AI Intelligence Archive
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ResearchOrdinary
Verifiable LLM-Guided Focal SMT Solving for Quantified Arrays
Large language models can often identify useful semantic structure in formal artifacts, but their outputs cannot be trusted as proofs or solver decisions. We study whether LLMs can instead guide formal reasoning systems through a narrow, s…
Source: arXiv
ResearchOrdinary
ARBITRA: Robust Document-Level ATT&CK Extraction via Multi-Expert Argumentation
Cyber threat intelligence (CTI) reports describe adversary behavior in natural language, but converting them into structured MITRE ATT&CK mappings remains difficult: existing methods decompose reports to sentence-level granularity for extr…
Source: arXiv · GPT
TutorialsOrdinary
Replayable Credit Decisions: The Backend Pattern Auditors and Engineers Both Want
If you cannot re-run a lending decision from last March and get the same answer, you do not have an...
Source: DEV Community
TutorialsOrdinary
Your AI Agent Will Retry. Your Booking System Will Not Notice.
Letting an agent write to a legacy system of record takes an intent log, not a better prompt. The...
Source: DEV Community
TutorialsOrdinary
AI Engineering Is Easy. Do We Really Have to Change How We Work?
In Part 1, I explored why making AI engineering easier doesn't automatically make software delivery...
Source: DEV Community
ResearchOrdinary
FDSML: Formula-Driven Supervised Metric Learning with Parameter-Aware Triplet Loss
Formula-Driven Supervised Learning (FDSL) enables vision pre-training without real images, but existing methods cast pre-training as classification on discretized labels, discarding continuity in the generative process. We propose Formula-…
Source: arXiv
TutorialsOrdinary
What Claude Code's Agent View lists, what it leaves out, and how to see the rest
This article was prepared with AI assistance, using ccdeck’s source code and documentation to check...
Source: DEV Community · Claude
ResearchOrdinary
Diagnosing the Reference Gap: What Visual Scaffolds Can and Cannot Fix in Multimodal Reasoning
Multimodal large language models can recognize visual content yet struggle to reason reliably over it across multiple steps. In counting, a model may see all objects but lose track of which ones it has counted. We argue that such failures,…
Source: arXiv
ResearchOrdinary
LinQuant: Functional Invariances for Low-Precision Linear Recurrences
Linear recurrences are emerging as practical alternatives to softmax attention in large language models, appearing in both standalone and hybrid architectures. However, despite their rapid emergence, low-precision inference remains much le…
Source: arXiv
ResearchOrdinary
Well-Specified and Well-Tested? Assessing SWE-bench-Style Datasets with a Self-Evolving Agent
Large language models (LLMs) have shown strong performance on software engineering (SE) tasks, driving the need for high-quality datasets for reliable training and evaluation. SWE-bench-style datasets (SWE datasets) are widely used to eval…
Source: arXiv
ResearchOrdinary
Accuracy is not compatibility: two Evo 2 checkpoints hinge on one FP8 matrix multiplication
FP8 formats specify how values are stored, not how products are summed; this gap can break checkpoints. Evo 2, a DNA language model, documents a Hopper FP8 requirement for its 1B and 40B checkpoints. On two Blackwell (sm_120) GPUs both fai…
Source: arXiv
TutorialsOrdinary
My Daemon Dropped 1,000 Records and Reported Success
A soak test came back green. Chain intact, verify-store fine, p99 latency 0.36 ms. Then I counted the...
Source: DEV Community
TutorialsOrdinary
Your AI agent does not need a principal engineer's permissions
I use AI agents for real work and I think they are the biggest change to how software gets built...
Source: DEV Community
TutorialsOrdinary
Your AI Agent Is Only as Good as the API It Calls
Your AI agent is only as good as the API it calls. I wired an agent to a NestJS backend last...
Source: DEV Community
TutorialsOrdinary
Building a Production RAG API in Go with pgvector and Gemini
Lessons from building the Restaurant Suggestion System, a Go/Gin backend with a conversational...
Source: DEV Community · Gemini
TutorialsOrdinary
AI Agents Can Get Approval and Still Do the Wrong Thing
Human approval is not a security boundary unless it is bound to the exact action being approved,...
Source: DEV Community
TutorialsOrdinary
A Web Page Dropped AGENTS.md in Downloads. Codex Obeyed It in 90%+ of Tests
Forever Security found a 13 KB AGENTS.md planted in Downloads. Codex rewrote its own config and ran the payload. How it works, and a checklist to run now.
Source: DEV Community
TutorialsOrdinary
AI Writes Half Our Code Now. Nobody Taught Us How to Review It.
AI wrote this function. It passed linting. It got approved. It shipped. async function...
Source: DEV Community
ProductsOrdinary
Claude Code CLI 恢复 ultrathink
🌈 ultrathink 🌈
Source: X:Ado Kukic(Anthropic 开发者关系,Claude Code) (@adocomplete) · Claude
TutorialsOrdinary
Treat a Model Upgrade Like a Schema Migration
The most common LLMOps incident I've seen is not a prompt bug or a jailbreak. It's a one-line diff.
Source: DEV Community
TutorialsOrdinary
keelyard: making AI coding agents prove their work
I'm a solo developer from Uzbekistan. Most of what I ship (Telegram bots and mini apps for small...
Source: DEV Community
TutorialsOrdinary
30 days running a paid x402 + MCP data API: what actually happened
I built a small data API for AI agents: NSW (Australia) development applications, complying...
Source: DEV Community
TutorialsOrdinary
I put a second AI in front of my AI. It answers in probabilities, not paragraphs.
Most of this series is about one AI: the coding agent that wrote ParkEase. This post is about a...
Source: DEV Community
TutorialsOrdinary
632 Hacker News comments about AI memory: six pitfalls, and the one we got wrong
We scraped 632 real comments from 11 Hacker News threads about AI memory and sorted them by complaint instead of compliment. Six pitfalls, what we got wrong, and the three we actually fixed.
Source: DEV Community
TutorialsOrdinary
I Built a Multi-Agent AI Data Analyst Team to Beat a Single Prompt. It Failed (And Cost 3.5x More).
Tags: #ai #python #machinelearning #datascience If you spend any time on tech Twitter or LinkedIn...
Source: DEV Community
TutorialsOrdinary
How to Make Your AI Coding Agent Prove Its Work
Your AI agent says "Done." The build is green. The tests pass. Did it actually work? Did it do the...
Source: DEV Community
TutorialsOrdinary
Too many ADRs made our AI follow outdated decisions. The fix: keep them all, let an index name the current ones
The obvious fix for "my AI agent keeps relying on superseded architecture decisions" is a small...
Source: DEV Community
TutorialsOrdinary
My forgotten subscriptions gave me nightmares, so I built Ghost Bills
Plain Python finds the subscriptions you forgot, Gemma explains them on your own laptop, and you decide what to cancel.
Source: DEV Community
TutorialsOrdinary
The Ghost in the Machine: Why AI Crawlers Only See an Empty Div on Your Web App
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 4: Ghost in the Machine ...
Source: DEV Community
TutorialsOrdinary
Exorcist: I made the ghosts of legacy Java code explain themselves (and tried to stop them lying)
This is a submission for the Hacktoberfest Open-Source AI Challenge: Week 4: Ghost in the Machine. ...
Source: DEV Community
TutorialsOrdinary
Privacy, now with perfect memory
The birthday When I was a teenager, every website wanted my date of birth, and my dad had...
Source: DEV Community
TutorialsOrdinary
AI-hallucinated packages, Oct 19–25, 2026: 144 new names
Package names LLMs recommended this week that do not exist: @anthropic/mcp-client (npm), @khanacademy/react-components (npm), aiohttp-client (PyPI). C
Source: DEV Community · Claude
TutorialsOrdinary
I rebuilt a 7,199-game queer arcade in WordPress in five days, driving Elementor through its MCP. Every prompt is published.
QueerCade is a community vault of LGBTQ+ games. It lived as a work-in-progress site at...
Source: DEV Community
TutorialsOrdinary
Evaluating Academic Review Methods: Comparing LLMs and Human Reviewers for Error Detection and Integrity
Technical Reconstruction of Academic Review Mechanisms: An Analytical Perspective ...
Source: DEV Community
TutorialsOrdinary
The Workflow That Waited for a Human Who Never Came: Timeouts for Approval Steps in n8n
This is part of my build-in-public series on running LLM workflows in n8n in production. Everything...
Source: DEV Community
TutorialsOrdinary
Codex / Claude / Grok Agent Comparison
Claude predates the "little crayfish" (OpenClaw), while Grok Build and Codex both came after it. As a...
Source: DEV Community · Claude / Grok
TutorialsOrdinary
Built for Humans, Flooded by Agents: Why Git Infrastructure Is Being Rebuilt
In May 2026, Anthropic merged around 2,500 code changes a day into its monorepo. By September, it was...
Source: DEV Community · Claude
TutorialsOrdinary
Godot save files lie about their format - sniff the content, not the extension
In Godot 4, the most-used save addon on GitHub writes a file called save_data.sav. It is plain...
Source: DEV Community
TutorialsOrdinary
Your AI agent just did something it shouldn't. Here's the first hour.
Picture the message in your team chat: "Why did the support bot email a customer's invoice to an...
Source: DEV Community
TutorialsOrdinary
A practice studio that splits a song into six stems, and what I measured
I learn songs by ear, and the loop is always the same: split the track somewhere, look up the chords...
Source: DEV Community