Knowledge catalogue
arXiv:2605.18684v1 Announce Type: cross Abstract: Legacy systems concentrate business rules, architectural decisions, and operational exceptions that often remain implicit in code, data, configuration
arXiv:2605.18332v1 Announce Type: cross Abstract: Behavioral studies of LLM-based software engineering agents extract operational rules about which trajectory shapes correlate with higher resolution r
Clem Delangue argues for increased support and flexibility for local inference engine options rather than restrictions or consolidation. The post advocates for maintaining diverse, locally-deployed AI
Brent D. Griffiths / Business Insider: A look at a new class of jobs created by AI companies, including AI storytellers or “evangelists”, forward deployed engineers, AI chiefs, and AI gig workers — -
Fred Lambert / Electrek: After EV maker Fisker's collapse, ~4,000 car owners formed a nonprofit to keep their cars working by reverse-engineering software and building open-source tools — When Fisker
LangSmith Engine automates the full agent fix loop — detecting failures, diagnosing causes and drafting PRs. But multi-model enterprises say a neutral observability layer still wins. http://venturebea
Many AI agents in finance rely on extremely high quality context engineering from documents 📑 They can be roughly divided into two categories: 1️⃣ Repetitive, operational work common in back-office us
getting ready for our first Cabinet Minister ever speaking not as a politician, but as a @NanoClaw_AI user and AI Engineer! All @aiDotEngineer SG talks kick off in 22 mins! Tune in live: https://www.y
Deedy / @deedydas: SF vibes are frenetic over the huge divide in outcomes and career uncertainty for software engineers; over 5 years ~10K people in AI attained retirement wealth — The vibes in SF fee
ICYMI: 1️⃣ LangSmith Engine 2️⃣ SmithDB 3️⃣ Managed Deep Agents 4️⃣ LangSmith Sandboxes: Now Generally Available 5️⃣ Context Hub 6️⃣ LangSmith LLM Gateway 7️⃣ Sandboxes, Prebuilt agents, + free model
Key ideas I picked up at the @LangChain conference this week: 'AI engineering is data science. Look at your data.' — @sh_reya & @HamelHusain 'Data strategy *before* agents.' — @AndrewYNg 'Coding agent
arXiv:2601.19924v2 Announce Type: replace-cross Abstract: We investigate the capabilities and scalability of Large Language Models (LLMs) in optimization modeling, a domain requiring structured reason
arXiv:2605.13619v1 Announce Type: cross Abstract: Extended depth of field microscopy encodes axial information into a single acquisition through engineered point spread functions, but conventional and
arXiv:2602.05242v1 Announce Type: cross Abstract: Agentic Test-Time Scaling (TTS) has delivered state-of-the-art (SOTA) performance on complex software engineering tasks such as code generation and bu
This post discusses implementing Physics-Informed Neural Networks (PINNs) to solve the 3D heat equation within a C++ WebAssembly engine for real-time aerospace applications. The work combines machine
LangSmith Engine, 6 months later imo, reading and analyzing long agent traces is a huge bottleneck and obstacle for progress (especially as these systems grow in time horizon). Imagine reading a langs
our engineers had an awesome time attending Interrupt:2026 by @LangChain learning about observability, agent evals, and best practices from the industry leaders! can't wait to see what they cook up wi
SmithDB is a feat of engineering. A new database for a new data shape Huge work from @ankush_gola11 and team We built SmithDB: the database purpose built for agent observability workloads that now pow
Swyx is giving a talk at AI Engineer Singapore on Saturday at 4pm about using reinforcement learning for long-running agents and reinforcement learning models (RLMs), exploring why this approach shoul
After months in stealth, my co-founder @helloericsf and I are finally sharing @cimentoai with the world. 🌎 AI changed social engineering. Attacks are now personalized, convincing, and cheap to generat
Coming up at Interrupt: 🎙️ How @clay scales their GTM Engineering agents with Head of AI @JeffBarg. 🎙️ @ummadisetti and @kordelfrance on how @Toyota Motor North America equipped 56,000 employees with
Digg expanded its ranking system beyond the top 1000 users, with Yohei Nakajima noting he was ranked #1556 and automatically classified as an engineer in the expanded rankings. The post reflects on th
arXiv:2605.11051v1 Announce Type: cross Abstract: LLM-based Software Engineering agents face a critical bottleneck: context length limitations cause failures on complex, long-horizon tasks. One promis
Spend less time on triaging Ship fixes faster Catch regressions earlier Introducing LangSmith Engine: an agent that works autonomously to find patterns in your agent's failures 💻 Accelerate the agent
Cluster magicians and GPU whisperers, come join us! We’re looking for supercomputing engineers to build the infrastructure behind real-time interactive models, Tinker, and large-scale training: schedu
arXiv:2605.10597v1 Announce Type: cross Abstract: Benchmarks for coding agents increasingly measure source-level software repair, and cybersecurity benchmarks increasingly measure broad capture-the-fl
arXiv:2605.09184v1 Announce Type: new Abstract: We present Open Ontologies, an open-source ontology engineering system implemented in Rust that integrates LLM-driven construction with formal OWL reaso
You will know that the AI labs believe in ASI when they disband their newly formed consulting (sorry “forward deployed engineering”) groups. As long as people are required to figure out how AI is usef
Agent engineering is hard Deep Agents hides a lot of the weird systems complexity, but still gives you more room to customize the harness than almost any agent SDK I've used This is harder to build th
AI existential crisis for software engineers is to go live in the woods and read poetry. AI existential crisis for creatives is to make things until 4am every day because you can't stop now. is this w
@trq212: An Anthropic engineer argues HTML is a better output format for AI agents than Markdown, citing information density, ease of sharing, and two-way interaction — Using Claude Code: The Unreason
arXiv:2605.06878v1 Announce Type: cross Abstract: This paper presents CARMEN, a runtime-adaptive, CORDIC-accelerated multi-precision vector engine for resource-efficient deep learning inference. The k
arXiv:2605.07389v1 Announce Type: cross Abstract: The integration of machine learning (ML) into complex software systems has increased challenges in collaboration and communication (CoCo) of the teams
I have one big problem with agentic engineering: I want agents to operate autonomously, but I also want granular, reversible control over every change they make. I could solve this by committing every
CTech: Israeli startup Frame Security, which protects organizations from AI-powered social engineering attacks, emerges from stealth with $50M led by Index and others — The Israeli firm aims to modern
To be clear, I meant 'idea' in the context of science and engineering, in particular AI, as in 'theory' or 'invention', like a new theory of cognition or an idea for a new ML approach. I thought that
Anthropic: Anthropic details how it improved Claude's safety training after finding agentic misalignment in older models, such as Opus 4 blackmailing engineers — Last year, we released a case study on
Europe does not lack innovation. It lacks scale. European universities produce world-class research, engineers and technology. But too many companies remain trapped inside fragmented national markets
@hwchase17 the tooling side is maturing fast but the feedback loop between engineers and domain experts is still the bottleneck. keep running into this building agents: you can instrument everything a
One theorem every ML engineer should know: The Johnson–Lindenstrauss Lemma. It states that high-dimensional data can be projected into a much lower-dimensional space while approximately preserving pai
this is a big deal, on the order of Kelsey Hightower’s “Kubernetes The Hard Way” and probably all ai engineers should go thru this once mostly i advocate “just in time learning”, but this is one scena
This means that agentic coding isn't exactly a replacement for software engineering. It is a fundamentally different way of producing software, with different best practices and different use cases. J
Elon Musk praised the Starlink engineering and production teams for their work and visited the production facility to observe operations firsthand. The post appears to be a positive acknowledgment of
Excited to speak at PyCon US @pycon about production LLM inference systems, runtime optimization, and next-gen engine design — including some of the new ideas behind the recently open-sourced project
The thing that struck us across all 10: most winners aren't traditional engineers. A teacher, a designer, a parent, a 3D-printing hobbyist. People who saw a problem in their own life and built a solut
New #YAAP episode out now 🎙️ @yuvalinthedeep sits down with @mikegchambers from @awsdevelopers to unpack harness engineering and why it's the reason most agents never make it to production. 🎧 Listen/W
arXiv:2505.19629v3 Announce Type: replace-cross Abstract: Self-adaptive robotic systems operate autonomously in dynamic and uncertain environments, requiring robust real-time monitoring and adaptive b
Welcome to DS4, a specialized inference engine for DeepSeek v4 Flash. https://github.com/antirez/ds4 This project would have been impossible without the existence of llama.cpp and GGML and the work of
I was talking with @josephruscio on the @heavybit podcast the other day when I realized that vibe coding and agentic engineering have started to blur a bit in some of my work - I published some extrac
Introducing TokenSpeed, a speed-of-light LLM inference engine. > TensorRT LLM level performance > vLLM level usability > Built by a lean and mission-driven team in two months > MIT license, open-sourc
It's time to build NYC's physical AI community. We're hosting a small dinner in NYC for engineers and people building across robotics, autonomous systems, and world models. It's a pretty unique and sp
arXiv:2605.02092v1 Announce Type: new Abstract: The automation of scientific research workflows has emerged as a transformative frontier in artificial intelligence, yet existing autonomous research ag
arXiv:2605.00827v1 Announce Type: cross Abstract: Large Language Model (LLM) agents increasingly interact with external systems through tool-calling protocols such as the Model Context Protocol (MCP).
A preview of Pinecone Nexus, a data retrieval engine available through an early access program, uses the declarative KnowQL language to improve accuracy while reducing token consumption by up to 90%.
everyone would have a deeper appreciation for Agent Products that rock because of great Context/Harness Engineering if they… talked to: - LLM Base models - Post-Trained models with no harness (no tool
Security remediation is an engineering capacity problem. AI has collapsed the time to exploit, but defensive tools haven’t kept up. Today we’re introducing Devin for Security: a set of workflows for r
Congratulations to @ashashutosh, @EdoLiberty, and the @pinecone team on the launch of Nexus, a knowledge engine for agents. They’ve spent years building at the core of AI infrastructure, and Nexus ref
deepagents you can run with a 'virtual filesystem' lets do lots of great context engineering tricks, without requiring an actual sandbox environment! @hwchase17 Where there's struggle is all of these
Introducing Pinecone Nexus. A knowledge engine for agents. The bottleneck for production agents isn't the model. It's the per-query work of searching, stitching, parsing tables, normalizing labels. Ne
arXiv:2605.00244v1 Announce Type: cross Abstract: We introduce Lucid-XR, a generative data engine for creating diverse and realistic-looking multi-modal data to train real-world robotic systems. At th