Mathias Kleverud

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Mathias Kleverud

Mathias Kleverud

@mathiiias

founder @humfrid_com | shared memory for product orgs | extraordinary alien

Menlo Park Katılım Şubat 2009
402 Takip Edilen125 Takipçiler
Mathias Kleverud
Mathias Kleverud@mathiiias·
One of @humfrid_com's best qualities is his ability to push back. Most agents agreeable. Humfrid isn't agreeable. He's on your side.
GREG ISENBERG@gregisenberg

Every AI right now is a "yes man", and I'm soooo tired of it. Maybe you are too. I don't want an LLM that claps for everything I do. I want the one that tells me my writing is weak, my logic falls apart halfway through, and I've been lying to myself about the thing I keep dodging. You can engineer an AI with a spine. Here's the exact setup I use: 1. Write a "critic" skill. A markdown file whose only job is to attack the work. It hunts for the weakest claim, the dodged question, the thing you're avoiding. Every agent that loads it gets a spine by default. 2. Run two agents against each other. One builds, one tears it apart. The builder has to defend or fix. You get the truth from the friction instead of from a single agent trying to please you. 3. Score against evals. Give it a rubric with real criteria and have it rate the work 1-10 on each. A number tied to a standard forces honesty that "what do you think?" will always dance around. 4. Make it cite evidence for every criticism. Set a rule: no critique without a concrete example from the work and a reason it matters. It has to show its work, so it can flatter you or hand wave. 5. Give it a kill criterion. Tell it the exact condition where it has to recommend you stop entirely. "If X isn't true, tell me to shut this down." Most agents will optimize a doomed idea forever because you gave them permission to call it dead. I've learned that the default AI claps for you. That's cool for a bit but it gets old quick. If you actually want to build exceptional products, create top 1% work, and grow as a person, you need an AI that pushes you harder than it flatters you. We're in the age of agency. The people who win are the ones who go build the version that tells them the truth. Best time to build there's ever been. Go get 'em.

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Mathias Kleverud
Mathias Kleverud@mathiiias·
Wanted to share a few technical breakthroughs that I'm particularly excited about. > Long-horizon goals: Humfrid can achieve goals over time Most agents complete work ad-hoc. You get tasks done, but nothing connects them to why they matter, or what difference they make over time. Humfrid keeps track of progress over time and finds the next step to get you there. He connects all work to its goal and purpose, and understands how it fits together. It’s the difference between an agent that completes tasks, and an agent that is actually working for you. > Proactivity: Humfrid doesn't wait to be asked From a UX point of view, the work we do with LLMs is demanding - you keep prompting and asking and waiting for answers. But you don't always know what you need to know. That's the most stressful part about work - the feeling of "did I miss anything?". Humfrid doesn’t wait to be prompted. He watches for stalled work, contradictions, and upcoming meetings, and then surfaces what matters at the right time. It's always grounded in your goals and context. > Context maintenance and retrieval: Humfrid aims for an objective truth Context is the whole game with agents. Wrong context means wrong actions and mediocre work. Humfrid is smart about context. Like, really smart. First, he's especially annoyed about contradictions in facts and decisions. If two data points don't add up or if a decision conflicts with what the data says, he'll tell you. Second, we’ve worked a lot on the retrieval so he fetches the right information - ranked for this person, this goal, this moment. The result is an agent that takes the right action and produces high-quality work, based on an objective truth that has not been achievable in organizations until now. > Sub-agent coordination: Humfrid completes work with specialists Humfrid does not only keep track of information for you, but completes the work you need done. You can simply ask Humfrid to ship PRs, prepare blog posts or research customers, and he'll get it done by spinning up specialist sub-agents. -- We'll keep making Humfrid even more helpful over the coming months - happy to hear your feedback.
Humfrid@humfrid_com

Today we’re announcing Humfrid. Humfrid is the agent product teams actually want to work with - from first idea to shipped product. Tell him your goals and he works proactively alongside you and your team in Slack to reach them. What does Humfrid actually do? 🐦‍⬛ He keeps track of your goals. Following up on metrics long after you've moved on to the next bet, and noticing when you're off track before anyone else does. 🐦‍⬛ He sharpens your thinking. Surfacing evidence with the numbers and customers quotes you need, drafting the questions you haven't asked yet, and pushing back when you rush to build before you've understood the problem. 🐦‍⬛ He keeps everyone aligned, without the meetings. He catches contradictions the moment they surface - when two teams are solving the same problem, a decision doesn't follow your product principles or when the PRs don't match the brief. Most agents are endlessly capable, but opinion-free. Humfrid isn't - he has a point of view about how product should work. Most agents are agreeable. Humfrid isn't. He's on your side. Meet Humfrid here - it's free to get started. → humfrid.com

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Mathias Kleverud retweetledi
Humfrid
Humfrid@humfrid_com·
Today we’re announcing Humfrid. Humfrid is the agent product teams actually want to work with - from first idea to shipped product. Tell him your goals and he works proactively alongside you and your team in Slack to reach them. What does Humfrid actually do? 🐦‍⬛ He keeps track of your goals. Following up on metrics long after you've moved on to the next bet, and noticing when you're off track before anyone else does. 🐦‍⬛ He sharpens your thinking. Surfacing evidence with the numbers and customers quotes you need, drafting the questions you haven't asked yet, and pushing back when you rush to build before you've understood the problem. 🐦‍⬛ He keeps everyone aligned, without the meetings. He catches contradictions the moment they surface - when two teams are solving the same problem, a decision doesn't follow your product principles or when the PRs don't match the brief. Most agents are endlessly capable, but opinion-free. Humfrid isn't - he has a point of view about how product should work. Most agents are agreeable. Humfrid isn't. He's on your side. Meet Humfrid here - it's free to get started. → humfrid.com
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Mathias Kleverud
Mathias Kleverud@mathiiias·
As a product manager you sometimes feel like you have to be a superhero So why not browse product context like Iron Man
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Mathias Kleverud
Mathias Kleverud@mathiiias·
/goal as it should be actual business objectives as the goal key results as verifiable outcomes problem spaces, possible solutions and tasks as the work tree
Mathias Kleverud tweet media
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Mathias Kleverud
Mathias Kleverud@mathiiias·
@snoopy_dot_jpg we're making our best attempt with @momentalos - it's defining the greater loop (business goal -> metrics to verify impact of tasks made). not fully there yet, but confident the architecture will work in the long run
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Mathias Kleverud
Mathias Kleverud@mathiiias·
imo they all need to be combined (and i see sims as subset of event-driven, we use it as a tool to produce sensor data) just relying on one or the other never produces good outcomes, good product management is knowing when to listen to feedback, when it should shape strategy and when it should be ignored
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Peter Zakin
Peter Zakin@pzakin·
The tldr. There are different kinds of "loops" that help agents figure out what they should work on. 1. Event-driven: Systems process sensor data (customer feedback, bug reports, observability etc...) in ways that uncover work that agents need to perform in pursuit of well-defined objectives. 2. Explorers: Agents continuously investigate the search space of possible improvements in ways that reflect company goals, strategy, and taste. 3. Sims: Synthetic users navigate the product to unearth potential issues before customers see them.
Peter Zakin@pzakin

I've thought a lot over the last few years about what it takes to build the autonomous product org; essentially loop design. The critical feature of an autonomous loop is autonomously figuring out what work needs to be done. One way of doing this is to stitch together sensors and clearly defined business objectives. This is the easiest kind of loop to architect and reason about (e.g. an autonomous bug fixer that remediates issues observed through error monitoring tools). There's another pattern I've been thinking about lately for how agents can figure out what work to do without clear event-trigger or our explicit say-so. The pattern is basically to clearly define objectives and place agents in data streams or environments that provide rich enough context to produce high-confidence suggestions of work to pursue. Examples I've been thinking about: - Explorers who propose work to do not in reaction to realtime events, but who search over the space of potential improvements given well-stated business objectives. - Sims which generate product insights from the behavior of synthetic users. Every product should be run in sim. A few closing thoughts: - I believe that every discrete step up the abstraction ladder produces good candidates for startups to compete against AI players who face the uncomfortable truth that dominance at one rung doesn't necessarily transfer to the next one. - I am pretty bummed I didn't get to invest in an agent orchestration tool... I would love to make up for it by investing in the set of companies that build the sensor, sim, or orchestration infra that enable the autonomous product org.

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Mathias Kleverud
Mathias Kleverud@mathiiias·
agent looping is agent leadership you can micromanage one agent/human 1:1 or you can provide the goals, the guardrails, the principles and the structure where high-level goals and intent is enough for the agents to figure out the right set of actions
Matt Van Horn@mvanhorn

x.com/i/article/2063…

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Mathias Kleverud
Mathias Kleverud@mathiiias·
we've built @momentalos on "loops" - but the big loop, where the goal is a business goal and verification is measuring what tasks actually have an impact on metrics, and then doubles down on what works it forces prioritization of how tokens are spent (it's simply the prod mgmt loop), and we also have a budget cap on each goal ("this goal is worth x monthly")
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Gergely Orosz
Gergely Orosz@GergelyOrosz·
If you built something specific that can be shown with loops that is useful, feel free to share. I see experimentation happening for those who don't have budgets (either working at eg an AI lab, or just being happy to burn hundreds on an idea that is throwaway output)
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Gergely Orosz
Gergely Orosz@GergelyOrosz·
On the whole “just use loops” Outside of the increasingly few people who 1) have unlimited AI token budgets 2) feel like prompting agents are holding them back (usually thanks to no #1) I don’t think many have a use case for them. I’m more than content prompting (esp w #1!)
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Mathias Kleverud
Mathias Kleverud@mathiiias·
figuring out what's between us and reaching our goal. > suggestions to review and edit > grounded in our company context > smooth ui
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Mathias Kleverud
Mathias Kleverud@mathiiias·
shared obsidian meets miro/trello for agents and humans might sound messy but its pretty neat
Mathias Kleverud@mathiiias

please checkout momentalos.com! it's shared obsidian meets miro/trello for agents and humans you set a goal and get help breaking it down into what needs to be done based on your memory and context drag and drop our cloud agents, your mcp connected agents (claude code, hermes etc) or humans (or your human teammates' agents!) to put them to work steer work and get updates on whatsapp, pull in data from ga and ship directly to github

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Mathias Kleverud
Mathias Kleverud@mathiiias·
please checkout momentalos.com! it's shared obsidian meets miro/trello for agents and humans you set a goal and get help breaking it down into what needs to be done based on your memory and context drag and drop our cloud agents, your mcp connected agents (claude code, hermes etc) or humans (or your human teammates' agents!) to put them to work steer work and get updates on whatsapp, pull in data from ga and ship directly to github
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GREG ISENBERG
GREG ISENBERG@gregisenberg·
I wish Slack was: - Agent-first - Beautiful to use - Integrated with agents natively so your Hermes or OpenClaw lives inside it - Huddles worked seamlessly and were fun - Built for teams of 1-3, not just teams of 300 - Truly a second brain similar to Obsidian - Searchable without wanting to throw your laptop - Designed around async, not constant interruption - Voice first for mobile - A place where I could see who's working on what right now without asking anyone - Smart enough to know the difference between "I need you right now" and "whenever you get to this" - A workspace where my agent could tap someone else's agent on the shoulder and coordinate without involving either human - Designed so the new hire on day 1 has the same context as the person who's been there 3 years -Something that felt like walking into a room of people building, not walking into a room of people typing - A place where decisions are first-class objects - Able to auto generate SOPs, skills, agents etc from conversation history - Something that rewards deep work instead of punishing it with 47 unread notifications
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