The article explains how unglamorous, overlooked industries—funeral homes, parking lots, trash hauling—generate outsized profits because competitors simply ignore them. Steve Ross built a media empire by rolling up these "invisible" businesses, and companies like Constellation Software continue this playbook today by acquiring niche software firms others dismiss as too small or slow-growing.

• Invisible companies exist in plain sight because no one searches for them: they're unknown, their data is private or buried, they're assumed to be mature dead-ends, or they carry social stigma. Since potential competitors don't know what they're missing, they never compete, leaving profits untouched.
• Standard business filters—looking for large markets, rapid growth, novel technology—screen out smaller, operationally mundane businesses that are quietly profitable. The opportunities aren't hidden; the algorithm most investors use just skips over them.
• Constellation Software has returned 34% annually since 2006 by buying boring vertical-market software businesses (marina management, funeral home records, library cataloging) that venture capitalists and other acquirers abandoned as too small. The company estimates 38,000+ similar businesses still exist.

Sakana AI released Sakana Marlin, an autonomous research assistant that takes a topic and runs up to eight hours to produce summary slides and a detailed strategy report. It uses long-horizon reasoning and multi-model control to form hypotheses, gather data, and verify findings without human input. After a closed beta with about 300 professionals, it’s now available via pay-per-use and tiered subscription plans.

• Sakana AI launched Marlin, an autonomous research assistant that runs unattended up to 8 hours to produce a ~100-page strategy report plus summary slides.
• It's built on Sakana's prior research (AI Scientist, AB-MCTS, ALE-Agent) to autonomously form hypotheses, gather data, and verify findings without human input.
• About 300 professionals from banks, consulting firms, and think tanks tested it in closed beta for market research, risk assessment, and competitive analysis.
• Now publicly available via free pay-per-use plus Pro/Team/Enterprise subscription tiers.

The article outlines five pricing strategies for AI app companies to avoid destructive discount battles. It covers recognizing available enterprise budgets, maintaining a premium position, experimenting with pricing units, offering flexible billing models, and making proofs of concept cheap without cutting core product prices.

• Enterprises often run 2-3 AI tools in parallel and aren't actually squeezing costs, so matching competitors' discounts can just leave money on the table.
• Premium positioning can command a 10-20% price cushion, but it erodes fast as new entrants ship slicker UIs or better benchmarks, so track sales cycle length, win/loss language, and churn to catch the shift.
• Changing the billing unit (per-outcome, per-workflow, gainshare) rather than cutting price breaks apples-to-oranges comparisons and reframes the conversation around results instead of "cheapest seat."