The infra behind this is Gigs (YC W21). They’ve spent years quietly rebuilding the telecom carrier stack: connectivity, billing, compliance, support, ops. Now companies like Block can launch mobile plans inside the products people already trust. Telecom is becoming programmable.

Proud to share that @Base10Partners has announced $850M in new capital to continue backing founders transforming the real economy, bringing total AUM to $2.6B When we started Base10, we believed the largest parts of the economy: logistics, healthcare, construction, manufacturing, financial services, and other essential industries, were still underserved by modern technology. That conviction feels more relevant than ever. AI is moving from demos into real workflows, creating enormous opportunities to help real-world businesses operate with greater speed, intelligence, and efficiency. Grateful to our LPs, founders, and the entire Base10 team for helping build the firm to this point. Excited for the future!

what is agent looping for the last two years we prompted agents one task at a time. that is starting to change instead of asking an agent to build the landing page and then driving every step yourself, you set up a loop that handles discovery, planning, the work, checking, and iterating until the goal is met looping is a setup you build. almost any agent harness can run it, it just depends on how you wire it up at its simplest, looping is one agent working on itself: > researches > drafts > checks the draft against a goal > fixes what is weak > runs that cycle again until the work clears the requirements you are not prompting each step anymore. the agent repeats the cycle for you the bigger version is a fleet looping. you give an orchestrator agent a goal, it breaks the goal into pieces, hands each piece to a specialist agent, and those specialists hand smaller jobs to their own subagents the whole tree keeps looping through discovery, planning, execution, and verification until the goal is met one agent looping is like a person redoing their own draft. a fleet looping is a whole team running a project end-to-end you create a goal, and the system runs the loop until it finishes within the reqs you set open and closed looping: OPEN LOOPING is exploratory. it still has conditions and a goal, but you give the agent or the fleet a wide space to move in. it can try different paths, discover things, build something you did not fully spec out this is the exciting end, it is what Peter and others are doing, and tbh it is where I want to spend more time the catch is cost, an open loop with real room to explore burns an insane amount of tokens. for the 90 percent of people without an unlimited budget it is not runnable yet, and pointed at projects with a loose standard it turns into a slop machine CLOSED LOOPING is bounded. a human designs the end-to-end path first: > clear goal > defined steps > an eval at each step > a point where it stops or hands back to you (and feeds back performance data) the agents still loop, but inside framework you built. it gets better every run because each pass feeds the next, and it runs on a normal budget because the path is tight. for most marketing work, closed is the one that pays off today. > the orchestrator owns the goal > the specialists own the steps > the subagents do the narrow work > an eval gate make sure its not slop

EXCLUSIVE: Notion has appointed a new board of directors in a big step towards an IPO. I spoke to co-founder @akothari about Notion's unusual board process after a decade-plus without. “How you recruit the right complementary skillset, it’s a fun game." upstartsmedia.com/p/notion-n…

Kirkland & Ellis, the world's highest-grossing law firm, is setting aside $500M to build its own AI platform rather than rely on tools available to its rivals (Financial Times) (Visit Techmeme dot com for the link and full context!)

Big news: StackAI is joining @asana!  We created StackAI to empower enterprises with secure, powerful agentic workflows that automate manual processes; Asana created the operating system for human-agent teams.  Now, we're building the place where humans and AI agents execute across every system a business runs on. Same product, same team, same brand, and way more fuel. We're just getting started. 🚀

Today, RADAR announced a $170 million Series B, bringing our valuation to more than $1 billion. We believe Physical AI can transform the 80% of global commerce that still happens in stores.  Retailers lose an estimated $1 trillion each year because their stores lack real-time visibility into what they have and where it is. RADAR is helping close that gap with 99% item-level inventory accuracy in real time, already deployed in more than 1,400 stores with leading retailers including American Eagle Outfitters and Gap Inc. brands such as Old Navy. We are just getting started.  A big thank you to our investors, including @nimble_partners, @gideonstrategic, @AlignVentures, @sound_ventures_, @ycombinator, our customers, including @AEO and @Gap Inc., @OldNavy and the entire RADAR team for helping bring us to this moment.

🌟 Congratulations to @enzo_health on raising 26M in funding! Click here to read more about Enzo Health and our partnership: n47.com/insights/ai-infrastr… CC: @vcheng11, @MatthewTCowan