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Everything / RAG and memory / Embeddings

Trend in RAG and memory · tag embeddings · through Sep 2026

Embeddings Growing

On TutorHero's Everything Index, Embeddings is growing on GitHub: 0.89 of every 10,000 new public repos over the last three months (843 a month), +197% vs a year ago. The 12-month forecast says rising (+41%). By the end of 2032, lines in the same state ended between 0.01x and 2.5x of where they started (median 0.54x).

Per 10k new repos0.89843 new repos a month
Year over year+197%3 months: +8%
Next 12 months+41%80% band +19% to 5x
2032, median of history0.54x90% of past cases: 0.01x to 2.5x
Attention0.66%of new stars, -32% in a year
Jev 2032 callnot read yetonly top trends are sent to Jev
Share on X

Since 2019, and the range to 2032

0.010.030.10.3131020192020202120222023202420252026202720282029203020312032Range to 2032 (history of similar lines)Stable Diffusion releasedChatGPT launchesGPT-4Llama 2, open weightsModel Context ProtocolDeepSeek-R1Claude Code previewHigh 2.21Median 0.48Low 0.01

New repos per 10,000 (3-month average, log scale)12-month forecastRange to 2032: middle half and 90% of past similar lines

The range is not a forecast of this line: it is what GitHub lines in the same state (more than doubled its share of new repos in a year) did 1 to 5 years later, 2019 to 2026, applied to today's level. Past 5 years it is stretched, not measured. Checked out of time (learned before 2022, scored after), 71% of outcomes landed inside the 90% range, so read it as wide. Open it in the Everything chart.

Week by week

Last week333 new reposOct 12 to Oct 18 · +4% against the field
Last 4 weeks▼ -16%913 new repos, against the 4 weeks before and the field
AprMayJunJulAugSepOct

New public repos with the embeddings tag each week (Monday to Sunday, UTC). The outlined bars, last week included, are still filling in, as tags are often added days after a repo is created, so their height will grow a little. "Against the field" divides the change by what the typical tag did, so a wave that lifts every tag does not count. Hover for the numbers.

Built vs talked about

Hacker News8 stories a month-42% share of HN vs a year ago · titles with "embeddings"
Talk vs buildingTalk and building in stepHacker News -42% vs GitHub new repos +197% over the year, compared with the typical trend

Each line is its own share (of all new GitHub repos, all Hacker News stories, all English Wikipedia views, all new stars on the repos we track), shown as a share of its own peak, so the timing and shape compare even though the units differ. Hover for the counts. Tap a name to hide or show a line.

What it means

Studentslearning it, contributing, getting hired
  • Worth learning now: Embeddings is growing, +197% share of new GitHub repos vs a year ago.
  • Start by reading Tencent/WeKnora (+10.7k stars in 3 months) and thedotmack/claude-mem (+2.7k stars in 3 months).
  • People to follow: Abdur Rahim, Ming Xu (徐明), Qdrant.
Founders and builderswhat to build next
  • Getting crowded: new repos +197% but attention -32%, so each new project competes harder for stars.
  • 6.70 new stars per new repo over 3 months, vs 8.50 for the typical trend: about average demand per project.
  • The 12-month forecast for its share: +41% (Rising).
  • Talk and building in step: Hacker News -42% vs new repos +197% in a year, close to the typical trend.
Investorswhich fields deserve research time
  • History: of past GitHub lines that more than doubled its share of new repos in a year, 61% had a smaller share 3 to 5 years later and 8% at least doubled.
  • Attention: 0.66% of new stars on the repos we track, -32% in a year.
  • Hacker News: 8 stories a month, -42% share in a year.
  • Not investment advice: this measures what people build on GitHub, not any company.
Developers choosing toolswhich tools to adopt
  • Most-starred tools here lately: Tencent/WeKnora (vouched), thedotmack/claude-mem (vouched).
  • The field is growing, so expect new tools and fast changes; pin versions.

Repos carrying it now

Tencent/WeKnoraOpen-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.+10.7k stars in 3 months · vouchedthedotmack/claude-memPersistent Context Across Sessions for Every Agent – Captures everything your agent does during sessions, compresses it with AI, and inject+2.7k stars in 3 months · vouched
RyanCodrai/turbovecA vector index built on TurboQuant, written in Rust with Python bindings+730 stars in 3 months · organic
codedogQBY/ReadAnyAI-powered cross-platform e-book reader with semantic search, RAG chat, local vector store, notes, TTS, and WebDAV sync.+406 stars in 3 months · organic
NirDiamant/RAG_TechniquesThis repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebo+362 stars in 3 months · vouched
InsForge/InsForgeThe all-in-one, open-source backend platform for agentic coding. InsForge gives your coding agent database, auth, storage, compute, hosting,+279 stars in 3 months · unclear

People building it

More in RAG and memory

Questions

Is Embeddings growing on GitHub?

Yes. Its share of all new public GitHub repos is +197% vs a year ago and +8% over the last three months (Sep 2026). Phase: Growing.

How many new Embeddings repos are created each month?

About 843 new public repos a month carry the embeddings tag (three-month average to Sep 2026), or 0.89 of every 10,000 new repos.

What will Embeddings look like in 2032?

Nobody knows, and we say how much. Of past GitHub lines that more than doubled its share of new repos in a year, the middle half had between 0.14x and 1.27x of their share 3 to 5 years later, and 61% ended smaller.

Is Embeddings more talked about than built?

Talk and building in step. Over the year its share of Hacker News stories moved -42% while its share of new GitHub repos moved +197%. New repos grew faster than talk for most AI trends this year, so the label compares it with the typical trend: about 1/1.4 of the talk per builder of the median trend.

Not investment advice. Measurements of what people build and star on GitHub, a statistical forecast, base rates and a model's reading of them. Nothing here is about any company's revenue, valuation or stock.