Insights for AI builders
Tutorials, product updates, and ideas to help you build and ship AI applications faster.
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Who Gets Credit When AI Solves a Math Problem Nobody Could?
AI models are solving open math problems, sparking fights over attribution, authorship, and whether humans still need to understand the proofs.
The Navier-Stokes AI Proof Controversy, Explained
An OpenAI model's claimed breakthrough on a Navier-Stokes problem sparked a credit fight. Here's what happened and why it matters.
Anthropic's Pacing the Frontier Strategy: What It Really Means
Anthropic pledged to slow its pace at the frontier, then released Opus 5.5 anyway. Here's what the strategy actually means going forward.
ChatGPT Sites: What OpenAI's No-Code App Feature Actually Does
OpenAI staff describe how ChatGPT's new app-building capabilities let non-technical people create interactive tools just by describing what they need.
Claude Opus 5.5 Pricing and Rate Limits: What Actually Changed
Anthropic cut Opus 5.5 API pricing on input, output, and cache tokens, and added rate-limit resets. Here's what's different from Opus 5.
Claude Opus 5.5: Benchmarks, Pricing, and Real-World Performance
Anthropic's Opus 5.5 explained: terminal bench and GDPval scores, 40% lower cost per task, and how it performs in hands-on coding tests.
Firecrawl's Developer Index: Better Web Search for Coding Agents
Firecrawl's Developer Index feeds AI coding agents live GitHub issues, PRs, and changelogs instead of stale blog posts from general web search.
How to Run MiMo-V2.6-Flash-RL Locally with vLLM or SGLang
A deployment guide to MiMo-V2.6-Flash-RL, Xiaomi's 309B MoE model with 15B active params, covering SGLang and vLLM setup.
MiMo V2.6: Xiaomi's Open Model Trained Live for $3.5M
Xiaomi's MiMo V2.6 Pro and Flash are open-weight models trained in a livestreamed RL run, rivaling GPT-5.6 and Claude Opus on coding benchmarks.
Are AI Labs Hiding Solved Math Problems? Scott Aaronson's Claims Explained
Scott Aaronson says OpenAI and Anthropic may be sitting on unpublished math breakthroughs after backlash over a Navier-Stokes proof claim.
How OpenAI's Codex Turned Computer Use From Party Trick to Tool
OpenAI engineers explain how Codex's computer-use feature clicks, browses and fills forms across your desktop, and why it took years to get reliable.
Opus 5.5 vs GPT-6 Sol: Which Model Wins Real Tasks?
A hands-on test of Opus 5.5 vs GPT-6 Sol across websites, video edits, and dashboards, comparing quality, speed, and cost per task.
Bonsai 2 27B: A 27B Model That Runs in Under 6GB on a Laptop
Bonsai 2 27B uses ternary quantization to shrink a 27B model to under 6GB while keeping 98% of FP16 performance. Here's how it works.
Bonsai 2 27B Benchmarks: Does Ternary Quantization Actually Hold Up?
Bonsai 2 27B claims 98.2% of FP16 intelligence at ~1.72 bits per weight. Here's how its benchmarks compare to conventional 2-bit and 4-bit builds.
Run Bonsai 2 27B Locally on a Mac: Ternary Quantization Explained
Bonsai 2 27B compresses a 27B reasoning model to 8.6GB with ternary weights, hitting ~47 tok/s on an M5 Max MacBook via MLX.
AI Is Now Writing and Reviewing Linux Kernel Code. Here's the Fallout
AI-generated patches and bug reports are reshaping Linux kernel development, forcing new disclosure rules and straining maintainer bandwidth.
How to Use OpenAI Codex: Core Concepts for Non-Coders Explained
A clear guide to installing Codex and understanding projects, agents.md, and agent loops for building AI workflows without writing code.
OpenAI Codex Pricing: What the $20, $100, and $200 Plans Actually Get You
A breakdown of Codex subscription pricing on ChatGPT's $20, $100, and $200 plans, how usage limits reset, and when API billing makes sense.
Context Engineering vs Bigger Models: Why AI Agents Fail
AI agents usually fail from broken context, not weak models. Here's why context engineering matters more than model size in production.
Grok 4.7 Hands-On: xAI's New Model Tested on Real Bugs, Circuits, Law
Grok 4.7 tested on live bug fixing, circuit diagnosis, legal reasoning, and 80-language coding tasks, checked against xAI's own benchmark claims.
How to Build an AI Model Router with Jev and Open Jev
Learn how to build a local AI model router that uses Jev-style classifiers to gate, categorize, and route prompts between local and cloud models.
Jev vs LLM: When a Classifier Beats a Generative Model
Jev's classifier approach compares against LLM-based classification for support routing, agent safety gates, and other real production patterns.
M6 Mac Mini Benchmarks: Is It Worth Upgrading from the M4?
M6 vs M4 Mac mini benchmarks compared: CPU, GPU, SSD, memory bandwidth, and local AI performance to see if upgrading is worth it.
M6 Mac Mini for Local AI: How Much Faster Than the M4, Really?
M6 Mac mini local AI benchmarks show big gains in prompt processing and image generation over the M4, with memory bandwidth as the key limit.