#MicrosoftBuild continues to be one of the most important events to watch for understanding where enterprise AI, developer platforms, cloud infrastructure, and intelligent applications are heading next. The presence of @satyanadella , alongside sessions focused on GitHub
AI
-
LangChain introduces SmithDB and LangSmith Engine for agent observability
By
–
which was your favorite launch? SmithDB (database purpose built for agent trace data): https://
langchain.com/blog/introduci
ng-smithdb
… LangSmith Engine (agent for improving your agents based on trace data): https://
langchain.com/blog/introduci
ng-langsmith-engine
… -
Hidden features turn Claude into AI collaborator
By
–
Stop using Claude like a search engine. You’re missing out on the 3 "hidden" features that turn Claude into a full-blown AI collaborator: Artifacts, Projects, and Skills. If you aren't using these, you're working 10x harder than you need to. Learn how to automate your
-
ProgramBench: A New Benchmark for Evaluating AI Agents in Software Development
By
–
Can AI build an entire software project from scratch, not just fix one bug? Researchers at Meta FAIR, Stanford, and Harvard introduce ProgramBench. This benchmark tests if language-model agents can take a program’s documentation and build a full codebase that behaves
-
Long-Horizon Reasoning in LLMs: An alphaXiv AI4Science Talk
By
–
If models can think for 100,000 tokens, why do they still lose the plot? Come join us for this AI4Science on alphaXiv talk: Long-Horizon Reasoning in LLMs. In this session, Sumeet Motwani (
@sumeetrm
) and Charles London (
@CharlieLondon02
) will share recent work on both training -
Fastokens addresses tokenization bottlenecks in AI inference pipelines
By
–
Thanks for building with us @CrusoeAI As context windows explode, tokenization is becoming a major hidden bottleneck in inference pipelines. fastokens is open source, already integrated with Dynamo & @lmsysorg
, and designed for the next generation of 100K-token agent -
Using AI coding agents for automated overnight development
By
–
What madness that they've got a robot working 8 hours. Oh well, I'm setting Codex with a /goal for tonight and leaving it to work while I sleep.
-
How Agentic LLMs Are Transforming Scientific Research and Mentorship
By
–
Why LLMs Aren't Scientists Yet? In our latest AI4Science talk, Prof. Dhruv Kumar (
@gargdhruv36
) and Dhruv Trehan (
@dhruvtrehan9
) from @lossfunk discussed how agentic LLM systems can support science in a whole new way, from generating research ideas to mentoring young researchers