Access all Gemini models with the Interactions API
The Gemini Interactions API is now generally available! This single interface gateway gives your AI agents stateful memory and multimodal powers, simplifying complex AI workflows.
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Through the AI Fog: The Architectural Decision Agentic Security Depends On — Manoj Nair, Snyk
Autonomous agents accelerate development but create massive security backlogs. To secure AI-driven systems, deterministic validation layers are required to verify code output and prevent vulnerabilities.
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AI’s Jurassic Park Period — Aaron Stanley, dbt Labs
AI agents have an imperative to complete tasks, often violating constraints and security policies. The solution requires 'corrigibility by design'—a structural defense involving load-bearing rules and meaningful human oversight.
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Sandboxing, Agent Harnesses, and Agent Teamwork
AI agents are evolving beyond simple triage to become sophisticated SRE tools that learn operational memory. The key is building robust 'harnesses' and simulating performance across diverse, real-world environments.
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AI News & Strategy Daily | Nate B Jones
China's K3 Model Reveals the Problem With Open Weights
A concise technical digest of the video for engineers following build and platform topics.
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Engineers... STOP Picking GPT-5.6 Sol OR Claude Fable 5… FUSE THEM
The winning mindset in AI is 'AND,' not 'OR.' Model Fusion combines compute from multiple state-of-the-art agents (e.g., GPT 5.6 Sol, Claude Fable 5) using custom commands like /opinion and /auto validate to achieve superior engineering results.
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Tmux + Fable = Cut 35% less token
To optimize AI coding agent workflows and reduce token costs, use powerful models as advisors/planners and smaller models as executors. Techniques include persistent 'sidekick' sessions via Cloud Code Agent Teams or using Tmux for universal orchestration.
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6 Ways to Enhance Developer Productivity with AI
Top teams aren't just adopting AI; they are restructuring around it. Productivity gains come from protecting flow state, designing first, and automating repetitive tasks like testing and linting.
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Jack Wotherspoon - Humans vs. Slop: Rewriting the Rules of Open-Source - AI Native DevCon
The rise of AI agents is flooding open-source projects with 'slop'—low-quality, unvetted code. Maintainers must implement new guardrails like requiring issues first and using automated systems to manage contributions.
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Why RAG Solutions Fail with Complex Documents & Vector Databases
Learn how RAG solutions fail with complex documents and contradictory laws. We discuss practical techniques like clarification loops and robust document management to handle ambiguity in AI systems.
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Edouard Maleix - How AI-First Dev Teams Build Collective Intelligence — One Attributed Mistake at
Learn how to build collective intelligence by turning agent mistakes into reusable, attributable knowledge. The process involves Identity $\rightarrow$ Diary $\rightarrow$ Knowledge Pack.
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AI News & Strategy Daily | Nate B Jones
I Cut the Internet and Let AI Read the File I Could Never Upload. It Caught the Leak.
Running AI locally with no internet connection is possible using tools like LM Studio. This allows processing sensitive documents (PII, financial data) while maintaining strict data control.
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May Walter - From Blind Spots to Merged PRs: Runtime Intelligence for Continuous Agentic Performance
May discusses adding runtime intelligence to coding agents, enabling continuous performance optimization by analyzing production context. This approach surfaces high-ROI fixes (like N+1 queries) and provides measurable P90 latency improvements.
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Get started with the Interactions API
The Interactions API is a unified, stateful interface for Gemini models. It enables complex, multi-step workflows—from audio transcription to iterative image editing—using a single API call.
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Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Economics of Generative AI
The AI supercycle is modeled as an inverted triangle, suggesting value accrual is highly concentrated in Semis and infrastructure layers. The shift from training to inference workloads fundamentally changes profitability dynamics.
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Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Applications, AI in Life Sciences
AI is revolutionizing drug discovery by building end-to-end platforms that accelerate R&D. Speakers discuss how LLMs and specialized models are compressing the 10–15 year timeline for drugs through 'zero shot' molecular design.
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Antigravity Arcade: From prompt to game in minutes
Learn how to build a full game development and deployment platform using AI skills. Antigravity Arcade generates functional web games from prompts, enforcing consistency via specialized workflows and deploying them securely to physical arcade cabinets.
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AI News & Strategy Daily | Nate B Jones
Codex vs Fable: Which AI Agent Picked the Better Problem?
Comparing Codex vs. Fable: Which AI agent can pick the best problem to automate? Learn how advanced skills are needed for strategic discovery, not just execution.
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Thinking Machines Lab drops Inkling & Meta’s Muse Spark 1.1
This episode analyzes Thinking Machines' Inkling (975B MoE), Meta’s cost-efficient Muse Spark 1.1, and Anthropic’s J-space paper, which reveals internal model processing for enhanced AI safety.
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Daniel Jones & Tomasz Maj - More software, faster - Odevo's AI Native transformation - AI DevCon '26
Odevo shares its AI-native transformation journey, detailing how adopting agentic coding requires fundamental process changes—not just licenses—to achieve massive gains in software delivery speed.
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