Fermah ✓

@fermah_xyz · joined 05 Jul 2024

Programmable, async compute infra - powering next-gen apps, starting with @flashcastsocial. Find out more: https://t.co/6mWi2fPWpn

101 666Followers

57Following

5 468Posts total

20.7KViews on collected posts

Últimas publicaciones

Fermah ✓@fermah_xyz7 Sep

Consensus orders transactions. External operators still decide which transactions exist—and when. At Fermah, production integrations expose the gap: bots, cron jobs, and relayers trigger actions after conditions are met. Protocol-native conditions can initiate composable 3.9K views · 91 likes · 18 reposts · 21 replies Open on X →

Fermah ✓@fermah_xyz7 Sep

Agent workflows outgrow the signed-transaction boundary: an agent starts work, continues elsewhere, then composes returned state into its next action. x402 makes the gap visible: an HTTP 402 can request machine payment while the underlying work finishes later. Fermah supports 3.1K views · 120 likes · 15 reposts · 29 replies Open on X →

Fermah ✓@fermah_xyz5 Sep

Consensus distributes agreement; autonomous markets require distributed action origination. In a liquidation market, an external bot must detect the threshold, choose a route, and submit the transaction before validators can act. Detection, path selection, and initiation 5.4K views · 111 likes · 18 reposts · 32 replies Open on X →

Fermah ✓@fermah_xyz4 Sep

Choose execution granularity by how often an action occurs. Across 100,000+ autonomous resolutions and 2.8M+ proofs, immediate events needed low-latency initiation; recurring actions could absorb batching. Latency-sensitive and batch-tolerant actions need different proving 4.9K views · 113 likes · 21 reposts · 29 replies Open on X →

Fermah ✓@fermah_xyz4 Sep

Human resolution determines which prediction markets can exist. A recurring market needs outcomes computed as each event arrives, not settled days later. Across 100,000+ production markets, Fermah has computed outcomes at market-creation speed. Human resolution decides what 3.4K views · 108 likes · 18 reposts · 33 replies Open on X →

Frente a cuentas del mismo tamaño

5 publicaciones de los últimos 90 días, junto al rango de 100K–1M seguidores. llega mucho más allá de su propia audiencia, y esa audiencia responde.

Visualizaciones medianas3 863esta cuenta5 986mediana de 100K–1M

Alcance, %3.80%esta cuenta1.57%mediana de 100K–1M

Interacción, %3.37%esta cuenta0.99%mediana de 100K–1M

Métrica	Esta cuenta	Mediana de 100K–1M	Proporción
Visualizaciones medianas por publicación	3 863	5 986	0.65×
Alcance (visualizaciones ÷ seguidores)	3.80%	1.57%	2.42×
Tasa de interacción	3.37%	0.99%	3.41×

Otras cuentas de este rango → Comparar con otra cuenta → Cómo se construyen estas referencias →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

3.4K4 Sep

4.9K

5.4K5 Sep

3.1K7 Sep

3.9K

Last 5 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

4.69%4 Sep

3.34%

2.97%5 Sep

5.26%7 Sep

3.37%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 0.99%.

What the audience does

Likes69.4%543 in total

Reposts11.5%90 in total

Replies18.4%144 in total

Bookmarks0.6%5 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.