The 50-year arc from "thinking about thinking" to AI agents that monitor their own uncertainty, replan when stuck, and store reflections as memory. Flavell, Nelson-Narens, Fleming, Wells, to Reflexion, Self-Refine, semantic entropy, o1, and Taskade Genesis.
Context engineering is the discipline of 2026. See how Workspace DNA — Memory, Intelligence, Execution — turns a workspace into a living context stack that AI agents can actually use, extend, and remember.
The 11 best AI text converter tools of 2026 ranked by output format. Taskade leads for text-to-markdown, flowchart, HTML, and PDF-to-outline. Free tiers compared.
11 best PDF to mind map AI tools of 2026 ranked and tested. Taskade Genesis leads for multi-source conversion across PDF, video, spreadsheet, and image inputs. Free + paid picks.
The 40-year arc from David Deutsch's 1985 paper to AI agents that build apps in parallel branches. Hugh Everett's many worlds, Feynman's interference, Wheeler's "It from Bit," and how Taskade Genesis ships the first commercial multi-agent system that actually uses the math.
A living knowledge graph, a neon task manager, and a smart recipe planner. Three Taskade Genesis daily-driver apps you can clone free.
11 best AI system design tools of 2026 ranked for devs and architects. Taskade Genesis for workspace-native architecture, Eraser AI for engineering docs, IcePanel for C4 modeling.
How Taskade runs reliable AI agent orchestration and automation pipelines on a durable execution foundation — patterns, lessons, and production tradeoffs.
How Taskade combines OpenSearch full-text, 1536-dim HNSW semantic vectors, and file content OCR into a single permission-aware search system. 70% of queries are still keyword lookups.
How Taskade's Workspace DNA — Memory, Intelligence, and Execution — creates a self-reinforcing loop where software gets smarter the more you use it. An engineering deep-dive into the architecture behind living software.
I read Doraemon every day as a kid. It turns out a Japanese manga from 1969 described the right architecture for AI agents — and almost every company building agents today is getting it wrong.
One of our most active Genesis users has built hundreds of apps. He also wrote our debugging framework, which we adopted as official docs. When a platform invites power users to build it with you, a different kind of company emerges.
