Make Honesty Less Risky Than Silence for Your Engineering Team
Your team may already know the risk. The question is whether they feel safe saying it.
QA Is What Happens When Software Meets Reality
Developers can prove the code works in a controlled environment. QA checks whether it survives the messy, unpredictable world customers actually live in.
Review fatigue is real. Here’s what my team did about it
When the volume of code outpaces the cognitive budget of the people asked to read it, fatigue happens.
Netlify CTO: “No longer should my developers be writing code”
Dana Lawson leads R&D at Netlify, overseeing engineering, product, and design. From where she sits, she sees the real shift clearly: one person or a tiny team can now cover far more ground.
How We Catch Messaging Campaign Drift Before It Spreads
Over time, the content a messaging campaign sends can shift away from what was originally approved. We call this campaign drift, and in business messaging, it's a real and recurring problem.
MongoDB: One write, two logs
At 55,000 operations per second across a 20 TB sharded cluster, you stop theorizing about databases and start reading their source code.
Runbooks Are Dead; Make Operations Executable
Static runbooks break under pressure. Operational knowledge should live in executable tools instead of documents nobody can follow at 3 AM.
LLMs Have a New Limit – It Costs More to Think Longer
NVIDIA’s Igor Dmochowski explained that LLMs are no longer limited just by model size or benchmark scores; the cost of longer reasoning means runtime, context length, memory use, and throughput matter just as much.
OpenAI’s Luis Velasco: Code is very cheap to produce, but the system around it isn’t
Luis Velasco works as a Forward Deployed Engineer at OpenAI. For him, code is becoming very cheap to produce, while building the system around the model is becoming critical.
Only 7% of Organizations Using Kubernetes for AI Do So Daily
Two-thirds of organizations run AI workloads on Kubernetes, but only 7% do it daily. Katie Gamanji says the ecosystem still needs better operational maturity and standards.
AI speeds up prototyping, but teams still need to distinguish decisions from assumptions
Figma’s Designer Advocate argued that AI can make prototypes look finished too early, which can hide dangerous assumptions.
Google DeepMind: AI’s Next Step Is Learning From Its Own Experience
We’re waiting for the next big AI leap - systems learning from their own experience rather than just human data - and at Infobip Shift, Google DeepMind’s Benoit Schillings said that’s exactly where the field is headed.