🕶️ Zero churn. $40M. Two years old.

Good morning, friends, colleagues, stakeholders in the future.

Everyone wants the model. Very few want to pay for the pipes.

That is the fight right now, how to run agents and inference at scale without bleeding out on telemetry, token costs, and brittle data connectors.

A couple tips on niching down and making tools stick, one story about a startup turning unglamorous infrastructure into a competitive moat, and a reminder that governance might matter more than another basis point of accuracy.

The boring work is starting to look expensive in the right way.

The best assistants don't multitask their attention across a hundred tools. Neither does Catch. It's an AI agent that focuses on one thing — the admin work you'd rather not touch — and does it exceptionally well.

Scheduling, flights, restaurants, follow-ups, vendors, clients. You hand it over; Catch handles the back-and-forth and comes back with it done.

No context-switching. No dropped balls. Just your admin, quietly cleared — so your focus stays on the work only you can do.

Meet the agent built for admin, and it'll be ready to work before your next meeting.

Get started at catchagent.ai — and give your attention back to what matters.

Start now for free

In AI, the glamorous part is the model; the line item that kills budgets is the data. DataBahn just raises $40M Series B to make that pain a product: an “agentic data control plane” that sits between producers and consumers, shaping which events go where and with how much context.

The bet is that the next infra layer isn’t more storage, it’s judgment at the pipe. As telemetry, cloud egress, and inference costs spike, their system and Cruz AI “data engineer” build agentic control plane logic to auto-discover sources, repair broken schemas, and enforce policy so agents see only governed, well-structured data.

The field is crowded with Cribl, Splunk, and clouds, so differentiation is neutrality and outcomes: 400%+ revenue growth, Fortune 100 deployments, tight Microsoft integrations. If AI is the new runtime, this is a wager that the real moat is the data plumbing arms-race, not the models.

🎥 James Dumoulin scales 26M-follower video network by systematizing street interviews and prioritizing human rapport over AI tools.

His crews run a tightly scripted but human-first funnel: scouts pre-qualify strangers, producers warm them up off-camera, and hosts follow a tested question tree that surfaces vulnerability in under three minutes. Every clip is then sliced into platform-native edits, seeding dozens of variants per interaction.

📬 Muck Rack finds 88% of outreach pitches deleted as editors cite original data; named by 40%, as key to survival.

In practice that means mining internal records; quotes, invoices, support tickets, returns, into six to 12 months of anonymized data tied to a clear method and publishing one specific, liftable number in the headline and opening. Those assets land roughly one in three times, then keep getting resurfaced in roundups, newsletters and AI answers long after the initial pitch dies.

🏠 Lift House founders pioneer London’s anti-hustle model as local AI startups hit $12B raised in 2026.

The house runs on explicit rituals rather than sprints, from Sunday journaling that tracks time in nature, food quality, and movement to a standing Tuesday volleyball league and recurring rooftop dinners mixing investors, researchers, and operators. Residents are screened for side hobbies and fitness habits, and founders quietly plug into SEIS/EIS-fueled angel capital while testing U.S. expansion plans from a calmer base.

🔒 Entrepreneur recounts $1M domain near-miss, urging founders to enforce MFA and registrar locks or risk total brand loss.

His checklist escalates from basics like moving registrar ownership off personal email and enforcing team-grade MFA with transfer and registry locks to tightening DNS change control, restricting admin seats, hardening SPF/DKIM/DMARC, and wiring domain access directly into offboarding and incident-response playbooks so a single stale login can't quietly redirect revenue, reset SaaS passwords, and turn the brand into a phishing asset overnight.