Congrats to Curious Cardinals on launching FlightPlan
LFG Audrey Wisch and Alec Katz! Been awesome to see their journey over the years. They have the right mindset to blend AI and human touch in their product.
The FlightPlan is live. This launch date is deliberate. May 1st is National College Decision Day: the moment every high school family in America watches seniors commit to college and quietly starts asking what it means for the students who come next.Read Audrey Wisch’s full post on LinkedIn
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Newer: Anthropic launches an enterprise AI services firmSoftware architectureAI agents
Absurd, a Postgres-native workflow engine for edge agents
Really cool Postgres-native workflow system. The agent's entire pause/resume state lives in the DB; the worker process can exit. For running AI agents on the edge on end client machines, this is the unlock: because the whole engine is one SQL file + stored procedures with no broker, no coordinator, no SDK-based orchestration in code. It also makes the entire execution workflow history immutable and viewable by a self-reflection agent. On local/edge where processes die routinely (laptop sleeps, browser tab closes, network drops, edge worker suspends), an agent that has already made 20 expensive tool calls resumes at step 21 instead of re-paying for everything. You get this without writing checkpoint code or a state machine; the trace of completed steps is the agent's memory. I’m a fan of the pattern where the data itself captures the state in an idempotent sort of way. earendil-works.github.io/absurd
AI agentsSoftware architecture
Separate working agents from codegen agents that build them
As agent prompts become an important part of the codebase, there needs to be an explicit separation of an agent with a prompt that does something and a codegen agent that generates another agent. An example is in scraping, a first agent uses the screenshot and DOM structure to fetch some data. And a meta codegen agent generates a piece of typescript code + prompt that is essentially the first agent. So the codegen agent is creating the prompt and agent graph the agent that does the work.
Enterprise AI
Enterprise knowledge is the new walled garden in AI startups
A new type of walled garden is now taking shape with enterprise knowledge, as they translate their workflows into closed-source AI startups. Both the code, as well as data, are going into these new silos. Enterprises are spending a bunch of effort to translate their workflows, processes, and memory into proprietary, closed source, non-interoperable structures that live in the source code and databases of some short-lived AI startup. This needs to be addressed with a new type of open intelligence system similar to open source. It requires rethinking the deployment, licensing and ownership of code, data and memory.
Customers and partnersEnterprise AI
Congrats to Sentra on raising $5M for organizational memory
Congrats Andrey Starenky! It's been a blast building with you. Sentra has figured out the right architecture for organizational context and memory. Excited for the road ahead....LFG!
AI agents
Anthropic launches Claude Managed Agents
Anthropic launches managed agents. This allows a non-technical user to build an agent in their Claude code desktop app and deploy in the Anthropic cloud to make it live. With this release, Anthropic moves into the space of sandboxes and infrastructure in general. platform.claude.com/docs/en/managed-agents/overview
Coding agents
The product trap of harness engineering and agentic coding
Harness engineering and agentic programming are super addictive and fun, there's strong parallels with video gaming. However, this will lead to a lot of smart, non-technical folks building software just for the sake of it without clarity on user pain points. I call this the “product trap.” Building software is gratifying in the minutes and the hours people are building small tools for themselves, but the act of creating the software itself is not a substitute for solving real user pain points
Coding agents
An open source fix to cmux for respawning agent teams
Was fun to make a small open source contribution to cmux.dev. I ran into an issue where claude was not able to find the surface id for its agent team members after the first run had completed. Fixing this allowed me to be able to re-spawn the agent team members after they had been shut down previously in that session. PS: for advanced users, you can use TeamCreate, TeamDelete, and SendMessage to allow the orchestrator agent to manage the child team members. github.com/manaflow-ai/cmux/releases/tag/v0.63.2
Coding agents
Claude Code needs an army of cloud sandboxes
While Claude Code is amazing as a tool on developer desktops, there feels this need to have an army of cloud sandboxes where you would want to run multiple concurrent codegens and the desktop is just playing the orchestrator role. Further, this would allow these sandboxes to also have things like browser-use and desktop-use access.