AI Intelligence Archive

On 16 March 2026 the batch runner for our content pipeline landed in a single commit. That commit...

Fancy Fox publishes one AI-assisted seasonal recipe idea each day. What began as a linear prompt...

AgentSelfEdit is an open-source sidecar that rewrites its own system prompt from execution feedback....

We learned about tools and wrote them ourselves. This is cute, but an application writing all of its...

A reactive, artifact-driven agent runtime — agents react to state changes instead of following a graph. Deterministic, versioned, accountable by default.

OpenAI is moving ChatGPT closer to the clinical systems healthcare teams use every day. The company...

I built an Express API that AI agents (or humans, or anything with fetch) can pay per call, in USDC,...

A website can be indexed, receive search traffic, and show no obvious issue in standard SEO tools...

Proof over claim Last time I described the hour a platform shipped the feature I had spent months...

Every "build an AI agent" tutorial starts the same way pip install langchain, import a few classes,...

OpenAI has launched Prism, a free AI-native workspace for scientists to write, revise, collaborate...

Let me tell you our starting point, precisely. Our beginning was not "people make the judgment." Our...

I’ve been working on a small experiment around a semantic shell. The basic idea is that the user...

The headline is a extract of a skeet from a gamedev/designer/dev person of Bluesky: Osaka Skilled...

September marks the official start of Preptember, a month dedicated to organizers planning local...

Learn exactly how to leverage AI in web development frameworks in 2026. Real stats, real tools, prices, and actionable workflow upgrades. No fluff—just results.

See how to integrate AI coding tools in Agile development: 2026 stats, tool costs, pitfalls, and actionable playbooks. AI team velocity, ceremonies, and quality metrics.

Here is a Python function and a test for it. def withdraw(balance, amount): if amount <=...

LLM-based evaluators of natural language generation (NLG) quality are widely deployed as scoring tools and as automated training signals, yet the internal procedure by which they assign a rating remains poorly understood. We investigate th…

Evaluating software engineering agents on realistic benchmarks is costly, since each task may require multi-step code exploration, modification, and test execution. Existing efficient evaluation methods select representative subsets to est…

The repository-level code generation task requires synthesizing code that satisfies task requirements while remaining consistent with the target repository context. Since real-world repositories often exceed the input length limits of LLMs…

Dynamic agent harnesses let language models change the software that shapes their own execution. This flexibility brings a new reasoning burden: a local plugin change can propagate through dependencies and cleanup. We introduce CordisBench…

Natural language is emerging as a primary feedback channel for improving language agents, capable of conveying intent, preferences, and causal structure in forms interpretable by both humans and modern language models. We call this paradig…

Real-world robotic assembly at sub-millimeter tolerances demands spatial precision, compliant interaction, and robustness to contact failures. We present Facet-0, a robotic foundation model that predicts and values the contact consequences…

We develop a framework for mechanism design with AI agents whose alignment (preferences) and capabilities (feasible actions and information) are unknown. We want such agents to act on our behalf so mechanisms must incentivize both honesty …

AI tutors are most useful when they adapt to each student's strengths, weaknesses, and preferred guidance, but evidence about which guidance works for which student is sparse, slow, and costly to collect from real learners. Student simulat…

Writing involves diverse cognitive activities, from ideation to revision, and writers' needs vary across individuals and moments. Proactive AI promises to provide the right support at the right time, yet existing proactive tools largely fo…

Post-training quantization (PTQ) is widely used to reduce the cost of serving large language models (LLMs), but its accuracy cost is uneven and is often tuned per model. We study where quantization damage occurs and how to allocate a small…

AgentSelfEdit is an open-source sidecar that rewrites its own system prompt from execution feedback....

In 660 of 800 autonomous research runs, the agent found a critical flaw and delivered the result anyway. Self-review is not a control unless it can block the effect.

Extracting structured fields from hundreds of millions of documents annually remains costly in regulated industries: bespoke OCR cascades cover only a fraction of workflows, privacy rules preclude external models, and existing open-source …

How to divide a fixed annotation budget between supervised fine-tuning (SFT) and reinforcement learning (RL) during LLM post-training remains an open problem. Existing work characterizes only broad trends (e.g., SFT dominates in low-data r…

Data-residency constraints force enterprises to self-host LLMs, but continuous adoption of newer models without decommissioning their predecessors expands the serving fleet, fragmenting a finite GPU pool. We consolidate traffic from over 2…

Vision-Language Models (VLMs) provide useful priors for interactive decision-making, but using them directly as policies is expensive and brittle: they must be queried at every step, do not improve from environment interaction, and can rep…

Large language models (LLMs) struggle to classify text into taxonomies with many semantically similar labels, as the distinctions are domain-specific and not captured by pre-training. To handle large label spaces, a common approach retriev…

Semiconductor supply chains face escalating risks from geopolitical tensions, geographic concentration, and rapid technological shifts, yet no scalable system continuously extracts, structures, and prioritizes risk intelligence from public…

We present H3-World, an efficient framework that turns the 33B MiniMax-H3 video generator into an interactive world model. Our key finding is that, as large video generators become more capable, language is emerging as a natural interface …

Training Physics-Informed Neural Networks (PINNs) requires jointly optimizing physics residual and initial/boundary condition loss terms, which often induce conflicting gradients. Gradient surgery methods mitigate this issue by constructin…

We evaluate embedding retrieval where surface form and meaning are pulled apart on purpose: retrieving items that share underlying structure but not wording, in two unrelated domains under one protocol, competition mathematics (MathNet-Ret…

Automated lesion segmentation in whole-body PET/CT is complicated by the variety of physiological tracer uptake patterns and by the differing appearance of lesions across tracers. The autoPET/CT V challenge addresses this by making segment…