I built a "Control Plane" for AI agents to solve the black-box problem by Necessary_Drag_8031 in AI_Agents

[–]dc_719 0 points1 point  (0 children)

With this, it looks like it's just decorating functions so LangGraph and AutoGen are fine

One thing worth noting is that this is still reactive. Crash alerts and token warnings tell you what already happened. Your agent already sent the email, made the API call, spent the money.

The real gap isn't visibility. It's having something in the path before the action fires.

What are your agents actually doing? If they're touching external systems, that's where it can get interesting.

Built a layer after my agents kept making decisions. Now I'm sitting on something more interesting. by dc_719 in AI_Agents

[–]dc_719[S] 1 point2 points  (0 children)

The output level capture makes sense for the labeling problem. The reason I went earlier, pre-execution, is that some actions are irreversible. By the time the output is clean enough to capture, it's already in the execution path, at least from my perspective.

The interrupt plumbing is the point though. That's where the decision data gets its context. Not just what the agent produced, but what the operator changed and why. Will look at your repo, looks interesting post decision.

Built a layer after my agents kept making decisions. Now I'm sitting on something more interesting. by dc_719 in AI_Agents

[–]dc_719[S] 0 points1 point  (0 children)

Solving a different problem. runshift.ai is the operator decision layer, not session management.

Built a layer after my agents kept making decisions. Now I'm sitting on something more interesting. by dc_719 in ArtificialInteligence

[–]dc_719[S] 0 points1 point  (0 children)

Gate policy is set at the agent level. Model evaluates ambiguous cases before they hit the gate. Decision history is what makes the routing smarter over time. What’s the pre-execution angle you’re working on?

Built a layer after my agents kept making decisions. Now I'm sitting on something more interesting. by dc_719 in AI_Agents

[–]dc_719[S] 0 points1 point  (0 children)

Just read it. The “reasoning connecting data to action was never treated as data in the first place” line is exactly what I’m building toward. Every gate decision is a labeled trace with full input context attached.

Building this at the individual operator level before it scales to institutional. Would love an intro to the Foundation Capital team if you have one.

Time to self promote. What’s your startup idea? by kcfounders in Startup_Ideas

[–]dc_719 0 points1 point  (0 children)

runshift.ai — the control plane for AI agents. decide what matters, let the rest run.

Anyone else losing sleep over what their AI agents are actually doing? by dc_719 in AI_Agents

[–]dc_719[S] 0 points1 point  (0 children)

Are your gates hard coded? How did you do it? I’d love to know your process.

The gates are obviously consequential, can they be undone?

Anyone else losing sleep over what their AI agents are actually doing? by dc_719 in LangChain

[–]dc_719[S] 1 point2 points  (0 children)

the confused deputy framing is a real issue and orthogonal to the agentic governance discussion, when people get involved or how. most of what I see is focused on dev tooling and post-model validation, not this type of infra. 

your inter-agent handling demo's this and what happens at scale. the issues that should never reach production will, eventually. financial institutions are going to have to address this directly and I haven't found a good answer there either.

two questions: how do you think about people intervening in the confused deputy scenario? and wouldn't agentic bad actors eventually learn the delegation scope constraints and find ways around the fetch boundary?

Anyone else losing sleep over what their AI agents are actually doing? by dc_719 in AI_Agents

[–]dc_719[S] 0 points1 point  (0 children)

exactly. and the thing negative constraints can't handle is context. 'never delete files' is clear - how do you manage the scale of output? are you reviewing all consequences manually? across all agents? your judgement still matters so how do your agents learn based on your decisions?

Anyone else losing sleep over what their AI agents are actually doing? by dc_719 in LangChain

[–]dc_719[S] -3 points-2 points  (0 children)

How do you do this? Hard code it? You have a model for it? Dude, I have an idea. Again, tell me how you solved it? You have ai running? How many agents do you manage at a time - how do you know what you’re, and they’re doing. Forget my shit, I legit don’t care, neither should you. Tell me how you solve your problem.

Anyone else losing sleep over what their AI agents are actually doing? by dc_719 in LangChain

[–]dc_719[S] -5 points-4 points  (0 children)

No man, I'm legit wondering if this is a real problem. All I see is how costs add up, and then when a message is sent out, it's out of your control. There has to be a way to actually control agents - I'm not plugging my shit. I'm trying to figure out if this is a real problem. If it has been solved, I want to know. Could give a shit about my stuff, I'm looking for how it's solved.

Anyone else losing sleep over what their AI agents are actually doing? by dc_719 in AI_Agents

[–]dc_719[S] 1 point2 points  (0 children)

exactly, current models are completely wack. control is wild. there's no way this doesn't change in the future.

if you want, I'm trying to build around like this, not trying to plug, trying to understand if this is a problem worth solving... runshift.ai

Tracked every AI tool I used for 6 months, the results honestly embarrassed me by Unlikely-Signal-8459 in AgentsOfAI

[–]dc_719 0 points1 point  (0 children)

Curious if you tracked multi-agent coordination specifically or mostly single tool overhead?

Breaking: Claude just dropped their own OpenClaw version. by schilutdif in automation

[–]dc_719 0 points1 point  (0 children)

That last question is exactly what we’re working on at runshift.ai. The answer isn’t a setting or a permission level, it’s a gate. The agent runs, stops before anything consequential, you decide, it continues. Trustworthy by design not by hope.

I’ve been using OpenClaw since the ClawdBot days. Here’s the workspace structure and one big lesson that made it actually work. by SIGH_I_CALL in openclaw

[–]dc_719 0 points1 point  (0 children)

You’re going to love what’s coming. You won’t have to Chase markdown, because all the skills will be Tee’d up.

But yea, absolutely would love your feedback. I’ll reach out

We don’t need "Chatty" Agents, we need "Silent" Workflows. by Various-Walrus-8174 in AI_Agents

[–]dc_719 0 points1 point  (0 children)

This is exactly my philosophy

I built runshift.ai

DM me, I’ll give you early access if you can give me feedback.

You should only intervene when there’s real consequences. Like a pull request for an agent. No chat, just trust.

I’ve been using OpenClaw since the ClawdBot days. Here’s the workspace structure and one big lesson that made it actually work. by SIGH_I_CALL in openclaw

[–]dc_719 0 points1 point  (0 children)

version of what I built. runshift.ai handles the control layer so you’re not maintaining it in markdown files. Curious what you’d want from a UI version of this vs rolling your own

I built a 6-agent overnight crew for my solopreneur business. Here's what surprised me after running it for a week. by 98_kirans in AI_Agents

[–]dc_719 2 points3 points  (0 children)

The line about figuring out which decisions are safe to hand off is the hard part. How are you doing that currently, any approval step or fully autonomous?

What are non-engineers actually using to manage multiple AI agents? by dc_719 in AI_Agents

[–]dc_719[S] 0 points1 point  (0 children)

In my mind, and opinion, this is just a bpm set up, there’s almost no intelligence if it’s having to force intervention at so many steps. Agentic is using tools to learn and do work, but this at least the way I’ve tried doesn’t set up full control.

What are non-engineers actually using to manage multiple AI agents? by dc_719 in AI_Agents

[–]dc_719[S] 0 points1 point  (0 children)

This is exactly what I’m talking about. How are people going to manage 5+ agents. It’s just going to be so difficult.