatchTST lost to a linear model on 92% of test windows.
Stanford's AI Index vs the Consensus: What 400 Pages of Data Actually Show
Stanford's 2026 AI Index contradicts consensus narratives. The US ranks 24th in AI adoption, benchmarks predict nothing about reliability, and transparency is collapsing.
The Deskilling Feedback Loop: When Vibe Coders Never Become Senior Engineers
AI coding tools create a pipeline time bomb. Junior devs develop a 17% comprehension gap while senior engineers drown in 98% more PR reviews.
The 25% Tax on AI: How Chip Tariffs Are Sorting the Industry
A 25% tariff on AI chips with a 100MW exemption floor favors hyperscalers. Startups face 50-75% cost increases while domestic production is years away.
Tennessee Wants to Jail Your AI Engineer for 15 Years
Tennessee SB 1493 makes chatbot building a Class A felony while the White House pushes deregulation. 78 AI bills across 27 states and zero federal preemption.
The Great Flattening: Why AI Is Killing Middle Management First
AI layoffs in Q1 2026 targeted middle management, not entry-level workers. Oracle, Amazon, Block, and Snap cut managers to fund AI infrastructure.
LLMs Don't Hear Music. Here's What They Actually Need.
You can't hand a song to an LLM and expect it to understand production. I built a decomposition pipeline that extracts 40+ parameters per stem, and the pattern applies far beyond music.
Allbirds Just Became an AI Company. That Should Worry You.
A shoe company rebranded as NewBird AI, surged 600%, and revealed exactly where we are in the AI hype cycle.
The AI Second Brain Wave: What Claude Code + Obsidian Actually Gets You
Everyone's building AI second brains with Claude Code and Obsidian. Here's what actually works, what breaks, and why I built two Obsidian plugins before the trend existed.
Open Source Just Passed Frontier: What GLM-5.1 Means for Builders
GLM-5.1 topped SWE-Bench Pro under MIT license. Gemma 4 shipped edge variants under Apache 2.0. Open source model parity is here — with caveats builders need to understand.
The $650B Zero-ROI Disconnect: AI's Biggest Bet vs the Data
Amazon, Meta, Google, and Microsoft are spending $650B on AI infrastructure. Goldman Sachs says the GDP contribution is basically zero. Here's what the data actually shows.
Inside Foliome: How the Agent Actually Works
The technical companion to Foliome's release. How the agent builds its own bank integrations, orchestrates parallel sync with MFA routing, recovers from errors without human intervention, and serves a dashboard from your local machine.
Foliome: Your Money, Your Machine, Your Agent
I haven't logged into a bank app in three months. An open-source financial operating system where your AI agent syncs your banks, classifies spending, and gives you complete financial intelligence. Everything local. Everything yours.
The Keynesian Folly: Why AI Will Never Fully Automate Finance
Financial markets are reflexive. AI models degrade the patterns they exploit. The CFA Institute says augmentation, not automation.
AI Platform Divergence: What It Means for Builders
OpenAI is betting on agents, Anthropic on coding, Google on multimodal. Here's the evidence, the strategy layer, and what to do if you're building in between.
DPO Fine-Tuning a 1.2B Model: What Worked, What Broke, What I'd Skip
DPO fine-tuning a 1.2B model with LoRA improved style but degraded reasoning after 400 samples — accuracy dropped from 39/40 to 34/40, and the base model won.
Multi-Model Routing: Instruct vs Thinking on Edge Devices
How I route between two LFM2.5-1.2B models on a Raspberry Pi 5 — when to use Instruct, when to use Thinking, and why user-controlled toggles beat automatic detection.
The Frontier Model Tax
Airbnb doesn't run OpenAI in production. Cursor built its own Tab model. The shift to fine-tuned small models is real — here's the decision framework for builders.
Agent AI Execution: Why Unix Shell Beats JSON Function Calling
Building agents with a single shell execution tool reduces formatting errors and improves autonomy by leveraging LLM training data instead of brittle JSON schemas.
M5 Max and Local LLMs: Why the Best AI Tools Will Never Be Open Sourced
M5 Max hardware enables 120B parameter models to run locally at 65.8 tokens per second, shifting developer focus from public open-source projects to private, hyper-personalized dark tools for maximum leverage.
The 2026 Solo Builder AI Stack: Picking Tools for Optionality, Not Features
Every solo builder is sharing their AI stack. Nobody explains why they chose it. The difference between a stack and a dependency trap.
The AI Displacement Report Card: What the Data Actually Shows
WEF predicted 85M AI job losses by 2025. Actual US figure: 200K-300K. Oil, tariffs, and DOGE explain more than AI does.
The Consultant-to-Builder Pipeline: How to Learn Technical Skills by Solving Problems
AI displaced 200K-300K jobs while employment grew 2.5%. The opportunity isn't learning to code. It's solving a $1,000 problem in your domain with AI tools.
Text-to-Data with Snowflake Cortex: Building a Natural Language Portal
Build a secure text-to-data portal using Snowflake Cortex and Llama 3.1 to translate English into Pandas while maintaining a strict Python sandbox.
Gemini Agentic Workflows: Solving Model Laziness with Skill Graphs
Reduce Gemini agent shortcuts and memory loss by replacing flat tool lists with a file-system Skill Graph for structured, stateful workflows.
The Entry Point Is Closing
Anthropic's own labor data shows AI isn't eliminating white-collar jobs yet — it's quietly shrinking entry-level hiring. Here's what that means if you're making the move into tech right now.
The End of the Context Window War: How Recursive Language Models Solve Infinite Data
Recursive Language Models replace massive context windows with a programmatic loop, letting small local models process infinitely long prompts.
Extracting an Obsidian Plugin From a Note App
I took the voice transcription pipeline out of my note app and shipped it as an Obsidian plugin. No platform. No local server. Just the slice that worked.
AI Agent Architecture: Why Single Prompt Files Fail at Scale
Why single prompt files fail for AI agents—and how failure-driven codification built a 108,000-line C# system with 19 specialized agents.
Agent Memory Architecture: Why Documentation is Agent RAM
How to manage a 24% knowledge-to-code ratio using a 3-tier context architecture—Hot, Warm, and Cold storage for AI agents.
AI Context Coverage: The 25% Rule for Large Codebases
How a 24% knowledge-to-code ratio prevents AI hallucinations and architectural rot in 100k+ line repositories.
AI Agent Architecture: How to Build 'Identity' Without Breaking Performance
Stop using 2,000-word system prompts. Learn how Tiered Context Architecture, Style Injection, and the Observer Pattern optimize AI agent performance and cost.
OpenClaw: Framework or File Bloat? What to Reuse (and Skip)
An evaluation of the OpenClaw gateway, the 'soul.md' ecosystem, and why separating Skills from Souls is the key to reliable agents.
Recursive Language Models: How to Process Infinite Context With an 8B Model
RLMs let small models handle inputs 100x beyond their context window by storing prompts in a REPL and recursively processing slices. Here's how it works.
The LLM Parameter Lie: What Actually Matters in 2026
Parameter counts are a vanity metric. How to read LLM architectures, what active parameters mean for your hardware, and the benchmarks that actually matter.
The 2026 AI Stack: Building Compound Systems and Agentic Workflows
A strategic blueprint for the modern AI stack: moving from simple LLM wrappers to model routing, multi-agent orchestration, and local-first memory.
ChatGPT Ads: What Changes When the Search Box Talks Back
ChatGPT Ads target conversation context, not keywords. Here's what OpenAI confirmed, what's speculated, and how GEO content prepares you for both.
Custom Blocks in Obsidian: The Scribe Block
Obsidian doesn't have custom blocks, so I faked it with a code fence, a hidden div, and two features that actually make it useful.
Lazy Engineering: Why GraphRAG Beats 1M Token Context Windows
Large context windows introduce massive KV cache costs and latency. GraphRAG provides better retrieval accuracy for complex datasets at a fraction of the compute expense.
RTX 5090 Local AI ROI: GPU Cluster vs. API TCO Analysis
An RTX 5090 cluster breaks even against DeepSeek API costs at 450M tokens of inference, providing a 14-month ROI for high-volume developers.
System 2 Distillation: Porting DeepSeek-R1 Reasoning via Probability Mapping
Distill DeepSeek-R1 reasoning into small models for $0.50 using logit-based probability mapping. A high-signal alternative to standard fine-tuning.
Qwen 3.5 vs Liquid LFM: Edge AI Benchmarks on Raspberry Pi 5
Comparing Qwen 3.5-2B and Liquid LFM2.5-1.2B on Raspberry Pi 5: benchmarks for GPQA intelligence, RAM usage, and time-to-first-token latency.
Voice Transcription Market: Current State and the Missing Piece
Voice transcription in 2026: who ships what (Monologue, Wispr Flow, Hey Lemon), what builders use (Whisper, AssemblyAI), and why fragmentation and lock-in are the real problem.
DIY Local Voice Assistant: Building a Raspberry Pi 5 AI Device
How to build a private, fully local voice assistant on Raspberry Pi 5 using Python and Whisper for on-device speech processing and LLM inference.
Launch Platform ROI: Data on Product Hunt, HN, and AppSumo
Actual traffic and conversion data for Product Hunt, Hacker News, and AppSumo — including the 10% featured rate and specific ROI math for indie makers.
LFM2.5-1.2B on Raspberry Pi 5: llama.cpp Optimization Guide
Optimizing llama.cpp for LFM2.5-1.2B on a Raspberry Pi 5. Recommended settings for quantization, threads, and KV cache to maximize local LLM performance.
Raspberry Pi 5 Local Voice Assistant: A Whisper and Liquid LFM AI Stack
Build a private AI voice assistant on Raspberry Pi 5 with Whisper and Liquid LFM2.5. Includes memory budgets, hardware setup, and Python code.
Deep Research: Exa.ai vs Other Providers
Embedding deep research in a note app with Exa.ai. I built a 5-phase enrichment pipeline, then simplified to Exa with a light review step.
GEO: The New Rules of Search Visibility
AI search engines don't rank pages — they cite sources. Here's what actually works for getting cited by ChatGPT, Perplexity, Claude, and Google AI Overview.
Handling Chain-of-Thought for GPT-OSS-120b: Harmony Format and Provider Quirks
GPT-OSS-120b uses OpenAI's Harmony token protocol — analysis, commentary, and final channels. Here's how we handle CoT leakage and provider routing.
Workspace vs Document Assistant: Why You Need Both
The best work happens when conversation stays continuous. Document-localized chat gives the workspace assistant richer context — here's how we architected it.
LFM2.5-1.2B vs LFM2-2.6B: Why We Chose the Smaller Model
Benchmarking Liquid AI's LFM2.5-1.2B against LFM2-2.6B on a Pi 5 — the smaller model scores higher on IFEval (+9), runs 2.3x faster, and fits in under 1GB.
Why We Stopped Forcing One Model to Do Everything
We built a Reasoner-Planner-Solver pipeline for a Pi 5 voice assistant, then replaced it with Instruct/Thinking model routing. Here's why simpler won.
Ditching Exa AI for Self-Hosted Search
Replacing Exa AI with self-hosted SearXNG and trafilatura on a Raspberry Pi — fully local web search in 2-3 seconds, no API keys, no data leaving the device.
From 78% to 97%: Making a 1.2B Model Actually Work
Three tricks that took a 1.2B model's tool routing from 78% to 97% — renaming tools, adding a calibration line, and a regex post-processor.
One Model, Three Roles: How a 1.2B Model Plays Reasoner, Planner, and Solver
One 1.2B model plays Reasoner, Planner, and Solver with different system prompts on a Raspberry Pi 5. Three LLM calls, 15-30 seconds for a reasoning task.
When to Stop Adding Rules: Building a Negation-Aware Sanitizer Without Overfitting
I kept adding regex patterns to fix edge cases until I realized I was overfitting a rule-based system — here's the framework for knowing when to stop
Thinking Without Thinking Models
How I got multi-step reasoning working on a Raspberry Pi 5 with a 1.2B model — no thinking model needed. ReWOO cuts it to 2 LLM calls and 80% fewer tokens.
The SKILLS.md Standard: Why the Agentic Web Needs a Universal Resume
Stop writing massive Python files to tell your AI agents what they can do. We need a portable, plain-text standard for agent capabilities.
The Instruction Gap: When AI Starts Building Its Own Systems
We want AI to work autonomously, but letting it write its own playbook creates a new kind of technical debt.