Levi

@deedydas @JC_ParetsX 👀

Billionaire Michael Milken joked “if a US company replaces the US-born CEO with a CEO born in India, I buy the stock” But he reveals he hasn’t backtested the idea. So we did. In the last 15yrs, that would’ve 50x’d your money: 7.5x more $$ and >2x IRR vs S&P500: 30% vs 14%!

When MCP took off, a lot of people assumed plugging models into tools would be enough. A year later, enterprise teams are realizing that off-the-shelf MCP servers still miss basic context, and also burn too much budget. We wanted to test this directly. So we benchmarked @glean's MCP server against off-the-shelf MCP tools in Claude Cowork across ~175 queries. The harness was the same, and so were the queries. The difference was the context layer behind them. Glean was preferred ~2.5x as often, and off-the-shelf MCP setups used ~30% more tokens (median token usage: 44k vs. 57k). MCP is a protocol, not a context layer. It standardizes how models call tools. It does not solve ranking, permissions, memory, identity, or cross-system understanding. When MCP is wired directly to a set of tools, the model has to search across systems and assemble context on its own. When MCP sits on top of a unified context layer (connectors, indexes, enterprise graph, permissions, memory), it can draw from a consistent view of the company and return better results. And it’s a lot less expensive. When systems have to brute-force their way through fragmented context, they need more tool calls, more reasoning loops, and more tokens to produce a usable answer. That’s the motivation behind Glean’s MCP server. It brings the same context layer behind Glean Assistant into tools like Claude, ChatGPT, and coding environments, without asking teams to rebuild retrieval and permissions from scratch, or pay the hefty token cost of reconstructing context over and over.

Agentic systems should be treated with the same rigor as any other enterprise software. They need requirements, testing, ownership, and observability. Today, we shipped the things that make that real: auto-mode so agents can plan and act without workflow config, sub-agents for modular composable builds, agent sandbox for reliable long-running computation, debug and trace views so you can see exactly what happened when something breaks, agent library and access policies for governed discovery and org-wide guardrails, and agent insights for adoption and observability coming soon. The thread connecting it all is the ADLC - our framework for taking agents from idea to measurable impact. One @glean engineering agent built with the ADLC: 17,000+ hours saved. $1.7M in ROI.

Agent sprawl has become a real concern for many leaders I talk with. Agents are popping up across the company without shared context, clear ownership, consistent guardrails, or a reliable way to know which ones are actually creating value. The next phase of enterprise AI will be defined less by agent creation and more by agent operations, where testing, versioning, monitoring, and governance are built into the system from the start. At @Glean, we think about that through the Agent Development Lifecycle (ADLC). It is a practical model for how enterprises move from promising demos to agents that are grounded in the right context, launched with the right controls, and improved over time. Alongside the ADLC, we’re announcing new product capabilities designed to support that lifecycle end-to-end: from auto-mode agents and sub-agents to agent sandbox, agent library, agent access policies, and agent insights. In the enterprise, success won’t come from building the most agents. It will come from building agents you can trust, govern, and improve over time.

@aleabitoreddit Given this, do you like any of these names? - Chroma ATE — 2360.TW - C Sun Mfg — 2467.TW - Gudeng Precision — 3680.TW - Scientech — 3583.TW - Disco — 6146.TW

Just a TLDR of recent semi developments: 1. $TSM pushing hard CoPoS - VisEra/others might go brrr earlier than expected. 2. $AAPL goes with $INTC for semi production, which is a major shift cause they normally go with TSM. Made in America go like Intel go brrr. 3. $NVDA Vera Rubin reportedly makes changes to cooling architectures very recently. "Taiwan's thermal management suppliers are emerging as one of the fastest-growing segments in the AI hardware ecosystem" - From Last Month. "Vera Rubin server architecture is expected to drive a fundamental shift in data center cooling and system design" Will cover thermal ecosystem later, maybe it's time to take a look? 4. 2D NAND shortage spirals after Samsung, Micron, and rivals exit market Macronix, Windbond go brrr. implications for GigaDevice and other niche players. 5. "Big Tech reportedly offers to fund SK Hynix fabs and EUV" - Memory that badly bottlenecked that mag7 wants to pay for it, so $MU, SK Hynix, Samsung go brr. 6. $TSM 2026 net revenue $12.6B for April 2026. Revenue up 30%, Semis keep going brr. 7. Anthropic needs compute -> SpaceX. So implications for compute demand is extreme here which is BRRR $NBIS and others. But it's very interesting they sidestepped Neoclouds and went with SpaceX. 8. "SKC to Accelerate Mass Production of Glass Substrates for U.S. Clients by the End of the Year" "the end of the year, ahead of its original plan, it has been announced" Glass Core substrates players like $LPK for mass production and other related players like SKC go brrr. Glass timelines moved up. heavy brrr glass. 9. "Power chip shortages deepen as AI server demand and GaN battles escalate" Maybe time to look into the power chip bottleneck anon? 10. "Adata said DRAM and NAND flash contract prices will each climb more than 40% in the second quarter of 2026" Another positive for $MU, SK Hynix, Samsung, $SNDK, and others.

Meet Waldo: Glean’s first agentic search model. Built on @nvidia Nemotron 3 Nano and post-trained for search planning, Waldo figures out how to break down a query, which tools to call, what to read next, and when it has enough evidence to hand off.

@ashwingop Already exists @glean is leading the way!

Stop rebuilding the same workflow from scratch. Glean Skills package your team's know-how so Glean executes with context every time. Import from Anthropic, OpenAI, Github, or Cursor. Or build one through chat or voice.

GPT-Realtime-2 from @OpenAI is now live in @Glean’s real-time voice capability! From our evals, it delivers a 42.9% relative increase in helpfulness over its previous version. It tracks complex conversations and synthesizes context from Glean agents more reliably, so conversations feel natural and like real collaboration on company work instead of generic back-and-forth. Talk it out with Glean.

@glean @Jason get @glean on TWIST!

20x growth in AI usage, 25% better performance on complex tasks, and faster time to completion. This is the impact when enterprise AI is grounded in your company's context 👏

Your favorite AI coworker just got a major upgrade 🙂‍↕️ → Personalized activity cards: proactively tells you what to act on next, based on everything already in motion across your work → Canvas revision review: every edit shows up inline, so you always know exactly what changed → Library: everything you create with Glean is saved and searchable so you can find and reuse it later

Productivitymaxxing with Assistant.  Now, you can run and delegate multiple workstreams at once. Bulk write tools → handle repeated tasks in one go Adaptive reasoning → adjust depth and approach based on the task Task delegation → hand work off to the right person or agent

@aleabitoreddit am I missing something? Did $SIVE move to a different exchange?

@aleabitoreddit Have you tried @moomoo ? Looks like most tickers r there and a better app experience imo. I have IBKR as well, it’s just so old school and boring but I know the point is to make money and not look pretty lol

US retail investors should switch from $HOOD to $IBKR for international equities. I’m not sure why anyone still uses Robinhood for investing anymore. Unless you have $50 and no clue what you’re doing. They had their chance to innovate but focused on Melania Coin integrations

@aleabitoreddit thoughts on Ajinomoto (2802.JP) ?

I’m excited to share that I’ve joined Glean as an AI Outcomes Manager. I’ve been passionate about AI for a long time, but what excites me most isn’t just the technology itself — it’s helping teams apply it in practical ways that drive real outcomes. That’s a big part of what drew me to Glean: the opportunity to join a company that helps organizations unlock more value from their knowledge, workflows, and people. I’m grateful for the warm welcome so far and energized by the opportunity to learn, contribute, and work alongside such a talented team. I’m looking forward to this next chapter. #AI #ArtificialIntelligence #CustomerOutcomes @glean

@APompliano @grok what are the top 10 stocks set to benefit from this

Wow. The White House just announced that grid infrastructure is essential to national defense. This includes transformers, transmission lines and conductors, substations, and high-voltage circuit breakers. Companies working to electrify America will have a big tailwind.

Teaching means forming people to listen to the heart, to inner freedom and the capacity for critical thinking. In this dynamic, faith and reason neither ignore nor oppose one another. They should both be traveling companions in the humble and sincere search for truth.