Identity + long-term memory + initiative = exactly what turns agents into teammates. Seraph was built around this from day one: persistent LanceDB memory, proactive background scheduler, and desktop awareness so it watches and acts without constant prompting. Local-first by design. Curious how others are giving agents real initiative without losing control.
Introducing Workers: unlimited AI employees that run your company...
And we've just made $1M ARR in a couple of days.
Most knowledge jobs shouldn't exist.
Not because the work isn't valuable.
Because the way we execute it is absurd.
Millions of people spend their days:
- Answering emails
- Following up
- Updating CRM
- Coordinating meetings
- Moving information between systems
There is no expertise here. That's workflow..
Workers are AI employees that can perform work across your organization like a human teammate.
The line between software and labor just disappeared.
Spot on. Overloading agents with every possible tool kills focus. In Seraph we keep a curated MCP toolset + hierarchical goals so it only surfaces what’s relevant for the current task. The proactive scheduler then decides when to act instead of reacting to everything. Filtering + parallel execution dropped our failure loops dramatically too. What tool selection strategy have you seen work best?
giving your ai agent 40+ tools is not the flex you think it is
it actually makes it dumber
before you come at me, hold on lemme explain
so imagine you walked into a hardware store and the worker handed you every single tool they have
[hammers, drills, 47 screwdrivers]
just to fix one thing, you’d freeze
that’s exactly what happens to ai agents when they get loaded with too many tools at ones
it gets confused, picks the wrong one, it fails, it tries again and wastes time in the process
in order to avoid all these, there are fixes that can be employed
• only show it what it needs
before the agent even starts working, filter the tools down to just the relevant ones for that specific task
like handing the worker only a hammer and two screwdrivers instead of the whole store
you’d notices tool errors dropped 29% from this alone
• stop doing things one by one
if two tasks don’t need each other, run them at the same time
you’d notice speed improved by 42%
now imagine combining both?
95% of tasks gets done in just 1–2 steps, no more agent running in circles
this is what @SentientAGI figured out
imo smarter doesn’t always mean more, sometimes it just means better organized
you can read the full break down in the blog in the comments
Introducing Sakana Fugu: A full multi-agent orchestration system accessible via a single model API.
Our ‘Fugu Ultra’ model matches the performance of Fable and Mythos, delivering frontier capability without the risk of export controls.
Try it: https://t.co/hhO6qTawgb 🐡
Just shipped Seraph v2026.4.11 🎉
The proactive AI Guardian is getting sharper:
• New screen-report controls + capture budgets
• Local screen End-of-Day reports
• Cleaner current-app guide
• Fixed local Codex operator routing
• Lots of docs & polish
Persistent memory, desktop watching (macOS daemon), proactive scheduler, browser cockpit, MCP tools — all still there and better.
Try it now: https://t.co/n3dvwn0eq5
Star it, run it, tell me what you think!
Fully open source, Docker-ready, and designed for power users & builders who want a real workspace guardian instead of another reactive chatbot.
Try it: https://t.co/n3dvwn0eq5
Star it, run it locally, and tell me what you think or what you’d like to see next.
#OpenSource #AIAgents #AgenticAI #BuildInPublic #LocalAI
Seraph v2026.4.11 is out. 🎉🤖
An open-source AI Guardian that remembers your context, watches what’s happening on your desktop, and actually acts on your goals — instead of waiting for the next prompt.
New in this release:
• Screen report controls & capture budgets
• Local screen EOD reports
• Improved local Codex routing
• Cleaner docs & guides
https://t.co/UW3a0F3CjG
https://t.co/n3dvwn0eq5
Optional macOS daemon gives it screen awareness + OCR so it can actually see what you’re working on.
Everything runs local-first with flexible LLM routing (Ollama, OpenRouter, Anthropic, OpenAI-compatible, etc.).
Introducing GLM-5.2: Frontier Intelligence, Open Weights
- Significant improvements in coding and agentic tasks
- Strong long-horizon capabilities with a 1M context window
- Two levels of reasoning effort: GLM-5.2 (max) pushes the limits, while GLM-5.2 (high) strikes a strong balance between performance and token efficiency
- MIT-licensed open weights
- Same API pricing as GLM-5.1
Tech Blog: https://t.co/LAsxUdN0JZ
Weights: https://t.co/g0A1C4UWx4
API: https://t.co/Kc3E22cbN7
Coding Plan: https://t.co/Nk8Y98HNhU
Chat: https://t.co/WCqWT0qCQb
This is going to have an opposite effect that the decels want. It's a huge open source AI accelerant, an accelerant for corporations, and enterprises
Now it's a real race. You either make your own AI infrastructure or you don't have a seat at the table
Announcing the Gemma challenge!
Google, Hugging Face, and the open-source AI community choose to empower AI builders rather than sabotage them.
Fun to see the Hub becoming the platform where agents collaborate, just as it became the platform where humans collaborate.
https://t.co/GbCfy1qwgx
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