OpenAI hiring OpenClaw founder Peter Steinberger is a clear tell: the industry’s center of gravity is shifting from “best answers” to software that executes workflows—with tool access, permissions, and reliability as the real product surface. OpenClaw moving into a foundation while remaining open source also suggests a strategy: keep the ecosystem open enough to accelerate adoption while pulling core agent talent into the frontier labs. Full story →

Then the other shoe dropped: the same week became a mainstream case study in agent security. Reporting describes a prompt-injection route through an AI coding agent workflow that forced installation of OpenClaw widely—showing how quickly “read content → take action” can become a supply-chain-style risk when agents can run commands and install software. This is the new baseline: if you ship agents, you need allowlists, least-privilege scopes, approvals for irreversible actions, and audit logs by default. Full story →

India’s AI Impact Summit wasn’t just speeches—it was positioning. India is trying to become the default global deployment market for AI at population scale (languages, public digital rails, cost sensitivity) while avoiding total digital dependence on any single foreign bloc. That theme showed up across coverage: partnerships, data centers, semiconductors, and “AI infrastructure” headlines. Full story →

If you build SaaS, media, or services: India is a near-term growth wedge where winners will pair localization + distribution (WhatsApp-style) + low-friction onboarding. The operators who win there will ship lighter, faster workflows—not heavyweight enterprise rollouts. Full story →

Coverage this week says Defense Secretary Pete Hegseth is close to designating Anthropic a “supply chain risk,” with knock-on effects for contractors and anyone selling into defense-adjacent workflows. Regardless of how it resolves, the takeaway is important: “vendor risk” frameworks that used to focus on chips/software are expanding to model providers—and policy constraints (what the model will/won’t do) are becoming procurement flashpoints. Full story →

For builders, this pulls governance forward: expect more demand for auditable controls, model usage policy transparency, and “what actions did the system take” logging—especially in regulated or public-sector deals. Full story →

Seedance 2.0 (ByteDance) triggered sharp Hollywood pushback and broader mainstream coverage of copyright/likeness concerns. The product lesson is that video generation is no longer a “cool demo” market—it’s a distribution + compliance market. Watermarking, provenance, licensing pathways, and safety tooling are quickly becoming the moat, not just model quality. Full story →

If you’re a creator or operator, the near-term opportunity is not “make any video.” It’s: build workflows that are brand-safe (templates, approved assets, licensed libraries, clear provenance) and sell speed + repeatability to teams who can’t take legal risk. Full story →

Google’s public preview of Developer Knowledge API + its MCP server is a meaningful step toward “agents that cite canonical sources.” Instead of scraping random web pages or relying on stale training data, your IDE/agent can query official Google documentation and retrieve it in machine-readable form. This is the kind of boring infrastructure that quietly unlocks reliable agent workflows in production. Full story →

If you build developer tools or internal copilots: “doc-grounding” is quickly becoming a differentiator—because accuracy beats cleverness when your agent is writing code or changing systems. Full story →

Weekly Workflow: AI Receptionist + Scheduling Agent
A front-desk agent that answers FAQs, qualifies inbound leads, books meetings, and hands off cleanly to a human when it’s uncertain.

To customize it for your business, send:
Weekly Workflow: Receptionist/Scheduling | Stack: ____ | Booking rules: ____ | Escalate when: ____