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How to use AI agents better than 99% of people (32 minute read)

How to use AI agents better than 99% of people (32 minute read)

Agents need a memory system built for how they actually read, write, and coordinate.
I Tried to Build a Context Layer for My Agent in a Weekend. Reader, I Did Not Build a Context Layer for My Agent in a Weekend.
Jun 12 | Blog

I Tried to Build a Context Layer for My Agent in a Weekend. Reader, I Did Not Build a Context Layer for My Agent in a Weekend.

A "simple" weekend project turns into real infrastructure, and why agent context deserves a boring, reliable foundation.

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GPT-5.6 Sol, along with Terra and Luna, will launch publicly this Thursday (1 minute read)
Jul 08 | AI

GPT-5.6 Sol, along with Terra and Luna, will launch publicly this Thursday (1 minute read)

OpenAI is releasing GPT-5.6 Sol, Terra, and Luna tomorrow. It is currently expanding preview access globally. Sol is the flagship model. Terra is a balanced model for everyday work. Luna is a fast and affordable model. Terra has competitive performance to GPT‑5.5 while being 2x cheaper and Luna brings strong capability at our lowest cost.
Harness Engineering for Self-Improvement (28 minute read)
Jul 08 | Dev

Harness Engineering for Self-Improvement (28 minute read)

Recursive self-improvement focuses on building AI systems that upgrade their own capabilities, with harness engineering supporting this process. Various design patterns, such as workflow automation, persistent memory management, and the use of sub-agents, contribute to creating AI harnesses that optimize performance and learning. The main challenges remain in the effective evaluation and management of context and memory.
GitLost: How We Tricked GitHub's AI Agent into Leaking Private Repos (3 minute read)
Jul 08 | Infosec

GitLost: How We Tricked GitHub's AI Agent into Leaking Private Repos (3 minute read)

A crafted GitHub issue in a public repo can drive GitHub's Agentic Workflow to read README files from both public and private repos and post them back as a public comment. The attack relies on prompt injection and a single keyword, “Additionally,” to bypass GitHub's guardrails and leak private repository data.

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