I do something similar with Cowork and skills at Towards AI, having the LLM maintain the knowledge base itself instead of me editing it manually changed everything. The "compile" framing is perfect.
AGENTS
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AI Will Automate R&D Itself, Not Just Copilot
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Many executives think AI will be a copilot. This vision is already outdated. The real issue is automating research itself. A data center will soon be able to replace entire R&D teams. My article with @dr_l_alexander [Translated from EN to English]
→ View original post on X — @alex_tsico, 2026-04-03 10:41 UTC
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Building AI Agents in Enterprise While Minimizing Risk
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How to build AI Agents without building risk in the enterprise… By Quang Tuan Dang @dangtony98 via @ForbesTechCncl & @infisical forbes.com/councils/forbeste… @BetaMoroney @Nicochan33 @enilev @mvollmer1 @mikeflache @antgrasso @FrRonconi @ramonvidall @baski_LA @AkwyZ @Khulood_Almani @sijlalhussain @PawlowskiMario @pierrepinna @sonu_monika @efipm @mvollmer1 @sallyeaves @NevilleGaunt @Corix_JC @enricomolinari @Shi4Tech @wcrpaul @RagusoSergio @RLDI_Lamy @NigelTozer @EstelaMandela @JagersbergKnut @DrFerdowsi @PerBBerggreen @sir4K_zen @AmitChampaneri1 @FmFrancoise @MasterofIoT @dcallahan2 @globaliqx @HLStockenstrom @quepasachico @ILoveBooks786 @Hana_ElSayyed @CurieuxExplorer @HaroldSinnott @MikeNashTech @SegundoConnect @pchamard @trudydarwin
→ View original post on X — @sallyeaves, 2026-04-03 09:04 UTC
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Running Full AI Assistant Locally on MacBook Air M4 Free
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Lets go: Running a full AI assistant locally on a MacBook Air M4 with 16GB, completely free, open source, no API keys needed.
— Chubby♨️ (@kimmonismus) 3 avril 2026
Atomic Bot makes it really simple: install, pick Gemma 4, and you have an always-on AI agent running on your machine. No cloud. No subscription. No data… https://t.co/iJyRNEuGHELets go: Running a full AI assistant locally on a MacBook Air M4 with 16GB, completely free, open source, no API keys needed. Atomic Bot makes it really simple: install, pick Gemma 4, and you have an always-on AI agent running on your machine. No cloud. No subscription. No data
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AI Transforms Drug Discovery Through Real Research Workflows
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That changes what AI can actually do in science. Instead of relying only on training data, it can connect to sources like PubMed and biological databases, then iterate through real research workflows. The result: → screen thousands of candidates
→ design potential therapies -
Next AI Wave: Disciplined Work Over Fluent Output
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My takeaway: the next wave of AI value will come from systems that can do disciplined work, not just fluent work. That is why self-running research is such an important signal. Watch the video to see how this works in practice, then tell me what you think . Are we looking at
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Breakthrough in AI: Multiple Specialized Agents Over Bigger Models
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The breakthrough is not one bigger model. It is multiple agents with clear roles: → one designs the research steps
→ one uses real tools and databases
→ one checks the work to catch errors
→ one writes conclusions, but only when evidence supports them In other words, less -
AI Evolution: From Question-Answering to Research-Based Systems
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Most people still think AI’s job is to answer questions.
— Ronald van Loon (@Ronald_vanLoon) 3 avril 2026
That framing is already outdated.
What got my attention about Eubiota is the shift from chatbot logic to research logic:
→ plan
→ execute
→ verify
→ refine
That is a very different category of system.
Here’s why it… pic.twitter.com/QJ6GP7JmSyMost people still think AI’s job is to answer questions. That framing is already outdated. What got my attention about Eubiota is the shift from chatbot logic to research logic: → plan
→ execute
→ verify
→ refine That is a very different category of system. Here’s why it -
Claude Skills Context Engineering: 3-Layer System for Hundreds of Skills
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Context engineering in Claude Skills is GENIUS! Skills use a 3-layer context management system that lets it use 100s of skills without hitting context limits. Here's how it works: > Layer 1: Main Context – Always loaded, it contains the project configuration. > Layer 2: Skill Metadata – Comprises only the YAML frontmatter, about 2-3 lines (< 200 tokens). > Layer 3: Active Skill Context – SKILL. md files and associated documentation are loaded as needed. Supporting files like scripts and templates aren't pre-loaded but accessed directly when in use, consuming zero tokens. This architecture supports hundreds of skills without breaching context limits. The article below is a complete guide to 𝗖𝗟𝗔𝗨𝗗𝗘.𝗺𝗱, hooks, skills, agents, and permissions, and how to set them up properly. Akshay 🚀 (@akshay_pachaar) x.com/i/article/203496196714… — https://nitter.net/akshay_pachaar/status/2035341800739877091#m
→ View original post on X — @akshay_pachaar, 2026-04-03 08:07 UTC
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Organizational Leverage Through Human-Agent Coordination Context
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Fascinating from the legal perspective, but the implications on organizational design cross over into every industry. “Leverage is no longer about how much one organization can produce; it’s found in how much context people, teams, and institutions can coordinate across humans and agents” Gabe Pereyra (@gabepereyra) x.com/i/article/203973340086… — https://nitter.net/gabepereyra/status/2039735237165404292#m
→ View original post on X — @paulroetzer, 2026-04-03 08:01 UTC