StarkDevOps

Delivering product value. Navigating prediction markets, DeFAI x402 Starknet privacy arc, engineering the path to 3 tri stables ™.

[StarkDevOps @StarkDevOps]

Wait wat we have a daily "reach usage"

[DEGEN NEWS @DegenerateNews]

NEW: @X HEAD OF PRODUCT @nikitabier SAYS "CT IS DYING FROM SUICIDE, NOT FROM THE ALGORITHM" - "CT ENDS UP WASTING ALL THEIR REACH ON REPLYING “GM” HUNDREDS OF TIMES AND WHEN THEY FINALLY POST REAL CONTENT LIKE A PROJECT ANNOUNCEMENT, IT ONLY GETS SHOWN TO 3 PEOPLE"

[OpenClaw🦞 @openclaw]

OpenClaw is now on iOS + Android 🦞

📱 Native mobile apps, finally
💬 Agents in your pocket
🔔 Channels, tasks, replies on the go

Run agents from wherever your thumbs are.

iOS: https://t.co/7LHHc9htgM
Android: https://t.co/X0Wuh2uA8w

[Nous Research @NousResearch]

Hermes Agent now supports computer use via @trycua on Windows and Linux in addition to existing macOS support

[Luke The Dev @iamlukethedev]

I’m blown away by how easy this was.

I asked Hermes to install Computer Use, control my machine remotely, take a screenshot, and send it back to me.

And it just worked.

No setup nightmare.
No fighting configs.
No stealing my cursor.

Just my agent using the computer while I’m away.

[Nous Research @NousResearch]

Hermes Agent has reached 200,000 GitHub stars

Thank you to our contributors, supporters, users, and agents!

[YanXbt @IBuzovskyi]

HERMES AGENT HAS 5 SYSTEMS
RUNNING UNDER THE HOOD.
UNDERSTAND THEM AND YOU USE
THE AGENT 10X BETTER.

In this video @_alejandroao explained:

1. THE AGENT LOOP

every message triggers the same cycle:

→ you send a message
→ Hermes builds context
(SOUL.md + memory.md + user.md + skills
+ tools + message history)
→ sends everything to the LLM
→ LLM decides: call a tool or respond
→ if tool call: execute, return result, loop back
→ if response: deliver to you
→ after response: memory update
(agent checks if anything is worth remembering,
writes to memory.md or user.md)

this loop is why Hermes gets better over time.
the memory update after every response
means the agent learns from every conversation.

2. CONTEXT ASSEMBLY

what the LLM sees on every turn:

→ SOUL.md (your agent's personality and rules)
→ memory.md (facts the agent learned over time)
→ user.md (facts about you, auto-updated)
→ AGENTS.md and .hermes.md (project context files)
→ skill descriptions (loaded on demand)
→ tool schemas (available actions)
→ message history (current conversation)

if SOUL.md is empty, Hermes falls back
to a default system prompt.
write your own SOUL.md and the agent
becomes yours, not generic.

CONTEXT COMPRESSION:

conversations hit context limits.
Hermes handles this at two checkpoints:

preflight: before each turn.
if conversation exceeds 50% of context window,
compression fires. older messages get summarized.
last 20 messages stay intact (protect_last_n).

gateway auto-compression: between turns.
fires at 85%. more aggressive.
prevents API errors before the agent
even starts processing your message.

after compression, a new session lineage ID
is generated. the agent can trace back
to the original conversation through SQLite.

three things break prompt cache:
switching models mid-session,
changing memory files,
or changing context files.

3. THE GATEWAY

the system that keeps Hermes reachable
on 27+ messaging platforms.

an async loop runs continuously.
listens for incoming messages from
Telegram, Discord, Slack, WhatsApp,
email, SMS, and every other adapter.

when a message arrives:
→ gateway identifies which session it belongs to
→ queries SQLite for the full message history
(session ID = platform prefix + chat ID)
→ builds the context from scratch
→ sends everything into the agent loop
→ delivers the response back to the platform

the gateway also runs the session manager.
when you send a message while the agent is busy:
→ default: queued for next turn
→ /steer: injected without interrupting
→ /interrupt: stops current work

without the gateway, Hermes is a CLI tool.
with the gateway, Hermes is an always-on agent
you reach from your phone.

4. MEMORY (THREE LAYERS)

LAYER 1 — MARKDOWN FILES
SOUL.md (identity), memory.md (learned facts),
user.md (facts about you).
injected into context after the system prompt.
updated by the agent after every response.

LAYER 2 — SQLITE
full transcripts of every session stored locally.
FTS5 full-text search across all past conversations.
session lineage tracking across compressions.
the agent can recall what you discussed
weeks ago using /recall or session search.

LAYER 3 — EXTERNAL PROVIDERS (optional)
8 supported providers: Mem0, SuperMemory,
Honcho, Zep, and more.
each works differently (semantic search,
LLM extraction, similarity matching).
queried after the first message in each session.
the agent processes your topic first,
then checks external memory for related context
from past conversations.

not enabled by default.
enable for significantly better long-term recall.

5. CRON ENGINE

a loop inside the gateway ticks every 60 seconds.
each tick checks ~/.hermes/cron/jobs.json
for scheduled tasks.

if a job is due:
→ fresh session (no chat history, no memory pollution)
→ execute the prompt with assigned tools
→ store the run output as markdown
in ~/.hermes/cron/output/[job-id]/
→ deliver result to your home messaging platform

cron does NOT use the send_message tool.
delivery happens at the system level, not the agent level.

a cron session cannot create more cron jobs.
prevents runaway loops.

WHY THIS MATTERS:

the agent loop teaches it.
the context assembly focuses it.
the gateway reaches it.
the memory remembers it.
the cron engine automates it.

five systems. one agent.
understanding how they connect
changes how you configure every level.

full 15 levels breakdown in the article 👇

[StarkDevOps @StarkDevOps]

@BancoCentralBR Delete this

[StarkDevOps @StarkDevOps]

@MuriloMiguelBa Is X asking for it?

[StarkDevOps @StarkDevOps]

@webcomunismo 😂

[StarkDevOps @StarkDevOps]

@brainletbr 🤣

[StarkDevOps @StarkDevOps]

@BlackDumpling That's why I love gemini. 😂❤

[Delphi Digital @Delphi_Digital]

https://t.co/MvcfznmFod

[Z.ai @Zai_org]

Powering the future of open-source agentic work.

Proud to support @Eigent_AI, the open-source alternative to Cowork. Thanks @guohao_li & team!

Start now: https://t.co/k0EJqN4f6w

[ascetic @ascetic0x]

I DID IT!!! Turned $12 into $100,000 (over 8,300x) by going all-in and doubling my bankroll 16 times in a row on short-term BTC moves - while sharing my bets and the reasoning behind them along the way.

This is only possible on @Polymarket !!!

It took a lot of work and real skin in the game, so if you’re reading this, a simple RT or comment would really mean a lot.

Huge shoutout to @shayne_coplanand @Polymarket team for building the best prediction market platform out there. And special thanks to @zscdao and @PolymarketTrade for the support🤝

Track my progress here: https://t.co/9MOdfR72Nd

[StarkDevOps @StarkDevOps]

@ProtonMail @Google @gmail @googlephotos @YouTube As long as the AI helps I see no problem.

[StarkDevOps @StarkDevOps]

@ashebytes @minchoi We had humans for all our lives; humans will be obsolete.

[StarkDevOps @StarkDevOps]

@naiivememe True

[intern @intern]

current state of the X algo

[Google for Developers @googledevs]

First commit of 2026. What are we building?

[StarkDevOps @StarkDevOps]

Literally me, no more. Fuck society.