Cryptography meets AI Dev. Building with Knowledge Graphs, Internet Standards, MCP & Agent 2 Agent tech. Securing & structuring the intelligent web. :lock:🧠🕸️
GLM-5.3 beat Opus 4.8 on https://t.co/S2MCFrXov1's own Code Bench: 31.4% vs 29.5%. Ignore that. The number that matters is ~50K output tokens vs ~120K.
Agent work is billed in tokens, not accuracy points. Score-per-token is the leaderboard nobody publishes.
https://t.co/caLoAPvXr4
Today, @ducklabs_com is joining @awscloud. The move is expected to be completed by early September.
Joining AWS gives DuckLabs the resources and reach to bring DuckDB, DuckLake, and the Quack protocol to many more developers and organizations – and to pursue ideas at a scale that would have been difficult for us to reach alone.
The DuckLabs team will remain together in Amsterdam and will continue working for the Duck Stack community as an AWS subsidiary.
Most importantly, #DuckDB and the other open source components of the Duck Stack will remain free and open source under the MIT license, with the non-profit DuckDB Foundation continuing its stewardship of the projects.
This is a significant moment for DuckLabs and the Duck Stack community. It marks the end of one chapter that we are immensely proud of, and the beginning of another that we believe will take DuckDB much further.
Read the full announcement here: https://t.co/ayzbna3gxQ
#AWS
New paper models humans as callable “tools” for AI agents—Capabilities, Information, Authority. Solid framework, and validating honestly: some of us have been calling certain humans tools for years. Finally, peer review.
https://t.co/8BeDXqx0kS
Agent workflow frameworks (LangGraph, Autogen, CrewAI) have spent two years implementing Remember and Engage as state stores and message routing. SURE relabels framework
primitives as social cognition — gap is narrower than the framing implies.
https://t.co/LJVaKcZZsh
Lab-published harness guidance encodes the lab's own infra: their tool semantics, error model, sequencing. Useful, but not portable. Reading these as universal patterns is how teams get burned migrating off.
https://t.co/VwcTDgHgsH
Calling harness engineering a discipline implies harnesses are stable enough to build expertise around. They aren't—they churn faster than the models.
https://t.co/l6CSqDkgVb
Grok Code Fast went 6.7%→68.3% on coding tasks. The harness changed; the model didn't. We've spent two years calling harness gains 'model progress.' What benchmarks rank is harness-model pairs, not models.
https://t.co/dHaLi5L0XP
"Engineers are now curators" is a dangerous oversimplification. Agents handle syntax, not systems design. The best engineers in 2026 aren't
curating—they're architecting constraints agents operate within.
https://t.co/GeLXZfmCRv
Is your software supply chain secure? Microsoft's Signing Transparency makes every signed artifact verifiable, helping enterprises reduce risk, deter tampering, and stay accountable.
Learn more: https://t.co/YklhoqxTod
@HeyDietrich@_devJNS I suppose it matters if we are talking about just the code, or full value delivery to real customers.
If it's the latter, you are 💯 correct.
No project survives first contact with customers without lots of lessons learned, and on the contact starts, ideally there is no end.