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aientity · one source so far

typesafe

for backend engineers

Steadynpm
Signal score
0
as of 12d ago
Live items
1
Trajectory
⏳ Too early
needs a few more snapshots

Why this scored 0

every term, weighted
Velocity+0.0 / 40

Its fastest-moving item, measured against the pace of its own source

Acceleration+9.4 / 25

Whether that velocity is itself speeding up, as a per-hour rate

Cross-source spread+0.0 / 25

How many independent communities its own items come from

Recency+0.0 / 10

Decays to zero over 14 days, counted from when we first saw it

Saturation penalty−30.0 / 30

Subtracted once something is big and old — sized by its biggest item, aged from when we first saw it

Composite-20.6 → clamped to 0

Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On an entity's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement, and velocity falls back to engagement over its whole lifetime until a second reading exists. Full methodology

Signal history

7-day window (free)
Not enough history yet — the trend line fills in as snapshots accrue (every 30 min).

The evidence

The live items this entity's score aggregates — every community independently talking about it right now. This is the corroboration, shown, not claimed.

  1. 1
    42

    How to Use Jev: A practical guide to TypeSafe's System One model

    Guide shows how to apply Jev's System One model for type-safe AI pipelines. · for ml engineers, data scientists

    devtoSteady 3 · jevai46d ago
  2. 2
    35

    kicking the tires on jev (TypeSafe's System One model) with 2048

    TypeSafe's System One model (jev) now supports 2048-token context for AI game applications. · for ml engineers

    lobstersSteady 3 · jevai46d ago
  3. 3
    16

    TypeSafe Jev Played Chess — And Landed Next to Reasoning Models

    Shows TypeSafe Jev's chess performance near reasoning models, indicating progress in agent evaluation. · for AI engineers

    devtoSteadyai48d ago
  4. 4
    16

    @ai-sdk/typesafe-ai — AI SDK integration for Typesafe AI

    Provides a typed SDK for integrating AI services in the Typesafe ecosystem. · for backend engineers

    npmSteadyai41d ago
  5. 5
    16

    Typesafe AI raises $870M at $7.5B

    Typesafe AI's $870M raise signals strong investor confidence in its AI platform. · for startup founders

    hackernewsSteadybusiness26d ago
  6. 6
    15

    foreman — An agent supervisor and software factory foreman powered by TypeSafe’s Jev model

    Foreman, built on TypeSafe's Jev model, supervises agents in software factories. · for platform engineers

    githubSteady 4 · jevdevtools−16 saturated46d ago
  7. 7
    13

    awesome-jev-tools — A curated list of tools built for Jev — TypeSafe AI's System One model for typed decisions.

    Curated Jev tool list and TypeSafe AI's System One model for typed decisions. · for web devs

    githubSteady 3 · jevai−16 saturated45d ago
  8. 8
    8

    awesome-jev — 1207 public resources for Jev, TypeSafe AI's System One decision model, indexed by decision pattern. Source citations, dated l

    Curated list of 1,207 resources for Jev decision model aids research and implementation. · for ai researchers

    githubSteady 2 · jevai−17 saturated38d ago
  9. 9
    8

    typesafe-computer-use — Computer use for about $0.0002 a step: OCR the screen, classify the next action with TypeSafe, click. macOS.

    TypeSafe enables cheap, step-by-step screen OCR and action automation on macOS. · for platform engineers, automation developers

    githubSteady 2 · macosdevtools−17 saturated46d ago
  10. 10
    0

    ollaya — Run open decision models locally: pull and serve Laya, decider, NLI and GLiClass behind a TypeSafe-compatible API. Ollama for decis

    Runs decision models locally via a TypeSafe API, avoiding external calls. · for ml engineers, backend developers

    githubSteadyai−17 saturated38d ago