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Liberal Families Are Looking Pretty Traditional.


Show HN: Active Source of Truth for Your Coding Agents. Howdy! Happy Saturday everyone!
As a solo founder, I have always tried to maximize my speed by letting coding agents build as much as possible in parallel. However, as an engineer, I don't trust that AI will always make the right decisions and work with the right context. In the past, I always needed to click through my sessions to glance at the AI's output, try to understand what it was doing, and hopefully steer it or stop it in time.
As a result, the maximum number of concurrent sessions I could manage at once was only 4. I didn't want to be the bottleneck, so I built Meetless Agent (MLA). It basically does what I had to do manually before:
- Monitors the coding agent's tasks and actions to supply it with the correct, up-to-date context.
- Continuously reconciles running information (such as provided/tagged documentation, the agent's output, and the agent's decisions) to actively maintain the source of truth at all times.
- Keeps track of the current rules for the repo, and if an action triggers a registered rule, the rule is injected into the agent context.
My benchmarks show that running coding agents with the help of an active monitor improves quality and accuracy, consumes fewer tokens, and finishes faster: https://research.meetless.ai/stale-context/
Of course, the agent alone can't decide the source of truth; it requires human review and decisions for contradictions, etc. But for the most part, it can safely build a consistent ontology of the current source of truth.
From this, I want to build an AI layer to maintain the source of truth across the business, so I will release more connectors for Slack, Jira, Confluence, etc., soon. The goal is for this AI to assist in every part of the business. Eventually, the same coordination layer will understand that a decision made in Slack affects a Jira task, a document, an email conversation, and what a coding agent should do next without every tool becoming another isolated memory silo.
The coding agent connector is open source at:
https://github.com/Meetless/mla
I am looking forward to your feedback!


2024 South Korean martial law crisis

2024 South Korean martial law crisis.


Oura rings unable to measure any signals needed to assess sleep quality / stages.


FTC Targets Personalized Pricing, Stops Short of Ban.


The Fastest Star in the Milky Way Will Test Relativity.


Bug test: I think I cannot delete this post in the allowed window.


Darth Vader speaks out on Flock cameras at City Council meeting [video].


FTC says "personalized pricing" based on consumer data could violate the law.


Show HN: Astronomy Buddy–what's worth pointing a telescope at tonight. I wanted a simple dashboard for my TRMNL display in my entryway that told me whether it was worth taking my telescope out that night, which I ended up extending into a web + iOS app if anyone else finds it useful.
All the apps talk to my own endpoint that consumes AstronomyAPI (current celestial body positions in our solar system), 7Timer! (cloud cover, seeing, transparency), and Open-Meteo (air quality), compares to your current location/elevation/equipment, and determines both a verdict on whether it's worth stargazing tonight and what to look at if you do go out. All the logic/strings to display are contained in my API so I can adjust if needed without re-deploying the separate front ends.
Hope someone else finds it handy!


Consumer Rights Wiki

Consumer Rights Wiki.


Hall of Shame: Documented Anti-Consumer Practices.


Launch HN: Vendo (YC S26) – Let users build features on top of your product. Hi HN, we’re Yousef & Nour, founders of Vendo (https://vendo.run). Vendo lets users create new features inside the software they already use. A user describes the dashboard, workflow, or small app they need, and Vendo builds it on top of the product’s existing data, API, and interface.
Demo: https://www.youtube.com/watch?v=VdpHehY64ls
We built Vendo because every SaaS eventually faces the same problem: every customer needs something slightly different. One wants a new report and another needs a workflow that only makes sense for their team. These requests either sit on the roadmap, become one-off engineering work, or force the customer into spreadsheets and external tools. We wanted the user to be able to create the missing feature themselves, without leaving the product.
Here is how it works:
- npx vendo init reads the product's API surface, theme, routes, and more. These are used so that the apps Vendo creates (1) look on-brand and native and (2) have the ability to read data and perform actions directly through the company's API
- When a user asks for a feature, we have a custom Vendo harness that writes a React component with a bunch of Vendo add-ons and guardrails (ex. ability to make calls to the host API + our component library). Every save is compiled, type-checked, run against real API responses, and rendered before the user sees it. We just released a benchmark and write-up here with more info for anyone interested: https://vendo.run/blog/generating-product-ui-measured
- We use QuickJS to make sure that anything the agent creates is sandboxed and can't mess with the company's site. Vendo compiles the component and runs it with Preact inside a QuickJS VM with no access to the DOM, network, or clock. The VM returns a UI tree, which the host renders using the product’s registered components. When the user clicks something, QuickJS emits a tool call; the host executes it through Vendo’s guard and passes the result back into the same VM, preserving the screen’s local state.
There's a lot of generative UI right now: streaming developer-written components into a chat (Vercel AI SDK, CopilotKit, Thesys), or rendering your app inside someone else's assistant (OpenAI Apps SDK, MCP Apps). We differ on two things. Vendo lives in your product and acts through your API as the signed-in user, so what it makes is durable: real apps users keep, pin, and run on triggers while they're away, and not components that are merely confined to a chat. Plus, it's not capped at putting together a bunch of prebuilt components: the agent can build arbitrary apps, from a quick dashboard out of your own components to real custom code running in a sandbox, and either way data only ever comes from tool calls to your API.
Here are some things customers are using Vendo for today:
- Letting their users create custom dashboards and reports. These are mainly UI-based and focused on letting the user see the exact graphs and metrics they care about
- Letting their customers create recurring automations. A big thing as well that has been used for these automations is the fact that we connect to external connections, so users have been automating many of their inter-tool workflows (ex. an automation that sends a slack alert based off of something in the product)
- B2B customers letting their customers customize the product with specific business logic. Often this is simple things like an extra field on a form, or an extra permission, but it is hard for a business to keep up with them otherwise.
- Creating and sharing custom dashboards/apps across an organization. Since the apps Vendo creates are durable, they can be shared, reused, and forked (which can’t be done with many of the other in-chat generative UI solutions)
We've spent a lot of time thinking about how AI and agents will change the way people consume software. We think the answer is personal(ized) software: you see the UI you need to see, you tell an agent exactly what you need, and the product molds to how you work.
The key insights that have enabled the product to work are:
- A rule in code always beats a rule in a prompt.
- Invent as little syntax as possible. Generation got faster and more reliable when the output looked like what models already know (JSX-shaped markup) instead of a clever custom format.
- Deterministic beats model wherever you can get away with it. Theme extraction is pure static analysis, and a remix starts as a copy of your component, no model call.
Vendo is completely open-source (Apache-2.0) and can be self-hosted, so feel free to c


FTC Warns Retailers on Using Private Consumer Data to Raise Prices.