How Fin Doubled Its Engineering Capabilities With AI Agents
Fin's Senior Principal Systems Engineer explains how agents took over low-risk work and how Fin counts the result: merged pull requests.
Archive for the tag: Infobip Shift 2026
Dan Maher from Datadog Says AI Agent Reliability Is an Engineering Problem, Not a Model Choice
The Senior Technical Advocate and Researcher at Datadog explained what actually determines whether an AI agent is trustworthy.
Todoist Founder: Developers Should Focus on Solving Customer Problems
I spoke with Todoist founder and CEO Amir Salihefendic about where developers and founders can find opportunities and what they should focus on next.
Chris Davidson, Atlassian: “Ask AI to Challenge You”
As a Solutions Engineer at Atlassian, Chris Davidson works with clients in an effort to make the most of Atlassian's tools and has first-hand experience of how we adapt to using AI.
The Real Problem in Voice AI Is Latency
Voice AI may be sold as a model problem, but the real bottleneck is whether the system can survive real-time demands, stay reliable, and do it at a cost that makes sense.
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.
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.
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.
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.