Skip to main content

Startup Autopsy Laboratory

Your idea has a fatal flaw.
Find it for $1.

Six months from now, you'll have either a product or a lesson. Four AI examiners tell you which — before you build. Verdict in 60 seconds. No account.

Latest verdict

A $20 Shelly plug and a one-time purchase undercut "couple hundred dollar" timers tenfold, if the Wi-Fi timing is actually accurate.

Case no.

4471

Examiners

4 agents

Status

Examination complete

Subject — idea submitted

“An app that reminds you to drink water”

Preliminary scan — agent findings

Market

No moat detected

Tech

Commodity execution

Finance

Negative unit econ

Timing

Market saturation

Cause of death— tap to reveal

“There are 200 of these on the App Store. The good news ends there.”

ROASTED
2/10

No account · No signup · Verdict in 60 seconds · $1 flat · 2 min vs. 6 months · 2-min walkthrough

Buying for a team or friend? Get a case bundle →

Live demo

What a roast actually does to an idea

Idea in. Fatal flaw out. Pivot clear.

01 — Idea submitted✓ received

“An app that reminds you to drink water and tracks your daily intake”

examining
02 — Market examinerfatal flaw

There are 200 of these on the App Store. The top three are free. Apple Health tracks this passively. You're asking someone to change a habit for a problem they've already accepted.

pivot
03 — Founder insight

"Daily water tracker for kidney stone patients."

Their doctor told them to drink 3L. They have a medical reason to care. Charge accordingly.

Loops automatically · yours takes 60 seconds

Free preview — no payment needed

How good is your idea, really?

Full panel ($1)

Enter your idea above to get started

0 ideas autopsied
avg score 4.6/10
only 0% survived
no account · $1 flat

The full range

Not every idea gets roasted

The verdict depends on the idea. Here's what each outcome looks like.

SHIP IT
8.5/10

“IFTA compliance software for owner-operator truckers — automates fuel receipts, mileage logs, and quarterly state filings. $49/month.”

“Mandatory compliance, captive audience, no modern SaaS incumbent. The regulatory moat is real.”

Market

IFTA compliance costs owner-operators 8–12 hrs/quarter. TruckingOffice and Q7 are legacy desktop. No modern SaaS owns this niche.

Finance

$49/mo with near-zero voluntary churn — compliance software is involuntary. CAC via trucking Facebook groups runs sub-$40.

Why it passes

Regulatory moat, near-zero voluntary churn, reachable niche via trucking communities. No fatal assumption in the analysis — the panel cleared it.

DECENT
6.5/10

“AI meeting summaries for solo consultants — auto-generates client-ready notes from recordings. $12/month.”

“Right pain, wrong market. Otter.ai owns the generic case. The moat is in the liability, not the transcription.”

Market

Generic meeting notes is saturated. But financial advisors and lawyers need compliance-grade records — a legal audit trail, not just a summary.

Timing

SEC and FCA record-keeping requirements tightened in 2024. Regulated consultants are actively shopping. Window is open.

Pivot

Narrow to compliance-grade records for regulated advisors (financial, legal). Double the price. The audit trail is the product, not the summary.

ROASTED
2.5/10

“A social network for dog owners — share photos, find local playdates, discover dog-friendly venues.”

“BarkHappy, Dogster, and Meetup.com already lost this war. Facebook Groups won by default.”

Market

Five funded attempts at this exist. All pivoted or shut down. Facebook Groups solve the core use case for free with the existing audience already there.

Finance

Niche social networks require critical mass before any monetization. CAC exceeds $80 before the first dollar of revenue. Math does not work.

Full panel — example output

Here's exactly what $1 gets you

A real analysis, shown in full. Every agent finding. Every red flag. Every action. Nothing cut.

Subject — idea submitted

“A subscription app that teaches kids to code through interactive games — $9.99/month”

NEEDS WORK
4.5/10

The verdict

“Code.org has $70M in backing and is free. You're selling what they give away.”

Market Agent
live data

Market is real but brutally crowded. Scratch, Code.org (backed by Bezos and Zuckerberg), Tynker ($130M+ raised), and Khan Academy dominate with free products. Your $9.99/mo is competing against free.

Tech Agent

Technical execution is straightforward — no moat in the stack. A two-person team at any of the 30+ existing edtech players could replicate your MVP in a sprint. Interactive coding games are a solved UI problem.

Finance Agent

CAC for children's apps through paid social runs $35–80. At $9.99/mo, payback is 4–8 months. Churn in kids' apps is brutal — content requirements are constant and parents cancel when interest wanes after week three.

Timing Agent

Edtech had its window during COVID lockdowns. The spike that launched Duolingo's explosive growth and pushed parents to pay for home learning tools has largely closed. School districts are now actively pushing back on screen time.

Competitors found during analysis

Live data

Code.org

$70M+ raised

Free. Backed by Bezos, Zuckerberg, Gates. 70M+ students. Your primary obstacle.

Tynker

$130M raised

Paid curriculum. Already in 100,000 schools. Direct competitor with a decade head start.

Scratch (MIT)

Non-profit raised

Free forever. 100M registered users. Sets the price expectation: zero.

Cause of death

01

Free competitors with massive backing

The market leader charges nothing. Overcoming free requires a 10x experience advantage or a different distribution channel entirely.

02

Post-COVID edtech churn

Retention data from the 2021–2023 edtech boom shows median churn of 40–60% after month two once novelty wears off. The TAM is real; the LTV is not.

03

Wrong decision-maker

Children don't pay. Parents pay — and they are already overwhelmed with subscription fatigue. The gap isn't better coding games; it's trust and habit formation.

⚠ Blind spot

You're building for the child but selling to the parent. The parent's actual fear isn't "will my kid learn to code" — it's "will they actually use this after day four." No amount of game design solves the abandonment problem without a retention loop aimed at the parent, not the kid.

Recommended intervention

01.

Call 5 after-school program directors this week — not to sell, to ask what they spend on curriculum and what problem they can't solve. You need 3 "yes, that's real" signals before building anything.

02.

Price one district pilot at $5k for 90 days, all-in. Remove the budget objection so you can test the actual product.

03.

Kill the parent-facing subscription page. Every hour spent on B2C conversion is a distraction from the channel that can actually scale.

04.

Map the procurement cycle for one specific district type (e.g. Title I schools — federal funding available, underserved, motivated). That's your wedge.

05.

Sign up for Duolingo for Schools and spend 30 minutes understanding exactly what they don't offer. That gap is your pitch.

Get this for your idea → $1

Or see a free sample first

Case files on record

Recent examinations

Full archive →
Case #0001DECENT

Subject

“I turned my iPhone and a $20 smart plug into an f-stop timer https://peterszentkiralyi.eu/darkplug/ Founder's Show HN post: I am a film photographer and do some darkroom printing and always wanted one of the proper, advanced f-stop timers, but never really wanted to spend a couple hundred dollars on one. Eventually I figured my phone was already perfectly capable of doing the timing, it just needed a way to switch the enlarger. So I built Darkplug around a cheap smart plug. The app controls the enlarger over the local network and does regular timing, f-stop timing, test strips, has an intuitive dodge/burn workflow, split grade (2 timing channels) and paper development timing. I’ve been using it for a few months in my improvised bathroom darkroom. Fair warning: the app was blindly vibe coded using Codex and Xcode. Landing page content (Darkplug – Péter Szentkirályi): Darkplug – Péter Szentkirályi # Darkplug A darkroom timer for iPhone that controls your enlarger. Control your enlarger with Darkplug and a compatible smart plug on your local network. Built for film photographers and darkroom printers, Darkplug combines precise timing, guided workflows, and a red-on-black interface designed for darkroom use. ☝️ You only need this beside your enlarger and you are set (EU model pictured). ## Designed for darkroom printing Darkplug times exposures like a classic darkroom timer, and also provides more advanced printing workflows with a very unique feature set. Whether you are making a straight print, testing exposure, planning a complex dodge and burn sequence, or doing split grade printing, Darkplug keeps the process fast and straightforward. Darkplug uses a red-on-black interface designed to stay safe to next to photo paper. The controls are simple, legible in low light, and focused on the task in front of you. The red colour was chosen and tested so that it does not fog paper. ## What you can do with Darkplug - Time straight prints - Add an optional 4-second count-in - Control the timer with F-Stop steps (Darkplug+ feature) - Run guided test strips with second or F-Stops increments (Darkplug+ feature) - Plan and execute complex dodge and burn steps with an easy to understand unique grid system (Darkplug+ feature) - Save and restore dodge and burn plans with reusable plan codes (coming soon as a Darkplug+ feature) - Split grade (two channel) print timer (Darkplug+ feature) - Use a guided paper developing timer (Darkplug+ feature) | | | | | --- | --- | --- | ## Darkplug+ Darkplug+ unlocks advanced tools and workflows for printers who want more control. It is available as a one-time in-app purchase. No subscriptions. ## How it works Set up your smart plug and note its local IP address. Make sure the plug and your iPhone or iPad share the same local network. Connect your enlarger to the smart plug. Enter the plug’s local IP address in Darkplug, and connect. Once set up, you can control the enlarger directly from your iPhone or iPad. ### Compatible smart plugs Darkplug works with the following smart plugs manufactured by Shelly: 1 - Shelly Plus Plug S Gen2 🇪🇺 - Shelly Plus Plug UK Gen2 🇬🇧 - Shelly Plug S Gen3 🇪🇺 - Shelly Outdoor Plug S Gen3 🇪🇺 - Shelly Plug M Gen3 🇪🇺 - Shelly Plug US Gen4 🇺🇸 ## Support For questions, feedback, or support, email me at fill.cans82@icloud.com. ## FAQ See here.”

Cause of death

“A $20 Shelly plug and a one-time purchase undercut "couple hundred dollar" timers tenfold, if the Wi-Fi timing is actually accurate.”

Case #0002DECENT

Subject

“Parseable, an open observability datalake, handles 100M time-series/min https://www.parseable.com Landing page content (Parseable | Observability infrastructure for fast growing teams): Parseable | Observability infrastructure for fast growing teams # Observability infrastructure for agents, apps, & systems Parseable unifies telemetry data, keeps full-fidelity data queryable. It all lives in open formats on object store with complete control and ownership THE PROBLEM Your observability stack costs more than it delivers users reported poor return on investment in their observability tooling. Primarily due to tool sprawl, lack of actionable insights, and the reactive nature of the tools. Poor customer experience Failures and performance issues are often detected by customers first, leading to frustration and loss of trust. Productive time lost Fragmented tooling and siloed data sources make it difficult to correlate events and understand root causes Rising costs eat into budgets Today's observability tools are reactive by design. You are always catching up to something that has already happened ### Predictive and proactive Modern time series forecasting model predict future trends and anomalies, giving you the power to proactively address issues before they arise ### Unified signals Single source of truth for all your observability signals. Goodbye tool sprawl! ### Compression up to 90% Columnar design for efficient storage and faster queries. Faster insights at a fraction of the cost ### Natural correlation Correlate across signals using natural language or SQL. Hello better insights and faster troubleshooting! ### Faster queries built-in Hybrid execution engine with columnar storage and indexing. Fast queries, no matter the scale ### Our cloud or yours Available wherever you are. Parseable is available as Parseable Cloud and BYOC model ### Open standards Zero vendor lock-in. From OTel to Parquet and object stores, open standards all the way Features that matter Proactive monitoring with forecasting Automatically analyze historical data to predict future trends and anomalies, enabling proactive monitoring and faster incident response Smart event parsing for filtering One click filters to quickly find the relevant data. Smart event parsing automatically extracts key information from your telemetry, making it easy to filter and analyze your data Slice and dice data with dashboards and SQL editor Power users love the SQL interface to slice and dice telemetry data exactly how they want. Use the assistant to generate SQL queries and dashboards in seconds Granular access control & federated IAM Connect with any”

Cause of death

“Parseable's 90% compression claim is a real cost wedge, but open Parquet on S3 means the moat is execution speed, not architecture.”

Case #0003SHIP IT

Subject

“Launch HN: Intuned (YC S22) – Build and run reliable browser automations as code https://intunedhq.com Founder's Show HN post: Hey HN, we're Faisal and Ahmad from Intuned (https://intunedhq.com). We’re building a platform for building, deploying, and maintaining browser automations. Customers primarily use the Intuned AI agent to automate websites that don't expose APIs. Common use-cases include scraping data, pulling reports, and submitting forms. As the website changes, our agent also helps automatically heal the automation. On Intuned, browser automations are created by an AI agent and run as code. Our infra captures the context of every run, allowing our agent to debug and maintain the underlying code - to keep the automations working over time. This way, we’re able to offer the predictability, speed, and cost of code, without the painful parts of writing and maintaining it. Here’s a demo of building a scraper on Intuned: https://youtu.be/ruZP73bK4FU Here’s a demo of using AI to maintain a project: https://youtu.be/e4R4hLdHBro Backstory: we were accepted into YC for a completely different idea. During the batch, because of Faisal's background at UiPath, several batchmates asked us whether RPA tools could fill API gaps in their products by automating websites without APIs. When it was time to pivot, we went back to those founders to dig deeper. (RPA in this context is referring to using UI automation to do complete non-testing tasks) We discovered that the actual hard problem in browser automation is maintenance. Websites change, selectors break, and failures can be painful to reproduce and fix. So in early 2024, we decided to take a crack at this problem with a handful of customers. It needed a fair number of iterations before we landed on our current code-first approach. How it works: Intuned is infra + agent, deeply integrated. On the infrastructure side, Intuned is a managed runtime for browser automation code. Projects are usually Playwright-based TypeScript or Python. Users can write them directly in our online IDE, or hand the work off to the agent. Either way, once deploy Landing page content (Reliable Integrations for Services with No APIs | Intuned): Reliable Integrations for Services with No APIs | Intuned # Build integrations for services with no APIs Intuned Agent builds and runs integrations for services that don't have APIs. It does this by either copying the service's network calls or automating a browser - whatever works best. Its platform then runs these integrations at scale and handles logins, captchas, and monitoring for you. ## Scrapers Create a scraper for any website - e-commerce, government portals, job boards, or anything else. Intuned Agent is the first AI Agent designed to build and maintain Scrapers. Intuned Agent generates playwright code that will be fast, cheap and predictable when it runs. Key Features: Intuned Agent - Generate any scraper from a prompt and schema, fix issues with AI when sites change. Enable self-healing and Intuned will monitor and fix your scrapers when they break. Support for authenticated scrapers - Scrape any website even if its behind authentication. Intuned Infra support helps you manage the authentication state as needed. Use Jobs to schedule the scraper runs and send the data to your backend, can be done via webhooks or another sink. Intuned observability saves records and traces for all your runs so you can debug them when something goes wrong. ## Crawlers Discover, navigate, and collect data across thousands of pages. Build crawlers that follow links, parse sitemaps, and index content - with built-in stealth, scheduling, and scale. Key Features: Use TypeScript or Python, use any framework you want. With Intuned, you can deploy any code you want. Crawl4AI support - First-class support for Crawl4AI - deploy and scale your crawlers without managing infrastructure Stealth mode - Anti-detection, proxies, and captcha solving built in Scheduled jobs & monitoring - Recurring crawls with full logs and session recordings Scalable infrastructure - Control how many machines to run on, we handle the rest ## Back Office Automation Automate internal operations in back-office systems that have no APIs. Intuned runs reliable browser automations for data entry, status checks, form submissions, report downloads, and account updates - with auth, stealth, concurrency, and monitoring built in. Key Features: Back-office workflows - Automate repetitive work inside CRMs, vendor portals, admin panels, and legacy systems. Authenticated operations - Intuned manages login sessions and auth state for systems your team already uses. Read, write, and submit -”

Cause of death

“Intuned's code-at-runtime, AI-at-build-time bet is smart, but "reliable automations" is a claim every scraper vendor makes, including Reworkd.”

Standard examination protocol

How it works

INTAKE

01

Submit the specimen

Describe your idea — what you're building, who it's for, where you stand. Rough is fine. The agents do the research.

EXAMINATION

02

Four agents convene

Market pulls live competitor data. Tech assesses execution risk. Finance runs the unit economics. Timing checks if the window is open.

VERDICT

03

Cause of death filed

A survival tier, a one-line verdict, the strongest case for your idea, the top kill shots, the blind spot you missed, founder fit assessment, and 3–5 specific actions to take in the next 7 days. Permanent and shareable.

Our forensic specialists

Why not a
generalist AI?

A general-purpose model is optimized to keep you engaged — it will validate your idea. Our four-agent panel is optimized to tell you the flaw that will kill it.

MKT-01live data

Market Examiner

Runs live competitor searches before filing a report. Only cites what it actually finds — not training-data guesses.

TECH-01

Technical Examiner

Evaluates execution risk and build complexity. Determines whether the moat is defensible or just a feature someone ships in a sprint.

FIN-01

Financial Examiner

Dissects unit economics, CAC, and LTV. Determines whether the business model survives contact with real margins.

TIME-01

Timing Examiner

Determines if the window is open, closing, or already shut. Checks whether you're early, on time, or two years late.

Common questions

Before you ask

Is this just ChatGPT with a prompt?

No. Four separate agents run in parallel — each with a specific mandate and access to live data. Market pulls real competitor funding and traction data. Finance runs actual unit economics. You get structured findings, not a pep talk.

What if my idea scores well?

Then you have evidence, not just optimism. A score of 7+ with agent-backed reasoning is something you can show a co-founder, investor, or your own doubting brain. Most ideas score between 3 and 6 — that's where the real work starts.

How is this different from asking a mentor or advisor?

Advisors give you their opinion. This gives you a structured breakdown across four failure dimensions — market, tech, finance, and timing — with live data attached. No bias, no social niceties, no 45-minute coffee meeting.

Ideas are now infinite.
Good ones still aren't.

No validation theater. No 6 months wasted.

For autonomous agents

The validation layer for the agent economy

Any autonomous agent can call /api/roast/free for a no-cost sanity check, or pay $1 via HTTP 402 at /api/agent for the full structured verdict.

"Rover already buried this with $200M. You're late."✦"Great UX. Zero moat. You'll be copied in six weeks."✦"The market exists. You just can't reach it for under $200 CAC."✦"This isn't a startup. It's a feature request to an existing product."✦"Your timing is two years off. The window opened and closed."✦"Four funded competitors. Three of them are pivoting away. That's a signal."✦"Lovely idea. Terrible unit economics. The math doesn't work."✦"You're solving a problem people tolerate, not one they'll pay to fix."✦"Quibi raised $1.75B and discovered people watch TikTok on their commute, not prestige short films."✦"Juicero built a $400 WiFi juicer. A journalist squeezed the bags by hand. Same result."✦"Notion already owns this shelf. You're building a feature, not a company."✦"The problem is real. The $29/month price point is not."✦"A $20 Shelly plug and a one-time purchase undercut "couple hundred dollar" timers tenfold, if the Wi-Fi timing is actually accurate."✦"Parseable's 90% compression claim is a real cost wedge, but open Parquet on S3 means the moat is execution speed, not architecture."✦"Intuned's code-at-runtime, AI-at-build-time bet is smart, but "reliable automations" is a claim every scraper vendor makes, including Reworkd."✦"Clubhouse proved live audio demand exists, then watched Twitter, Spotify, and LinkedIn ship the same feature to 3 billion users for free."✦"You're pitching Google Glass in 2026 — the product that literally coined the term "Glasshole" — into a market where Meta and Apple spend more on optics R&D than your entire valuation."✦"You spent $11.8M to earn $619K, then aired a Super Bowl ad for a sock puppet — Chewy did it right sixteen years later by solving logistics first."✦"WeWork burned $2B+ per year proving that signing 15-year leases to sell monthly memberships is not a tech company — it's a suicide pact with a landlord."✦"Rover already buried this with $200M. You're late."✦"Great UX. Zero moat. You'll be copied in six weeks."✦"The market exists. You just can't reach it for under $200 CAC."✦"This isn't a startup. It's a feature request to an existing product."✦"Your timing is two years off. The window opened and closed."✦"Four funded competitors. Three of them are pivoting away. That's a signal."✦"Lovely idea. Terrible unit economics. The math doesn't work."✦"You're solving a problem people tolerate, not one they'll pay to fix."✦"Quibi raised $1.75B and discovered people watch TikTok on their commute, not prestige short films."✦"Juicero built a $400 WiFi juicer. A journalist squeezed the bags by hand. Same result."✦"Notion already owns this shelf. You're building a feature, not a company."✦"The problem is real. The $29/month price point is not."✦"A $20 Shelly plug and a one-time purchase undercut "couple hundred dollar" timers tenfold, if the Wi-Fi timing is actually accurate."✦"Parseable's 90% compression claim is a real cost wedge, but open Parquet on S3 means the moat is execution speed, not architecture."✦"Intuned's code-at-runtime, AI-at-build-time bet is smart, but "reliable automations" is a claim every scraper vendor makes, including Reworkd."✦"Clubhouse proved live audio demand exists, then watched Twitter, Spotify, and LinkedIn ship the same feature to 3 billion users for free."✦"You're pitching Google Glass in 2026 — the product that literally coined the term "Glasshole" — into a market where Meta and Apple spend more on optics R&D than your entire valuation."✦"You spent $11.8M to earn $619K, then aired a Super Bowl ad for a sock puppet — Chewy did it right sixteen years later by solving logistics first."✦"WeWork burned $2B+ per year proving that signing 15-year leases to sell monthly memberships is not a tech company — it's a suicide pact with a landlord."✦