The next era of product development is built on context and agency. Here's how Linear is evolving. And what we're launching today.
I Think They Are Lying To You
Project 2025 Tracker
A comprehensive, community-driven initiative to track the implementation of Project 2025's policy proposals
Building what customers need, not just what they ask for - Linear
Notes from our product team on building the tools we use every day.
Signals: Toward a Self-Improving Agent | Factory.ai
Traditional product analytics tell you what happened. Session duration, tool calls executed, completion rates. But they...
Regular exchange of issues between lab members to share research tasks
At the start of this project, we suggested that our graph-based "issue dashboards" would be used widely by members ...
Beyond Digital Exhaust: Reclaiming Agency in the Context Economy - A MozFest Discussion on Personal Context Infrastructure and the Future of AI
At this year's MozFest in Barcelona, we convened an urgent conversation about what may be the defining struggle of our digital future: who will control the vast
Tools – The Markup
Our tools hold institutions accountable for the way they use technology, pulling back the curtain so readers can see for themselves how technology affects them.
We Can Just Build Things
Build the tools your community needs — production-grade, privacy-respecting freedom tech, made with an AI agent and grounded in a verified, values-aligned catalog (Nostr, AT Protocol, and beyond).
Pacing the Frontier | Gillian K. Hadfield
The Pacing the Frontier letter calls on the US government to support an international effort to build the technical and governance tools needed to protect our option to pace AI development. I and others have been working on the problem of how to build such infrastructure for ten years, including participating in dialogues on AI safety with Chinese academic colleagues during the past three. Here are my suggestions: 1. Don’t rely on off-the-shelf models like FINRA and the FDA which were built for 20th Century single-domain government expertise. They’re not fit for purpose. 2. Don’t act like no-one’s thought about the AI governance problem before. We’ve spent two years refining a regulatory markets design into working legislative language, for example, and it’s now in AI governance bills in five states and in Congress. 3. Don’t try to write an exhaustive set of rules for AGI first. 4. Pick a domain that can achieve widespread global consensus to start. Mine would be recursive self-improvement: models should not build models. Build the technology that verifies that. 5. Focus relentlessly on building flexible verification infrastructure that is able to enforce whatever rules we can ultimately agree on. 6. Don’t assume we already know how to do this and governments can just write tests into law. Technology needs to be built and by the private sector. 7. Don’t wait for the infrastructure to emerge first. The components and people are there and the ecosystem can scale fast with the right incentives. 8. Incentivize large-scale investment in verification technology by building a governance structure and industry funding that creates a market for private verification organizations. 9. Use licensing and public oversight to ensure verifiers are independent of the frontier labs. 10. Protect sovereignty by enabling each government to license its own verifiers from a global market of verifiers recognized by other countries. 11. Leverage the incentive of global trade for models and model services by requiring verification for market access. 12. Just start. Sources in comments.
DevEx in Action
Somewhere, right now, a software developer is pulling open a ticket from the project backlog, excited by the prospect of working on something new. As the developer begins reading through the description of the task, their laptop is suddenly flooded with alerts from the team’s production error-tracking system, disrupting the developer’s ability to focus. Eventually, returning to the task at hand, the developer studies the requirements described in the ticket. Unfortunately, the task lacks context and clarity, so the developer asks for help, which will take days to resolve.
Value Pairs: A New Way of Approaching Product Development
How AI-enabled teams can change how we think about product development
The Tyranny of the Marginal User
why consumer software gets worse, not better, over time
Agents get budgets and boundaries - Sensemaker
Microsoft shipped more concrete agent controls while Uber put coding agents on a token budget. The agent story is becoming IT management, not demos.
