Is asahi sustainable?
I really would like to get your opinion about the sustainability of asahi linux on m1/2 over the versions. Can I trust it as a main dev workstation? Does new updates can break system boot?
I really would like to get your opinion about the sustainability of asahi linux on m1/2 over the versions. Can I trust it as a main dev workstation? Does new updates can break system boot?
Memora update:
https://github.com/agentic-box/memora.git
https://i.redd.it/jv2q2bzk4w3h1.gif
The core idea is simple:
Agents produce useful facts while working: decisions, TODOs, bugs, notes, implementation details. Instead of leaving that knowledge buried in chat history, Memora can absorb it into durable memory.
Then later, another agent can ask for a digest on a topic and get back the relevant memories, open TODOs/ issues, related edges, and source memory IDs.
The flow is:
agent work
-> memory_absorb(...) stores decisions / TODOs / issues / notes
-> Memora dedupes, updates, and links related memories
-> memory_digest(topic=...) returns focused context with source memory IDs
The important change is memory_digest.
Instead of asking an agent to manually search memory, inspect related entries, check open TODOs, and reconstruct project state, memory_digest does the deterministic aggregation step:
- hybrid search for the topic
- active/latest memories
- optional supersession lineage
- related memories
- matching TODOs/issues
- raw source IDs included in the output
We're intentionally keeping this first version source-backed rather than “magic summary only.” The caller still gets the underlying memory IDs, so the result can be inspected, verified, or expanded.
This is part of the broader agentic-box / clmux workflow I’m building, where multiple CLI agents coordinate through MCP and need durable memory across sessions.
Memora update:
https://github.com/agentic-box/memora.git
https://i.redd.it/sk37zuh84w3h1.gif
The core idea is simple:
Agents produce useful facts while working: decisions, TODOs, bugs, notes, implementation details. Instead of leaving that knowledge buried in chat history, Memora can absorb it into durable memory.
Then later, another agent can ask for a digest on a topic and get back the relevant memories, open TODOs/ issues, related edges, and source memory IDs.
The flow is:
agent work
-> memory_absorb(...) stores decisions / TODOs / issues / notes
-> Memora dedupes, updates, and links related memories
-> memory_digest(topic=...) returns focused context with source memory IDs
The important change is memory_digest.
Instead of asking an agent to manually search memory, inspect related entries, check open TODOs, and reconstruct project state, memory_digest does the deterministic aggregation step:
- hybrid search for the topic
- active/latest memories
- optional supersession lineage
- related memories
- matching TODOs/issues
- raw source IDs included in the output
We're intentionally keeping this first version source-backed rather than “magic summary only.” The caller still gets the underlying memory IDs, so the result can be inspected, verified, or expanded.
This is part of the broader agentic-box / clmux workflow I’m building, where multiple CLI agents coordinate through MCP and need durable memory across sessions.
Memora update:
https://github.com/agentic-box/memora.git
The core idea is simple:
Agents produce useful facts while working: decisions, TODOs, bugs, notes, implementation details. Instead of leaving that knowledge buried in chat history, Memora can absorb it into durable memory.
Then later, another agent can ask for a digest on a topic and get back the relevant memories, open TODOs/ issues, related edges, and source memory IDs.
The flow is:
agent work
-> memory_absorb(...) stores decisions / TODOs / issues / notes
-> Memora dedupes, updates, and links related memories
-> memory_digest(topic=...) returns focused context with source memory IDs
The important change is memory_digest.
Instead of asking an agent to manually search memory, inspect related entries, check open TODOs, and reconstruct project state, memory_digest does the deterministic aggregation step:
- hybrid search for the topic
- active/latest memories
- optional supersession lineage
- related memories
- matching TODOs/issues
- raw source IDs included in the output
We're intentionally keeping this first version source-backed rather than “magic summary only.” The caller still gets the underlying memory IDs, so the result can be inspected, verified, or expanded.
This is part of the broader agentic-box / clmux workflow I’m building, where multiple CLI agents coordinate through MCP and need durable memory across sessions.
Memora update:
https://github.com/agentic-box/memora.git
https://i.redd.it/fevni7ie3w3h1.gif
The core idea is simple:
Agents produce useful facts while working: decisions, TODOs, bugs, notes, implementation details. Instead of leaving that knowledge buried in chat history, Memora can absorb it into durable memory.
Then later, another agent can ask for a digest on a topic and get back the relevant memories, open TODOs/ issues, related edges, and source memory IDs.
The flow is:
agent work
-> memory_absorb(...) stores decisions / TODOs / issues / notes
-> Memora dedupes, updates, and links related memories
-> memory_digest(topic=...) returns focused context with source memory IDs
The important change is memory_digest.
Instead of asking an agent to manually search memory, inspect related entries, check open TODOs, and reconstruct project state, memory_digest does the deterministic aggregation step:
- hybrid search for the topic
- active/latest memories
- optional supersession lineage
- related memories
- matching TODOs/issues
- raw source IDs included in the output
We're intentionally keeping this first version source-backed rather than “magic summary only.” The caller still gets the underlying memory IDs, so the result can be inspected, verified, or expanded.
This is part of the broader agentic-box / clmux workflow I’m building, where multiple CLI agents coordinate through MCP and need durable memory across sessions.