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Just the real architecture:
- agent loops
- tools
- memory
- RAG
- orchestration
- multi-agent systems
- evaluation
- production failure modes
If you’re building agents, I’d appreciate a star.
We spent weeks turning scattered AI agent material into a clean engineering handbook.
No “AGI is near.”
No “agents replace developers.”
No toy chatbot-only examples.
Open-source:
https://t.co/yIehFnwmUT
Most agent demos show a chatbot calling one tool.
That is not enough for production.
The hard parts are:
- context window management
- memory design
- failed tool calls
- evals
- observability
- cost control
- human approval paths
That is what AgentSystems101 focuses on.
AI agents are not magic.
They are software systems with:
- state
- tools
- memory
- retrieval
- orchestration
- evaluation
- failure modes
So we built AgentSystems101: an open-source engineering handbook for people who want to build agents properly.
https://t.co/yIehFnwmUT
What is inside:
1. LLM foundations
2. Agent loops
3. Tool use
4. Memory systems
5. RAG
6. Context engineering
7. Orchestration
8. Multi-agent systems
9. Evaluation
10. Production failure modes
Built for engineers, not hype.
@sama AI agents are not magic.
They are software systems with:
- state
- tools
- memory
- retrieval
- orchestration
- evaluation
- failure modes
So we built AgentSystems101: an open-source engineering handbook for people who want to build agents properly.
https://t.co/yIehFnwmUT
The biggest shift in e-commerce isn’t a new store. It’s AI agents.
Google’s Universal Commerce Protocol gives AI a common language across product discovery, checkout, and post-purchase support.
So the game is changing fast: brands used to fight for shelf space.
Every AI bro on LinkedIn: "multi-agent orchestration is the future."
Reality for a $1M service business: one clean n8n workflow that books jobs from missed calls beats 12 agents arguing with each other.
Start simple. Ship this week.
DeepSeek just dropped V4 Flash and V4 Pro. Top-tier coding benchmarks, major agentic gains.
Translation for small shops: inference costs keep falling. The AI customer service bot that cost $400/mo last year runs for $80 now.
Keep shipping.
OpenAI shipped GPT-5.5. Switches tools, writes code, runs deep research on its own.
For service business operators: the quoting bot, follow-up SMS, inbox triage — all get smarter this week without you lifting a finger.
Agents stopped being a demo. They're infra now.
@deepseek_ai The real story isn't DeepSeek vs OpenAI. It's that open-source AI just leveled up so fast that any business still waiting to "see how AI develops" is already behind. The tools are here. The cost barrier is gone. What's your excuse now?
DeepSeek just proved that you don't need $100B compute budget to build a frontier AI model.
A Chinese lab released an open-source model that matched GPT-4 level performance at a fraction of the cost and the entire Western AI industry had to sit with that for a minute.@deepseek_ai
Tesla’s Cybercab isn’t just a new car. It’s Tesla saying the future of transport has no driver, no steering wheel, no pedals, and eventually no excuse for human-operated urban fleets. Production has reportedly started in April 2026.@Tesla
@OpenAIDevs “A new way of getting computer work done” is a big claim. If GPT-5.5 delivers on reasoning, tool use, and task completion, it could change how teams actually operate.
@OpenAI If GPT-5.5 actually handles complex goals, uses tools properly, and checks its own work, this could be the first real step from chatbot to true work agent.@ChatGPTapp
Instagram has launched Instants, a new standalone app now available in Italy. Meta has not announced whether or when the app will roll out in the U.S. @Meta
Most businesses are still using AI as a search engine.
The ones pulling ahead are using it as a worker.
There's a massive gap opening right now between those two groups.
GPT-5.5 dropping today just made that gap bigger.