Your friends love your startup idea. ChatGPT loves it. The market might not.
Find out — with hard data, not vibes.
Saturday: top-5 ideas the market is killing.
Neurocosmetics: 30.6/100.
Press calls it "the future of beauty."
Our 6 live signals say otherwise — low search growth, zero funding last 6 months, saturated SERP.
Fluenta scores every startup idea like this.
Free preview → https://t.co/DWHpZjMkBf
YC Demo Day, June 16
The biggest stage in startups opens in four days. The Spring 2026 batch puts 194 companies on stage - https://t.co/WQY1EvYyTC. We scored all 194 before they walk on, then split the batch into four groups and we're dropping one a day.
The method: 6 public signals, a 0 to 100 Launch Readiness Score (LRS). Search demand, social pain, competition, monetization, funding, urgency. Public data only. The outside view every investor in that room runs before the meeting.
Group 1 of 4: Agent Infrastructure. The picks and shovels. 55 startups building the rails everyone else builds agents on. Group average: 50.3.
Highest scored:
1. Kuli, 65.5, automated influencer marketing - @maradoh22
2. Armature, 63.2, product analytics for agents - @Totzenberger
3. Superlog, 63.2, self-healing logging - @superlogYC , @ArseniySvist , @nicolomagnante
4. Memory Store, 62.4, memory layer for agents - @memorydotstore , @IshitaJindal17 , @diwanksingh
5. Netter, 62.4, data ops for mid-market
Lowest on the outside view:
51. Hub xyz, 38.2, real-world AI datasets - @hubxyz, @xarmin@tim404x
52. The Company Company, 38.2, autonomous company - @thecompanyai, @juliuslip
53. General Instinct, 38.0, physical-AI deployment - @BillJiao930@Guanming717
54. Minicor, 37.7, self-healing desktop agents - @minicor_ , @faizchishtie@sahee_d
55. RentAHuman, 32.7, real-world tasks marketplace @rentahumanx, @AlexanderTw33ts
If the score reads low, it usually means the data on 6 public signals (search demand, social pain, competition, monetization, funding, urgency) is either poor or hardly available. Could be worth closing that gap on stage on June 16.
3 things the data says about this group:
1) Some are building ahead of demand, some aren't, and search alone won't tell you which. 33 of 55 sit under 500 searches a month (nobody googles "agent memory" yet). But a few have real pull: Kuli and Netter clear 11k at 80 to 94% purchase intent, and the biggest raw number, Runtime's 311k, is mostly generic "runtime" spill, not category demand. The caveat that matters most: this is public search only. Infrastructure sells through private B2B motion, so a low score can sit on top of signed LOIs, paid design partners, or institutional pre-orders the outside view can't see. If that's you, that private demand is the single strongest thing to put on stage June 16.
2) One bet, 55 ways, and from the outside every idea could have the same shape. Half literally build "for agents," 71% sit in dev tools or AI automation, median 10 direct competitors each. Strong willingness to pay, crowded competition, and weak funding, not because these founders can't raise, but because the capital already came to some of these categories in 2020 to 2022 and got absorbed, not broken out. The batch converged on one thesis and now competes with itself.
3) The strongest signal is the one that lies. Monetization scores highest across the board, people pay. But that score measures whether a market pays, not whether you can afford to win it. On the real CAC vs payback math, 14 of 49 priced startups need 12+ months to earn back one customer, and 13 of those 14 scored STRONG on monetization. So the question isn't "is there a business," it's "is this a company or a feature." That's what you get pushed on June 16.
How to use it:
- Founders in the batch: find your card, look at your lowest of the 6 signals. Those could be the questions coming. Worth prepping now.
- VCs and angels: want the full breakdown on any project, competitors, the CAC vs payback math, search demand, etc? Check on https://t.co/lM4X8lkhCH. DM us to uncover the paywalled parts as well. The reports are done, so no additional costs here. Or use Fluenta MCP to pull all reports in one batch and do a thorough analysis on each one in Claude, Cursor, etc.
- Everyone not in the room June 16: the high-LRS names are the ones who’d mostly likely get funded, and who get cloned in every local market inside 90 days. Browse the board for your business inspiration.
Tomorrow, Batch 2 of 4: The AI Workforce. The agents coming for entire job functions.
Tagging the teams above in case you want to grab your report. No hidden subscription, no signup gate - the analysis is already done, the file is yours to pick up. DM here or email [email protected] and we'll send it same-day.
If the score reads you wrong, that gap is the thing to close on stage.
We spent days cleaning, transforming, and aggregating a month of startup-idea data. It gave us a hairball.
Then we read the hairball: 16 ideas that 3 or more major sources all chased in May. a16z, YC, McKinsey, TechCrunch, tangled around the same handful of concepts.
The mess is the point. This is what "market consensus" looks like up close, and consensus means crowded.
So how do you read this: as a decorative ornament, or as 16 traffic jams with a waiting list?
Full State of Business Ideas May Report here - https://t.co/IHTgLEKUtQ
@TurnerNovak The sadder part is how few founders check for traction before building. 38% of new ideas in May were AI, but under 2% of what founders paid to validate. Everyone's building the thing; almost no one's checking if anyone wants it first.
@ShaanVP Honestly Black Mirror might out-pick the real pipeline. We scored 4,092 new ideas in May: 38% were AI, but under 2% of the ones founders actually paid to validate. Everyone's generating the same AI idea; almost no one's validating it.
@edzitron Upstream evidence for this: 38% of every new business idea in May was AI, but under 2% of what founders actually paid to validate. The supply is manufactured and the conviction isn't there. Even the builders won't bet on their own AI ideas.
@agazdecki Exactly this, and the data backs it. 38% of new ideas in May were AI, but under 2% of what founders paid to validate. AI made the easy part even easier; it did nothing to the hard part, finding someone who actually wants it.
@gregisenberg That lying-about-ARR thing has a quieter cousin at the idea stage. We scored 4,092 new ideas in May: 38% were AI, but under 2% of the ones founders actually paid to validate were AI. Even the builders won't bet their own money on the category they're all pitching.
@CharlesRollet1 This matches what we see upstream - we scored 4,092 new ideas in May: AI was 38% of supply but under 10% of what founders actually validate. The over-supply mirrors the productivity gap you reported.
First edition of the Fluenta State of New Business Ideas, May 2026
tldr: The market is manufacturing the one thing founders aren't trying to build.
We collected 4,092 new business ideas across 74 sources in May and deep-scored 386 on six live market signals.
38% of every idea surfaced this month was AI.
Founder demand for AI, measured by what people actually bring us to validate: under 2%.
The feed sells AI agents. Founders are quietly trying to build services, vertical tools, and boring niche businesses.
Three more findings:
- Pain is cheap. A quarter of all ideas are burning problems nobody pays to solve.
- The whole ecosystem converged on the same 16 concepts. Consensus means crowded.
- The quiet sectors score highest: legal, HR, productivity, dev tools.
The market in one number: BIDI (Business Idea Demand Index) opened at 57 out of 100. Busy. A good month to find an idea, a hard month to fund one.
Full report, free, no signup:
https://t.co/6f6GII6TKC
Three ideas on the Fluenta board right now:
A lab-grown rhino horn business.
An AI value-at-risk pricing engine for banks.
A streetwear culture magazine.
One came from a startup database. One from BCG. One from Hypebeast.
Same six signals. Same screen.
This week's board was pulled from 80+ sources across 8 worlds that rarely meet in one place: McKinsey, BCG and Bain. a16z, Sequoia and YC. MIT, Stanford and Harvard. Inman, Hypebeast and Modern Retail. Product Hunt, GitHub and the App Store. Breaking Defense, Hacker News and Reddit.
Most idea databases scrape one or two feeds. We as humans tend to scroll the same launches everyone else already saw.
Fluenta looks different because the inputs are different. Synthetic biology next to bank-grade fintech next to a culture play, each one scored on demand, pain, competition, monetization, funding and urgency, each stamped with the exact source it came from.
The rhino horn idea scored 36.5. You can see the six numbers that say we would kill it. The interesting part is which ideas are winning, and where they came from.
Go find out.
→ https://t.co/DfRK0nkHGo
Saturday Kill List - 6 June 2026
5 ideas we'd kill before you write a line of code.
All 5 came from a different room where smart people decide what's next. A VC. A magazine. The App Store. An ag journal. A defense newsletter. Five sources, five confident calls.
From the deadest up.
1 Missile Seeker Systems - LRS 26.2 - Defense News
0 monthly searches. Source was Defense News on the Army wanting thousands of Stinger replacements. BAE, Raytheon, Lockheed and Northrop own it. Seekers go for ~$0.9M each on government contracts; BAE shipped its 1,000th THAAD seeker last year.
A procurement headline is not a market opening.
2 Robotic Crop Platform - LRS 29.4 - AgFunderNews
0 monthly searches. Source was AgFunder calling this "the golden age of robotics in agriculture." Carbon Robotics, FarmWise, Naio and Monarch already put 1,000+ machines in the field. From r/robotics: "Why do agri-robots work in demos but not the field?"
The golden age already shipped. You'd be entrant 1,001.
3 Seller Incentive Package - LRS 34.7 - App Store (TikTok Shop)
0 monthly searches. Zero category funding. Source was the TikTok Shop Seller Center trending on the App Store. Amazon, Walmart, Shopify and TikTok all hand new sellers discounts and credits free, because seller acquisition is their loss leader.
You'd be selling back what the platforms give away.
4 Culture Media Gallery Platform - LRS 34.7 - Hypebeast
0 monthly searches. Last meaningful raise in the category: 2016. Source was a Hypebeast profile of a Shoreditch gallery. Your competitors are Hypebeast, Highsnobiety, i-D and Dazed.
You'd be building Hypebeast to compete with the Hypebeast article that gave you the idea.
5 System Controls Engineering - LRS 36.1 - Lightspeed
5,060 searches/mo, but only 8% transactional intent and budget proof of 0/10. Source was a Lightspeed portfolio job posting. People research robot control; none have shown they'll pay a startup for it. Boston Dynamics, ABB, Siemens and Fanuc own it.
Search traffic without a checkbook is a syllabus, not a market.
5 ideas. 5 sources. Zero of them were "I noticed a painful problem nobody is solving."
All 5 were "a credentialed source pointed, so I pointed too."
Attention is not demand. The rubric reads the market, not the room, and the market did not show up: 4 of these 5 have zero monthly searches.
A note on what the rubric cannot see.
Our 6-signal score reads public demand and supply only. Search volume. Complaint threads. Named incumbents. Funding rounds. Monetization patterns. It does not see your private edge.
If you have a distribution channel competitors cannot copy, a co-founder with industry trust nobody else can buy, a technical moat invisible from a job board or a launch page, or a customer pipeline already warm, the picture changes.
The named incumbents above are the wall. Your edge is whether you brought a ladder. The rubric scores the wall. Only you know if you have the ladder.
If you do, the kill argument is wrong. Tell us what we missed. We will re-score.
Want your idea graded on the same 6 signals before you sink a quarter into it?
$7. ~10 min. Human-readable report.
→ https://t.co/kT2HOUX1V6
More kills next Saturday.
Disagree with a call? Reply with which one we killed unfairly. The strongest pushback gets a follow-up post.
Fluenta MCP is live
One API key. Your AI agent now has the full Fluenta surface inside Claude Code, Cursor, or Codex.
Stop tabbing. Start asking.
After signup (email verification, key from your dashboard):
→ Show today's fresh business ideas and new collections.
→ Show ideas with LRS above 60.
→ Find ideas in real estate. Any sector works. Search runs on context, not strict tags.
→ Show the top 5 ideas by search demand or by recent funding.
→ Compare idea X and Y on LRS metrics. Show me where the gap is.
→ Save this idea to my pipeline. Or remove it.
→ Pull the full report on the top Trending Now idea. Download as txt or md.
→ Score my idea (whatever yours is) with Fluenta X-Ray.
Or in free form, no commands: "I'm thinking about a new business. Here are the candidates I'm weighing. Which one gets me to first revenue fastest, and why? Use Fluenta MCP to check fresh ideas and compare."
Free tier is real, not a teaser. You get a daily-refreshed search slice filtered by LRS. The day's #1 Trending Now idea is fully unlocked. Full report, downloadable as txt or md, processed inline in your chat. Every metric, every link, every named competitor, every business model, real user complaints with source URLs.
You can also delegate. Set your agent to pull MCP daily and drop fresh ideas into your chat (Notion, Slack, wherever you live). Open it in the morning, the day's curated batch is already there. All on the free tier.
Paid tier is $9/mo. Full access to every idea, every sector, every collection. We are keeping it wide open while the base is growing. We will rate-limit later, before someone tries to vacuum the database in one afternoon.
For your own ideas: run the sandbox preview free. The depth is noticeably less than the paid full run. Smart move before you commit credits: download a free Top Trending report first, see the actual depth, then decide if you want the same on your own idea.
Install in 90 seconds. JSON snippet, API key, restart your client.
Docs: https://t.co/y2JyBBQT2a
We ship new functionality every week. Reply with what you want first, or what is missing. We prioritize what you actually use.