635 Photos and videos
We know #dataengineers spend hours investigating pipeline failures.
Now Otto #agent from @astronomerio reads the logs, finds the root cause, spots recurring patterns, and suggests a fix.
Finally, a teammate that enjoys reading logs: astronomer.io/blog/investiga…
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Bigger isn't always better. Turns out 80% of #AI workloads don't need an expensive genius, just a fast, cheap model that gets it right. Great work @FireworksAI_HQ proving the point: techcrunch.com/2026/06/09/ca…
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Frontier labs are running the same lock-in play #hyperscalers ran. Tooling layer capture, not token price, is the real risk. #opensource won the #cloudcomputing era. It'll win the #agenticAI one too
langchain.com/blog/model-neu…
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Turns out “world models” aren’t just #AI making pretty videos of cats in space. The real challenge is building systems that can predict, plan, and not immediately drive the robot into a wall...and if anyone should know, its the author
drfeifei.substack.com/p/a-fu…
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With some help from @cyera_io, we finally measured how broken permissions are
osohq.com/post/we-finally-me…
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What's not to love - #opensource and #AI. @RedHat turns to @ApacheAirflow and @astronomerio to deliver #agenticAI astronomer.io/blog/airflow-i…
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The next data stack shift:
Old world → #ETL pipelines → dashboards
New world → #context pipelines → #AI agents
Models aren’t the bottleneck anymore. Context is.
The winners will build the AI context layer: substack.com/home/post/p-190…
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If #AI #agents become the primary “users” of #databases, a lot changes: query patterns, isolation, ephemeral environments.
Interesting industry perspective. Keen to see how other database vendors approach this shift.
thenewstack.io/databases-for…
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Visa-scale data orchestration
I put together a new Airflow in Action case study on how @Visa runs @ApacheAirflow for critical #Analytics and
data workflows, with a ready made #Context layer for #AI
astronomer.io/blog/airflow-i…
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If your #AIAgents can call tools, read data, or execute workflows…you’ve built an authorization problem.
I wrote a guide on preventing over-permissioned agents for my friends over at @osoHQ :
osohq.com/learn/how-to-preve…
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The team at @datadoghq processes 100 trillion events per day. How do you orchestrate data workflows at that scale? In our latest @ApacheAirflow in Action case study, Datadog shares why they adopted #Airflow 3: astronomer.io/blog/airflow-i…
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Seeing @ApacheAirflow increasingly deployed as a shared platform across #Engineering teams.
Dag-level roles on @astronomerio add the missing piece: fine-grained access control so teams only see and operate the pipelines they own. astronomer.io/blog/dag-level…
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How #SoftwareEngineering is evolving in face of #AgenticAI. Specs should be equations, not essays. Precision wins over prose when AI writes code. Also addresses risk of "cognitive debt"
fromanengineersight.substack…
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Left #MongoDB thinking CAP theorem was behind me. #Agents pulled me right back in: Capability, Autonomy, Permissions: pick 2.
The difference: CAP is physics. The agent version is an infrastructure problem and these are solvable - the @osoHQ take
osohq.com/post/the-cap-theor…
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Nearly 50% of #AI #agentic usage today is in #softwareengineering. The other half? Fragmented across 16 industries with most under 5% each. Coding may be saturated. Vertical AI agents are the wide-open frontier. garryslist.org/posts/half-th…
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Mat Keep retweeted
Feb 24
We made an implicit bargain with overpermissioning: bad, but not bad enough to fix. It worked because humans sleep, work business hours, slow down.
Agents have no remorse and no speed limit. The bargain is over.
osohq.com/post/least-privile…
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"Cognitive debt" is gaining traction. Fueled by #vibecoding it slows teams down more than #techdebt, accumulating when assumptions aren’t documented and context is lost. Product Requirement and Design Decisions docs have never been more important! simonwillison.net/2026/Feb/1…
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