et al.

What do they actually do

et al. is a mobile app (in beta) that pulls together the newsletters, research papers, podcasts, and articles you already follow, uses large language models to extract short takeaways, and shows them in a personalized, scrollable feed. Each insight links back to the original so you can decide quickly what to read in full YC profile et al. homepage.

Right now they are running a closed/early beta and actively recruiting testers. The team is two founders based in the Bay Area, iterating on personalization and source integrations ahead of a broader release YC profile YC jobs page et al. homepage.

Who are their target customer(s)

• Researchers and academics tracking new literature: Papers and alerts are scattered and long; they need quick, reliable signals to triage what merits a full read. A concise feed of insights with links back to the paper speeds screening and follow-up YC profile et al. homepage.
• Product managers and startup builders: They must monitor blogs, newsletters, and podcasts while shipping; fragmented sources cost time and lead to missed updates. A single feed of bite-sized takeaways reduces context switching YC profile et al. homepage.
• Investors and industry analysts: They synthesize trends across niche newsletters and long reports and need high-precision highlights with provenance. Short insights with links back to evidence help surface leads quickly YC profile et al. homepage.
• Consultants and busy knowledge workers: Client work demands staying current without deep-diving every update. A scrollable feed of short insights preserves time while keeping verifiable source links handy YC profile et al. homepage.
• Graduate students and lifelong learners: They subscribe to many newsletters and follow podcasts but need help prioritizing and building sustained knowledge. Personalized insights plus read-more links turn scattered content into a daily habit YC profile et al. homepage.

How would they acquire their first 10, 50, and 100 customers

• First 10: Founder-led outreach to researchers, PMs, analysts, and newsletter authors in their networks and via YC; offer free beta with concierge onboarding where a founder connects sources and tunes the feed, and ask for blunt feedback plus two peer intros YC profile et al. homepage.
• First 50: Post example insights and short demos in discipline-specific Slack/Discords, academic lists, PM groups, and on Twitter/LinkedIn; send personalized invite links to responders and turn the best testers into short case studies added to the signup page.
• First 100: Do lightweight partnerships with niche newsletters, research groups, or VC/analyst shops to provide an insights sample and a simple join flow; run webinars showing real content, targeted LinkedIn outreach with field-specific examples, and a simple referral perk to keep the pipeline active.

What is the rough total addressable market

Top-down context:

The audience for curated knowledge feeds is large and growing: podcast listening and online audio usage in the U.S. hit record highs in 2024, per Edison Research’s Infinite Dial report, indicating sustained demand for summary-friendly formats Edison Research. Newsletter ecosystems are also sizable, with Substack reporting more than 4 million paid subscriptions and tens of millions of weekly active readers across its network Substack post Substack About. For research-heavy users, there are roughly 8.8 million researchers worldwide in R&D roles, a proxy for one core segment Science|Business Our World in Data.

Bottom-up calculation:

As an initial wedge, if et al. charges about $10 per month and converts roughly 100k researchers/grad students, 60k PMs/builders, and 40k analysts/consultants over time, that is ~200k paying users at ~$120 per year, or about $24M in bottom-up TAM for the early target segments.

Assumptions:

• Pricing at $8–12 per month ($96–$144 ARPU per year).
• Conversion of 2–5% from English-language, mobile-first newsletter/podcast power users within the identified niches (researchers, PMs/builders, analysts).
• Excludes casual readers; focuses on users who already consume research/newsletters/podcasts regularly.

Who are some of their notable competitors

• Readwise Reader: Read-it-later and highlights app that aggregates articles and newsletters and includes AI summarization; overlaps on aggregation and takeaways but centers on saving/highlighting and long-term review, not a daily insights feed Docs.
• Refind: Personalized discovery app recommending articles and sending daily link sets; competes on “one place to see relevant links,” but focuses on recommendations rather than LLM-extracted insights from a user’s own subscriptions.
• Matter: Mobile/web reading app for saving articles and newsletters with text-to-speech and an AI co-reader; emphasizes clean reading and audio as much as automated summaries App Store.
• Upword: AI research/summarization tool for documents that generates condensed summaries, notes, and Q&A; more about deep document workflows than a continuous personalized feed Listing.
• Consensus: AI search engine for academic research returning short summaries with evidence; focused on scholarly search and provenance rather than aggregating a user’s newsletters/podcasts into a daily mobile feed.