Metre Lemoisson
187 posts

Metre Lemoisson
@LemoissonMetre
Founder https://t.co/UqD1hvxiKK | Building AI-first Products for Africa like https://t.co/mxYmBqSQR8 & https://t.co/b7l9QxIuPq | Full Stack Lead (PHP, React, TS)


I asked Claude to look at startups.rip the site with details of YCombinator startups that didn't make it and this was what it found: Here's what stands out when you look across the graveyard on startups.rip, combined with the broader failure research: 1. Premature platform ambition — winning a niche, then abandoning it Posterous is the clearest example: it launched with a genuinely elegant premise, drove 30% month-over-month growth, and hit 15 million monthly visitors — then abandoned its winning position to fight a social media war it was never built for. Feature accumulation eroded the product's clarity. By March 2012, monthly visitors had collapsed from 15 million to 1.33 million. This pattern — find a sharp edge, then blunt it chasing a bigger vision — recurs constantly across the list. 2. Timing mismatch (too early, not too wrong) Loopt is the canonical case: Sam Altman built what we now take for granted in apps like Google Maps, Life360, and Find My — but in 2008 the smartphone ecosystem, social norms around location sharing, and carrier infrastructure weren't ready. The idea was right; the moment was wrong. Looking at the startups.rip list, this appears repeatedly in the community/social cluster — Openland, Allo, Tress, Quest — products that might have found audiences at different points in the cycle but launched into a market not yet ready or already saturated. 3. The "feature, not a company" problem — especially brutal in the AI wave The W22–S23 cohort on the list is telling: Flike, Parabolic, Fabius, CoffeeAI, Dialect, Mercator, Demo Gorilla — almost all AI-wrapper companies doing one thing (AI sales emails, AI customer support, AI outreach, AI forms). When ChatGPT can do 80% of what your product does for $20/month, your margin for differentiation becomes razor-thin. These companies weren't solving hard problems — they were building thin layers on top of foundational models that rapidly caught up with them. 4. Marketplace leakage — the disintermediation trap Tutorspree's business model had a structural flaw baked in: once a tutor and student connected on the platform, nothing stopped them from cutting Tutorspree out of the transaction. The company was taking 50% of tutor fees, giving both sides a massive incentive to bypass it. This same trap hit many marketplace plays on the list — Gigster, The Muse, Creative Market — where the platform creates the match but can't hold the relationship. 5. Regulatory/compliance exposure in regulated industries Call9 (healthcare at nursing facilities), LendUp (predatory lending regulations), Argovox (healthcare billing), SimpleCitizen (immigration) — companies operating in highly regulated spaces ran into the same wall. They built genuine utility but couldn't survive the compliance overhead, regulatory shifts, or the cost of becoming legitimate at scale. LendUp in particular is interesting: it raised significant capital on a "socially responsible" fintech mission but ultimately ran afoul of the CFPB for the very lending practices it claimed to be reforming. 6. Over-dependence on a single acquisition channel Tutorspree was almost entirely dependent on Google search traffic for new student acquisition — any algorithm change could significantly reduce their traffic and in return their users. As resources dwindled and the traffic dried up, there was no alternative funnel to fall back on. This single-channel dependency is a recurring killer across the list, especially for consumer and marketplace plays. 7. The acqui-hire as soft failure — talent over traction A large chunk of the "Acquired" column on startups.rip aren't real exits — they're acqui-hires: Twitter buying Posterous for the Garry Tan/Sachin Agarwal team, Apple absorbing Raven Tech, Google absorbing Bump. About 40% of YC startups ultimately achieve an exit, but a significant portion of those are acqui-hires with very small outcomes for early investors. The acqui-hire is the startup world's equivalent of a graceful funeral — the company dies but the founders land softly, which obscures how common actual failure really is. 8. Community/social products without cold-start solutions Looking at the community cluster — Openland, Allo, Tress, BlackOakTV, Quest — none found a way to solve the cold-start problem. A community product is worthless to user #1 and only marginally useful to user #100. None of these had the distribution engine, the density play, or the content moat needed to get over that hump. At YC's early stage, companies fail because they give up or the founders don't get along, and another big reason is the company is not making what people really want. In the community sector specifically, founders often build for a demographic they believe in (Black women's hair care, neighboring families, audio career advice) without finding a sustainable engine for growth. 9. The "idea whose time came and went" — wave mistiming Escher Reality (AR backends, 2017), NeoWize (ML algorithms), Pit.AI (AI for investing), CrowdAI (vision AI) — these companies were building on technology waves that either didn't materialize at the expected pace or got absorbed by the foundational layer providers (Apple ARKit eating Escher Reality, for instance). They weren't wrong about the technology, but the value accrued to the platform, not the middleware. The meta-pattern across all of it What startups.rip reveals most starkly is that YC's selection process gets founders in the door but doesn't solve the three things that actually kill companies: finding a defensible position (not just a clever insight), building a business model with structural integrity, and surviving long enough for the market to catch up to the idea. Most of the dead companies on that list had real ideas — some of the ideas are now worth billions in other hands. The gap between insight and execution, between timing and readiness, between building something people want and building something that sustains itself financially — that's where the graveyard fills up.



Introducing Code Review, a new feature for Claude Code. When a PR opens, Claude dispatches a team of agents to hunt for bugs.

🚨Claude Opus 4.6 wrote vulnerable code, leading to a smart contract exploit with $1.78M loss cbETH asset's price was set to $1.12 instead of ~$2,200. The PRs of the project show commits were co-authored by Claude - Is this the first hack of vibe-coded Solidity code?



🔴 INFO - #Chine : L’intelligence artificielle déjà utilisée pour corriger automatiquement les devoirs dans certaines écoles. Les systèmes scannent les cahiers, attribuent des notes et génèrent des commentaires détaillés sur les erreurs. Objectif : faire gagner du temps aux enseignants et renforcer l’accompagnement individualisé des élèves.






African startups should stop defaulting to AWS and Kubernetes. Get a VPS on Hetzner, deploy with Coolify, and start experimenting until you start making money. Oh, and when you do start making money, still stay there!


















