Developer AlafIA retweeted
HERMES CAN NOW CONTROL YOUR PHONE. 🤯📱🔥
A new Phone Harness plugin gives Hermes the ability to actually operate an iPhone or Android.
We're talking real phone control:
• See what's on the screen
• Open apps and navigate menus
• Tap, swipe, scroll, and type
• Read the results and continue working
• Handle multi-step tasks inside mobile apps
And here's what makes this so interesting...
Hermes doesn't need a dedicated API integration for every app. It can interact with the same interface you use.
Supports iPhone through Mac mirroring, Android through ADB, and cloud phones.
Think about how many new workflows this opens up for Hermes.
Repo + setup in the first reply. 🔥
@phone_harness
Developer AlafIA retweeted
我发现,几乎所有想靠 AI 赚钱的人,最后都会经历这五个阶段。
第一阶段:钻研技术。天天研究新模型、新工具、插件,skill,越学越兴奋。最容易产生一种幻觉:我懂了这么多别人不懂的东西,肯定能赚到钱。
于是进入第二阶段。
第二阶段:搞“一人公司”。觉得自己会 AI,就不应该再用传统方式做生意。运营、设计、程序员、客服,全部让 AI 干。一个人、一台电脑,顶一个团队。结果做了一阵才发现:Token 越烧越多,订阅费越来越高,钱却没赚到多少。这时候才明白:AI 只能提高效率,但如果你做的东西没人要,效率越高,只是更快地生产垃圾。于是进入第三阶段。
第三阶段:开始搞流量。你发现,产品再好,没人看见也没用。于是开始研究自媒体、标题、短视频、算法、完播率、互动率、涨粉。以前研究的是:“AI 怎么用?”后来研究的是:“怎么让更多人看到我?”然后你会发现,AI 变现翻来覆去就那么几种:卖课、咨询、社群、定制开发、卖资料。于是进入第四阶段。
第四阶段:开始教别人赚钱。把自己踩过的坑、研究过的方法打包成产品。开始讲:“普通人怎么靠 AI 赚钱。”“我是怎么用 AI 涨粉的。”“一个人怎么靠 AI 做公司。”结果又发现,教人赚钱这条赛道早就挤满了。用户也被各种“副业”“搞钱”“认知课”割麻了。于是进入第五阶段。
第五阶段: 就是彻底佛系了,对AI去魅了。
极少人进入第六阶段:找到一个真正适合自己、有人愿意付钱,而且可以长期做的方向。把技术、流量、产品和商业模式真正串起来。
Developer AlafIA retweeted
EVERYONE LOVES FREE 😍🆓
Hermes currently gives you 7 models you can run for free 🙌
No API key. No OpenCode account.
The current OpenCode Free lineup:
• `deepseek-v4-flash-free`
• `muse-spark-1.2-contributor-free`
• `mimo-v2.5-free`
• `ling-3.0-flash-fin-free`
• `nemotron-3-ultra-free`
• `nemotron-3.5-lightning-free`
• `laguna-s-2.1-free`
And I think the more interesting use for these is not necessarily replacing your main model.
It's using them for the work that doesn't need your best model in the first place.
Hermes lets you assign different models to auxiliary jobs like:
• context compression
• webpage summarization
• title generation
• Skill search
• MCP routing
• triage and task decomposition
So you can keep your stronger paid or subscription model focused on the work where quality matters most, while pushing more routine background work to the free pool.
You can access OpenCode Free through `hermes model` or `/model free`.
And there's another nice improvement here.
Hermes now checks OpenCode's live free-model catalog instead of relying on a frozen list.
So as OpenCode rotates models in and out of the free tier, Hermes can keep up automatically. New free models can appear and delisted ones can disappear without waiting for another Hermes update.
The free lineup will change.
But that's kind of the point.
Use the free models for the routine work. Save your paid model usage for the jobs where the model actually matters.
One comparison to end the @bot vs @NousResearch debate once and for all...
Developer AlafIA retweeted
HERMES AGENT HAS 4 MEMORY LAYERS.
MOST USERS ONLY KNOW ABOUT 1.
THE OTHER 3 ARE WHY SOME AGENTS
GET SMARTER EVERY MONTH AND YOURS DOESN'T.
LAYER 1: USER.MD (who you are)
~/.hermes/memories/USER.md
the agent builds a profile of you over time.
your role, your stack, your communication style,
your goals. capped at ~1,375 characters.
the cap is the point. forces the agent
to keep only what matters about you.
not a diary. a compressed identity.
you don't write this. the agent does.
but you SHOULD read it monthly.
hermes memory status
open the file. delete what's wrong.
"user prefers Python" (you mentioned it once).
"user works at [old company]" (3 months outdated).
one wrong fact = wrong assumptions every session.
LAYER 2: MEMORY.MD (what the agent learned)
~/.hermes/memories/MEMORY.md
agent-curated notes about your projects,
preferences, environment, workflows.
capped at ~2,200 characters.
the agent decides what goes here
based on conversation patterns.
not because you said "remember this."
because it noticed something worth keeping.
entries get timestamped automatically:
keep the timestamps. the agent uses them
to decide which entries are still relevant.
same rule: read monthly. delete outdated facts.
the agent doesn't prune on its own.
when memory is full, new writes get rejected
instead of silently dropping old ones.
LAYER 3: SESSION SEARCH (full conversation archive)
~/.hermes/state.db
every CLI and messaging session stored in SQLite
with FTS5 full-text search.
the agent searches its own past:
"what did we discuss about the auth migration?"
it queries the database. returns actual messages.
no LLM summarization. no truncation.
real conversations from weeks ago.
memory = critical facts always in context.
session search = historical lookup when needed.
most users don't know this exists.
the agent uses it automatically when you reference
something from a past conversation.
LAYER 4: EXTERNAL MEMORY PROVIDERS (8 options)
beyond the built-in files, Hermes ships with
8 external memory provider plugins:
Honcho: dialectic reasoning + deep user modeling.
derives implicit patterns you don't articulate.
Hindsight: shared memory bank across agents.
Hermes remembers → Codex knows. and vice versa.
Mem0: semantic search + auto-consolidation.
OpenViking: graph-based memory with entity linking.
Holographic: vector similarity recall.
RetainDB: hierarchical knowledge tree.
ByteRover: local-first with cloud sync.
Supermemory: semantic search + profile recall.
one active at a time. built-in memory
(USER.md + MEMORY.md) stays alongside it.
hermes memory setup
(interactive picker + configuration)
hermes memory status
(check what's active)
HOW THEY STACK:
layer 1 (USER.md): always in system prompt.
who you are. updated by the agent.
layer 2 (MEMORY.md): always in system prompt.
what the agent learned. updated by the agent.
layer 3 (session search): queried on demand.
full conversation history in SQLite.
layer 4 (external provider): runs in background.
prefetches relevant memories before each turn.
syncs conversation after each response.
layers 1-3 are free and built-in.
layer 4 is optional and extends the system.
WHAT MOST PEOPLE GET WRONG:
MISTAKE 1: never reading memory files.
open USER.md and MEMORY.md right now.
Desktop app: sidebar → Memory.
CLI: cat ~/.hermes/memories/USER.md
wrong facts compound. one bad entry
= wrong assumptions on every future session.
MISTAKE 2: thinking bigger memory = better.
bounded memory works better than unlimited.
2,200 characters forces curation.
unlimited memory encourages dumping everything
and never cleaning up.
MISTAKE 3: confusing memory with session search.
memory = facts that should ALWAYS be in context.
session search = historical lookups when needed.
put your API server address in memory.
don't put last Tuesday's debugging session.
MISTAKE 4: two agents sharing one home directory.
memory writes are automatic.
two writers sharing ~/.hermes/ compound entries
neither of them authored.
give each agent its own profile.
shared memory = use an external provider (layer 4).
SECURITY:
every memory entry scanned before acceptance.
prompt injection attempts = blocked.
credential exfiltration = blocked.
SSH backdoors = blocked.
invisible Unicode characters = blocked.
exact duplicates = rejected automatically.
your memory files are injected into the system prompt.
that's why security scanning is non-negotiable.
5-MINUTE MONTHLY CLEANUP:
1. hermes memory status (check what's active)
2. open USER.md. delete outdated facts. 1 minute.
3. open MEMORY.md. delete stale entries. 2 minutes.
4. check timestamps. anything older than 60 days
with no recent reference = candidate for removal.
5. done. sharper agent for 30 days.
The LLM Cheat-Sheet for OpenClaw and Hermes agents
The goal is to choose the right models that best fit your agents' needs for as little cost as possible.
Do this and you can build a proficient agent that will never die.
Here's the full landscape on popular models for AI agents: 12 models, 4 tiers, every one earning its place.
Tier 1 - Frontier Models
- Claude Opus 4.6: #1 agentic terminal coding
- GPT-5.4: superhuman computer use, real planning
- Gemini 3.1 Pro: best price/intelligence at frontier, native multimodal
Tier 2 - Execution
- MiniMax M2.7: 97% skill adherence, built for agents
- Kimi K2.5: long-horizon stability, agent swarm
- DeepSeek V3.2: frontier reasoning at 1/50th the cost
Tier 3 - Balanced
- Claude Sonnet 4.6: 98% of Opus at 1/5 the cost
- GPT-5.4 mini: 93.4% tool-call reliability
- Qwen3.6 Plus: near-frontier coding, completely free
- Llama 4 Maverick: open-weight, self-host at zero marginal cost
Tier 4 - Local / $0
- Qwen3.5-9B: always-on subconscious loop, 16GB RAM, beats models 13x its size
- Qwen3.5-27B: stronger instruction following, 32GB RAM
- Gemma 4 31B: best local reasoning, Apache 2.0, commercial-ready
- DeepSeek R1 distill: best chain-of-thought at $0
- GLM-4.5-Air: purpose-built for agent tool use and web browsing, not a trimmed general model
Full breakdown with benchmarks, costs, and use cases in the table 🔽
Developer AlafIA retweeted
This is the Claude Code Resource Bible.
54 tools.
Agents. MCP servers. Skills. Automation.
Most people still haven’t discovered this stack.
That’s your edge. ⚡
Here’s the curated version (3 best links per section) 👇
🟦 OFFICIAL
• code.claude.com/docs — Claude Code docs
• lnkd.in/eBZZGsMx — official MCP servers
• lnkd.in/ekUBf8a6 — free certification
🟧 DIRECTORIES
• ecc.tools/ — everything Claude Code
• lnkd.in/ebE2iDvV — MCP list
• lnkd.in/emQbMwbG — 50+ MCPs
🟨 MCP SERVERS
• lnkd.in/eMC5dUqR — browser automation
• lnkd.in/eESCpJPv — database + auth
• github.com/Dokploy/mcp — deploy apps
🟩 SKILLS
• lnkd.in/eppbgRaK — browser control
• lnkd.in/ejAPia8C — full dev workflow
• github.com/tadaspetra/loop — recurring tasks
🟪 MULTIPLEXERS
• cmux.com — agent terminal
• gmux.sh/ — orchestrate agents
• github.com/coder/mux — parallel dev
🟥 AGENT FRAMEWORKS
• github.com/HKUDS/ClawTeam — multi-agent coordination
• lnkd.in/eJPYijMk — agent collaboration
• lnkd.in/eMt3sS7N — NousResearch agents
⚙️ AUTOMATION
• lnkd.in/e9sarX3R — workflows in code
• openlogs.dev/ — monitor agents
• lnkd.in/eDKBPrPU — self-hosted infra
📚 ARTICLES
• lnkd.in/e9gfhHhm — best CLI tools
• lnkd.in/ePCzNw5w — top MCP servers
• lnkd.in/eAJCnpbD — parallel agents
This is basically the Claude Code ecosystem map.
Learn it now → you're early
Ignore it → you're late
Bookmark this. You'll need it
Developer AlafIA retweeted
20 Completely FREE Programming Courses for 2026:
1. Python
youtube.com/playlist?list=…
2. JavaScript
youtube.com/playlist?list=…
3. SQL
youtube.com/playlist?list=…
4. Java
youtube.com/playlist?list=…
5. React 19
youtube.com/playlist?list=…
6. React Native
youtube.com/watch?v=f8Z9Jy…
7. Django
youtube.com/playlist?list=…
8. C++
youtube.com/watch?v=FpfHmA…
9. Rust
youtube.com/playlist?list=…
10. TypeScript
youtube.com/playlist?list=…
11. Golang
youtube.com/playlist?list=…
12. C#
youtube.com/watch?v=0QUgvf…
13. Kotlin
youtube.com/watch?v=TEXaoS…
14. Swift
youtube.com/watch?v=CwA1VW…
15. PHP
youtube.com/playlist?list=…
16. C
youtube.com/playlist?list=…
17. DSA
youtube.com/playlist?list=…
18. Machine Learning
youtube.com/watch?v=hDKCxe…
19. LLM
youtube.com/playlist?list=…
20. Generative AI
youtube.com/watch?v=mEsleV…
Developer AlafIA retweeted
Best GitHub repos for Claude Code that will 10x your next project in 2026:
1. Claude Skills
github.com/alirezarezvani/cl…
2. Claude Code Plugins + Skills
github.com/jeremylongshore/c…
3. Awesome Claude Skills
github.com/ComposioHQ/awesom…
4. Awesome Claude Skills
github.com/travisvn/awesome-…
5. Repomix
github.com/yamadashy/repomix
6. Claude Session Restore
github.com/ZENG3LD/claude-se…
7. Awesome Claude Code Toolkit
github.com/rohitg00/awesome-…
8. Awesome Claude Code
github.com/hesreallyhim/awes…
9. Claude Code Best Practice
github.com/shanraisshan/clau… ✅
10. Superpowers
github.com/obra/superpowers
WILD: The first $1B company with 1 employee is inevitable.
Not a team.
Not a startup.
One person.
Running everything with AI.
And it’s already starting. 🧵
OpenClaw Mission Control just dropped.
- Multi-device sync
- 3D Claw office (built by @iamlukethedev)
- Multiple chats
- Live actions
- Kanban Board
- Org Chart
- Memory
- All data lives on your openclaw machine
All inside Hyperclaw.
Deploy your agents on a Mac Mini or VPS → command them live from anywhere on Earth.
Mobile dropping soon.
This isn't an update. It's the control center for your AI workforce.
Open beta is live links in my bio.
Looking for early testers who want to architect the future.
Developer AlafIA retweeted
Best GitHub repos for Claude code that will 10x your next project in 2026:
1. Claude Mem github.com/thedotmack/claude…
2. UI UX Pro Max github.com/nextlevelbuilder/…
3. n8n-MCP github.com/czlonkowski/n8n-m…
4. Obsidian Skills github.com/kepano/obsidian-s…
5. LightRAG github.com/hkuds/lightrag
6. Everything Claude Code github.com/affaan-m/everythi…
7. Superpowers github.com/obra/superpowers
8. Awesome Claude Code github.com/hesreallyhim/awes…
9. GSD (Get Shit Done) github.com/gsd-build/get-shi…




























