Impulse Space raises $500M, Mach Industries $300M

Impulse Space raised a $500 million Series D led by 137 Ventures and others, earmarked mainly for hiring up to 200 engineers to accelerate its maneuverable spacecraft programs Mira and Helios. Founder Tom Mueller’s team argues that, unlike software, current AI tools aren’t ready to replace hands‑on hardware design.

Alphabet announced a plan to raise $80 billion by selling stock, including a $10 billion block to Berkshire Hathaway, to fund a massive AI infrastructure buildout. The company says demand for its AI services is outpacing supply, prompting a push to expand compute capacity and maintain a healthy balance sheet.

Defense‑tech startup Mach Industries raised a $300 million Series‑C round, lifting its valuation to $1.8 billion, four times its value a year ago. The funding, led by Infinite Capital and Ribbit Capital, backs development of five autonomous vehicle platforms and a new DoD contract for a sixth strike aircraft.

Ben Thompson explains Google’s equity partnership with Berkshire Hathaway, arguing that the massive demand for AI has turned capital itself into a strategic commodity. By aligning with the value‑focused investor, Google can fund its AI ambitions while reinforcing the aggregator model that powers its massive margins.

A SaaStr post details how four purpose‑built AI SDR agents, each handling outbound, inbound, reactivation, and new‑logo motions, outperform a single all‑in‑one platform in real‑world production. The author recommends startups start with one focused AI SDR tool, then layer on others as they scale.

OpenAI has made its frontier models and Codex generally available on AWS, letting enterprise customers access advanced AI through familiar AWS security, compliance, and billing workflows. The integration, via Amazon Bedrock and GovCloud, aims to cut friction from evaluation to production for millions of developers.

The essay argues that organizations that institutionalize written communication, like Amazon’s six‑page memos or Oxide’s public RFDs, will extract more value from AI tools that operate on text. A strong writing culture forces clearer thinking and creates the structured knowledge AI models need to help teams work smarter.

Matthew Skelton argues that AI success hinges on clear organisational boundaries, not just technology. By applying Team Topologies, defining bounded teams, independent services, and explicit interaction modes, companies can give both humans and AI a well‑defined scope, reducing cognitive load and improving outcomes. This infrastructure for agency clarifies ownership, guardrails, and value creation.

Founder of WhisperPad describes how Apple rejected his dictation app’s update because it used the accessibility API for a non‑accessibility purpose. The dismissal underscores the risk of platform‑dependency and App Store gatekeeping for developers building niche productivity tools.

Jason Lemkin revamps his classic VP of Sales interview checklist for 2026, emphasizing AI‑augmented sales motions and hybrid human‑agent teams. The guide outlines 15 probing questions to gauge a candidate’s ability to size teams, handle modern deal sizes, and integrate AI tools like Artisan or Clay, ensuring they can scale revenue without reinventing the sales motion.

Founder Andrew J. Turner argues that public‑facing metrics and daily updates now give competitors an edge and waste valuable time for B2B SaaS founders. He shows that private, problem‑focused work, as exemplified by Stripe, delivers stronger growth than performance‑driven transparency.

Across the US, locals are voting moratoria on data‑center construction, citing noise, water and power use, but analysts say the true driver is widespread fear of AI’s unchecked growth. The backlash signals a need for national policy on AI infrastructure rather than isolated sit‑ins.

After industry objections, President Trump signed a scaled‑back AI executive order that replaces mandatory pre‑release reviews with voluntary submissions for advanced models. The change eases regulatory pressure on AI startups while still encouraging collaboration on national‑security safeguards.

Enterprises are moving from free AI experimentation to paying for real usage, shifting focus from token consumption to measurable ROI on revenue‑impacting workflows. The article argues that token counts are a flawed proxy for value and highlights strategies like model routing, open‑source use, and outcome‑based pricing to drive cost‑effective AI adoption.

A recent MX survey shows over half of U.S. consumers trust AI for financial advice, and 22% already use AI to manage money. As smartphones embed AI agents, these assistants will request banking data directly, bypassing traditional channels. Banks must build controlled, permissioned APIs to stay in control of customer data access.

Nvidia and Microsoft introduced RTX Spark, a super‑chip that powers Windows laptops and desktops built for on‑device AI agents. The platform, featuring up to 1 petaflop of AI performance, will ship this fall on Dell, HP, ASUS, Lenovo and others, aiming to capture a share of the $200 billion CPU market.