AI industry builder / agent workflows
Brad ZhangLongform AI writing, forum-grade X thinking, and open-source proof for founders, operators, and early AI teams.
Open to
Remote / Sprints
Topic dossier
Persistence, compression, retrieval, and the editorial judgment behind what a system should keep.
What deserves to survive between sessions, and what should be compacted, rewritten, or deliberately forgotten?
Memory is treated here as an editorial surface rather than a warehouse. The topic is less about infinite recall than about what changes the next judgment.
Lead essay
Useful memory is not what survives by default. It is what a system learns to preserve on purpose.
A long-form essay on why agent memory should be treated as editorial selection rather than infinite accumulation.
SEO intent / Founder question
Teams diagnosing why RAG systems still feel untrustworthy in real workflows.
Capability promise
Failure diagnosis, retrieval loops, evidence presentation, skill routing, and trust-oriented UX.
Project evidence
Memory as a recoverable working surface
A memory system for coding agents that values persistence, reuse, and editorial recall over mere accumulation.
Reading as a technical operating system
A paper-reading tool that frames comprehension as an active workflow of margin notes, synthesis, and return visits.