One month = 130,000 engineering tasks done by AI agents.
@DoorDash is already operating Agents at serious scale.
Once you reach that point, the model isn’t the only thing that matters.
You need:
→ Agent identity
→ Tool access
→ Permissions
→ Communication
→ Observability
→ Reliable execution
That’s why @Fetch_ai built an end-to-end Agent stack. Not another isolated AI tool.
https://www.infoq.com/news/2026/08/doordash-flux-cloud-agent/
70·B+Long
n
news9/8news
One month = 130,000 engineering tasks done by AI agents.
@DoorDash is already operating Agents at serious scale.
Once you reach that point, the model isn’t the only thing that matters.
That’s why http://Fetch.ai built an end-to-end Agent stack. Not another isolated AI tool. https://www.infoq.com/news/2026/08/doordash-flux-cloud-agent/
70·B+Long
n
news9/8news
One month = 130,000 engineering tasks done by AI agents.
@DoorDash is already operating Agents at serious scale.
Once you reach that point, the model isn’t the only thing that matters.
You need:
→ Agent identity
→ Tool access
→ Permissions
→ Communication
→ Observability
→ Reliable execution
That’s why http://Fetch.ai built an end-to-end Agent stack. Not another isolated AI tool.
https://www.infoq.com/news/2026/08/doordash-flux-cloud-agent/
70·B+Long
n
news9/7news
Want to combine uAgents + @solana transactions? Build this 3-Agent flow.
PlayerAgent
→ Loads its Solana wallet → Sends an `escrowRequest` → Transfers SOL to escrow
ChallengerAgent
→ Does the same from a second wallet
EscrowAgent
→ Receives both requests → Pulls live BTC price data → Determines the winner → Transfers the payout → Messages both Agents with the result
All three register through http://Fetch.ai’s Almanac, communicate through typed uAgent messages and execute transactions on Solana Devnet.
The example uses three specialised Agents instead of stuffing wallet management, external data, decision logic and settlement into one process.
Run it on Devnet first: `poetry run python escrow_agent.py`
Then start the Player and Challenger Agents. From there, extend the pattern into DeFi workflows, NFT auctions or other Agent-driven on-chain logic.
Build the Solana example today. Check @Fetch_ai_IL guide → https://innovationlab.fetch.ai/resources/docs/examples/on-chain-examples/solana-agents
35·CLong
n
news9/7news
Our CEO, Dr. @bengoertzel, has responded to the @BernieSanders–Casar “Ban Artificial Superintelligence Act,” which would permanently prohibit the development and deployment of superintelligent AI, pause advanced AI development pending federal review, and direct US foreign policy toward preventing superintelligence from being built anywhere in the world.
The legislation focuses on the concentration of frontier AI development among a small number of large corporations. Dr. Goertzel agrees that this concentration creates a problem and supports external audits, incident reporting, and independent technical oversight. He disagrees with prohibition as the response.
AGI development does not depend on a scarce physical resource that can be controlled through international agreements. The research consists of mathematics, software, published algorithms, and commodity hardware. A global ban would therefore require surveillance of general-purpose computing while leaving states, military programs, and other actors outside that system able to continue their work.
The effect on open development is a central concern. A ban carrying severe criminal penalties would be easier to enforce against researchers who publish their work, open-source their code, and collaborate across institutions than against programs operating in secret. “It selectively destroys the development that is visible, which is to say, the open, decentralized, academically published, internationally collaborative work, while leaving intact the development that is hidden.”
The proposed pause on advanced AI development raises another issue. Establishing a new federal agency and review process could favor companies with large compliance teams and existing relationships with regulators. The result could be greater advantage for the same incumbents the legislation seeks to constrain.
Dr. Goertzel proposes a different approach centered on public compute, open development, external oversight, cognitive-liberty protections, and mechanisms for distributing AI-generated economic gains. The question he puts forward is “under whose control, with what values, and toward whose benefit.”
55·BShort
n
news9/7news
Our CEO, Dr. @bengoertzel, has responded to the @BernieSanders–Casar “Ban Artificial Superintelligence Act,” which would permanently prohibit the development and deployment of superintelligent AI, pause advanced AI development pending federal review, and direct US foreign policy toward preventing superintelligence from being built anywhere in the world.
The legislation focuses on the concentration of frontier AI development among a small number of large corporations. Dr. Goertzel agrees that this concentration creates a problem and supports external audits, incident reporting, and independent technical oversight. He disagrees with prohibition as the response.
AGI development does not depend on a scarce physical resource that can be controlled through international agreements. The research consists of mathematics, software, published algorithms, and commodity hardware. A global ban would therefore require surveillance of general-purpose computing while leaving states, military programs, and other actors outside that system able to continue their work.
The effect on open development is a central concern. A ban carrying severe criminal penalties would be easier to enforce against researchers who publish their work, open-source their code, and collaborate across institutions than against programs operating in secret. “It selectively destroys the development that is visible, which is to say, the open, decentralized, academically published, internationally collaborative work, while leaving intact the development that is hidden.”
The proposed pause on advanced AI development raises another issue. Establishing a new federal agency and review process could favor companies with large compliance teams and existing relationships with regulators. The result could be greater advantage for the same incumbents the legislation seeks to constrain.
Dr. Goertzel proposes a different approach centered on public compute, open development, external oversight, cognitive-liberty protections, and mechanisms for distributing AI-generated economic gains. The question he puts forward is “under whose control, with what values, and toward whose benefit.”
55·BShort
n
news9/6news
🚨 Create a brand-new AI Agent in 20 seconds, using a prompt + agentic intelligence.
It’s that easy. Try it → https://agentverse.ai https://t.co/VOR4pILoWN
10·CNeutral
n
news9/5news
MIT reports that brands will find success with a complete agentic AI environment where agents plan, retrieve, remember, and act reliably at scale.
But it depends on the right foundation and system compatibility.
@Fetch_ai provides the agent infrastructure needed above that compute layer: building, orchestration, discovery, interoperability, identity and verifiable execution.