AI Intelligence Archive

Built for the WeMakeDevs × TrueFoundry Agent Harness Hackathon. There are two kinds of "AI for...

What actually makes an AI agent work? Explore the practical architecture behind modern AI agents—from...

If you are interested to get this project developed further, cosider starring it on my github:...

Transactional Outbox no JurisOS: Resiliência Local-First e Criptografia End-to-End com...

TL;DR I moved 40 REST endpoints to GraphQL in 12 days using Claude Code as the grunt-work...

If you have spent the last few months building projects with AI coding assistants (Antigravity,...

MCP promises one server, any AI client. I put that to the test by wiring Actian VectorAI DB up to...

Last week I wrote about our Product Hunt launch. 2 upvotes, 0 signups. This is the other half of the...

Language barriers in mobile apps, games, and foreign media are a constant friction point. Traditional...

We ran 160 agent tasks across two frameworks. The frameworks tied. Then we changed the model — and...

A page showed 0 views. I drew a reasonable conclusion and wrote it into my state file. Two days later I found the page had never had analytics installed at all. Didn't happen and wasn't measured look identical.

When I started building Shotinger, I thought the hardest part would be the AI. Getting good images....

Why Route Handlers are Holding Back Your AI Apps For months, the standard advice for...

Every enterprise AI initiative I've seen fail had one thing in common. The engineers who built the...

If you've ever tried to fix accessibility on an old WordPress site, you know the drill: hundreds of...

As part of the Gen AI Academy APAC, I set out to solve a major pain point for educators: manually...

Modern software development gives us access to increasingly powerful AI tools. But using AI...

If you have Cloudflare in front of your site, and at some point you wrote a cache rule that matches...

Anthropic published an AI-Native SDLC playbook last week. Its central claim: code generation is no...

You have an email agent that works in a test inbox. It classifies a support request, pulls the...

v0.2.1 RELEASED — Aug 28, 2026. Release notes · Field test report v0.2.1 Key Finding: The Mistral...

I was in the middle of a vibe-coding session, building something completely different, as I do very...

Friday evening is when most free-tier experiments begin. An engineer assigns a coding agent a large...

AI agents are getting very good at doing things. They can search databases, call APIs, modify...

SleepSwitch is a macOS menu bar toggle that stops your Mac from sleeping — lid closed included. One...

I think we are still talking about AI memory in the wrong way. Most implementations are variations of...

Note: Rails Baseline is the production-ready Rails foundation I tested here. It gives a new SaaS...

Recent advances in inference-time scaling have significantly improved the reasoning performance of large language models (LLMs). However, these methods typically rely on repeated generation or external verification. To address this limitat…

Agent skills package specialized knowledge and workflows into reusable resources that extend AI agent capabilities. Recent work automatically discovers such skills from agent experience, which enables agents to progressively adapt through …

Recent prominent post-training methods, such as Reinforcement Learning (RL) and On-Policy Self-Distillation (OPSD), have driven rapid progress in mathematical reasoning for large language models, yet their reliance on ground-truth labels p…

To improve large language models' ability to resolve real-world software issues, prior work has focused on constructing large-scale agent trajectory datasets and performing supervised fine-tuning (SFT) on successful trajectories. However, …

In real-world software development, code review typically involves iterative interactions between developers and reviewers to improve software quality, making the process costly and time-consuming. Although recent work explores large langu…

LLM-based agents are increasingly deployed in product-level execution harnesses, where jailbreaks can trigger harmful tool use and persistent state changes, creating greater risks than unsafe text generation alone. Existing automatic red-t…

Chemical reactions are fundamentally transformations in electron space, yet most machine learning approaches model them either through \textit{de novo} generation of product molecules or through heuristic graph edits that operate directly …

Transduced language models (TLMs) compose a pretrained \emph{source} language model with a functional finite-state transducer to induce a language model over \emph{target} strings. Computing the probability of a target prefix under a TLM a…

Large language model (LLM) agents in governed organizations must let the persona (instructions, tone, self-presentation) evolve freely, while keeping execution (stateful, audited work) traceable. A single trust domain does not satisfy both…

Static scanners are increasingly used to identify executable or otherwise unsafe content in machine- learning artifacts, yet conventional evaluation metrics characterize only cases where a scanner yields a usable security judgment. We eval…

Currently used sepsis severity indices rely on fixed variables and weights established decades ago, which are coarsely discretized and calibrated to a cohort that no longer reflects contemporary critical care. No alternative learned direct…

Reinforcement Learning with Verifiable Rewards (RLVR) significantly improves LLM reasoning but often causes a drop in policy entropy, leading to narrowed reasoning coverage and degraded pass@$k$ for large $k$. While existing methods mitiga…

Friend recommendation is inherently graph-structured: the relevance of a potential connection depends on multi-hop social context rather than user attributes alone. However, deploying message-passing GNNs on a production-scale social graph…