iFeeling Daily
Daily curated AI insights you can't miss.
Harnessing Claude’s Intelligence: Patterns for Evolving Agents
Anthropic shares concrete patterns for building agent harnesses that keep pace with Claude's rapid capability growth—focusing on leveraging familiar tools, letting Claude orchestrate its own actions, and carefully pruning assumptions that become stale as the model evolves.
Claude Managed Agents: 10x Faster Production Agent Deployment
Claude Managed Agents removes months of infrastructure overhead for production agents by providing a built-in orchestration harness, long-running sessions, and scoped governance—letting teams ship 10x faster. Available in public beta, it already powers agents at Notion, Rakuten, Asana, and Sentry.
Google Cloud’s AI Monthly Recap: Agent Platform, TPU 8i, and Security
Google Cloud's monthly recap reveals the core tension of 2026: the explosion of AI models, tools, and frameworks creates fragmentation, making it hard for teams to build, scale, and secure production agents without drowning in choices. The article surfaces this as a coordination and infrastructure problem, not a model quality one. Google Cloud's answer is to unify everything under the **Agent Platform**, folding Vertex AI into it and offering no-code designers, long-running sandboxed agents, and governance tools like CodeMender. Meanwhile, hardware advances like **TPU 8i** deliver 80% better inference performance per dollar, and new models from Claude Fable 5 to Nano Banana 2 target both frontier reasoning and cost-effective scale.
ScarfBench: Benchmarking AI Agents for Enterprise Java Framework Migration
ScarfBench is an open benchmark for evaluating AI agents on enterprise Java framework migration, revealing that frontier agents achieve under 10% behavioral success. The biggest challenge isn't code translation but managing dependencies across configuration, infrastructure, and runtime environments.
How Schrödinger sped up molecular discovery by 4x with AlphaEvolve
Schrödinger achieved a 4x speedup in molecular dynamics MLFF training by using AlphaEvolve, an evolutionary AI coding agent from Google DeepMind, to optimize the computationally expensive Ewald summation algorithm. The agent replaced simple for-loops with parallel batch matrix multiplication, improving performance from a baseline of 7.9 to nearly 30 and raising the program success rate from under 1% to over 60%.
Claude Sonnet 5: More Agentic, Lower Cost
Claude Sonnet 5 offers agentic performance close to Opus 4.8 at a much lower price, with improved safety and reliability. It's ideal for multi-step tasks like coding, tool use, and knowledge work.
How Agentic AI (Codex) Is Transforming Work at OpenAI
OpenAI's internal data shows Codex adoption shifting from chatbots to agents, with non-developer use exploding 137x and tasks exceeding 8 hours growing fastest — a concrete look at the future of agentic work.
Databricks’ Agent Cloud: Why Open Source and LTAP Matter for AI
Databricks co-founders Matei Zaharia and Reynold Xin unpack Omnigent (an open-source meta-harness above coding and enterprise agents), LTAP (their database bet for live transactional data in column-oriented formats), and why agent security, spend controls, and a common API matter more than ever. The thesis: traditional software gets rewritten once the data is in the right place and agents sit on top.
Build real agentic apps using CUGA: lightweight harness, two dozen examples
CUGA (Configurable Generalist Agent) is an open-source harness from IBM that strips away the repetitive plumbing of agentic apps, letting you focus on tools and prompts. With two dozen single-file examples and built-in governance, it shows how to build agents that scale from a laptop to a governed production deployment without rewriting.