
Stop Prompting. Start Designing Loops.
The next useful AI skill is not a better one-shot prompt. It is learning how to turn repeated work into supervised systems…
Timeglass is an AI-powered knowledge platform that gives teams a persistent, queryable memory of everything happening inside their company. It is built for engineering, product, operations, and leadership teams whose institutional knowledge is scattered across Slack, GitHub, Notion, Linear, email, and meeting transcripts. Instead of relying on an employee to remember where a decision was documented, Timeglass continuously ingests work signals and lets anyone ask natural-language questions about projects, decisions, context, and status. That makes it especially useful during onboarding, cross-team handoffs, retrospectives, and executive reviews where missing context slows teams down. What makes Timeglass notable now is that it treats organizational memory as a first-class AI infrastructure problem rather than a search feature bolted onto a chatbot.
Reader rating
No ratings yet
You might also like
Ollama is a local AI platform for running, managing, and sharing open models on your own machine or private infrastructure. It makes it easy to pull models, serve them through an API, and integrate local inference into developer workflows without relying on a fully managed cloud stack. Teams use Ollama for privacy-sensitive assistants, internal tools, offline experimentation, and rapid testing of open-weight models across laptops, workstations, and servers. It is especially useful for developers, operators, and AI builders who want quick setup with less operational overhead. What makes Ollama distinctive is how approachable it is: it packages model runtime, distribution, and deployment into a streamlined experience that helps people get productive with local AI in minutes instead of spending days on configuration.
OpenAgentd is a self-hosted AI-agent OS that runs entirely on the user’s machine. It provides a web cockpit, streaming chat, persistent editable memory, tool use, workspace file browsing, image viewing, local voice transcription, scheduling and multi-agent teams with lead-worker delegation. Agents can read and write files, run shell commands, search the web, generate media, manage todos and extend capabilities via skills or MCP servers. The tool is for users who want a local, inspectable alternative to cloud-only agent workspaces. It is notable now because privacy, long-running autonomy and multi-agent coordination are converging into desktop systems rather than isolated chat tabs.
Together AI is an AI inference and training cloud platform that provides fast, cost-effective access to open-weight models. It offers fine-tuning, inference endpoints, and a startup program for early-stage companies building on open AI. Targeted at developers and startups who want an alternative to proprietary model APIs with transparent pricing and open-model support.
From the blog

The next useful AI skill is not a better one-shot prompt. It is learning how to turn repeated work into supervised systems…

AI teams are learning that token spend is easy to count. The harder question is whether those tokens changed any real work…

Anthropic didn't just release a new model. It shipped two versions of the same brain, and quietly invented the playbook every AI company will copy. The Mythos split isn't an AI story. It's a product strategy story…