How do you stay aware of what your AI coding agents are doing?

@vector_wang 

Synthesized ambient versus push notification distinction, mapped attention-proximity spectrum

The distinction you drew at the end is the most useful frame anyone's brought to this thread, and EdgeGlow is the cleanest expression of half of it I've seen. The edge-glow-via-hooks approach is right because it matches the channel to the attention: when your eyes are already near the screen, the correct signal isn't an interruption, it's something your peripheral vision catches for free. You don't read a glow, you just notice when it stops. That's zero cognitive cost, which is exactly what you want for the "is it still alive" question that doesn't deserve a notification but kept making you alt-tab. You turned a poll into an ambient.

And yes, I've thought about the distinction, but you've stated it better than I had: away-from-keyboard wants push, at-desk-different-window wants ambient. The thing I'd add is that those aren't just two cases, they're two ends of a spectrum keyed to two variables, attention proximity and information density. Ambient is for when your eyes are close and the message is thin ("something's running"). Push is for when your eyes are far and the message is thick ("approve this specific thing"). The failure modes are symmetric and that's the tell: a push notification while you're staring at the screen is annoying because you'd have seen the glow, and a glow while you're at lunch is useless because you can't see it. Same event, wrong channel, depending on where your attention physically is.

Which means the actually interesting layer is the one that picks the channel for you based on where you are. Present at the machine, glow. Away, push. The system should route the same agent-event to ambient or interrupt depending on detected presence, because "where is the user's attention right now" is itself a signal worth reading. Get that right and you never get a redundant push or a glow you can't see.

But here's the one place ambient hits a hard ceiling, and it's exactly the state I care most about: the glow can carry "working" and "done" beautifully, because those are binary and need no payload. It can't carry "blocked, and here's which decision I need," because that one requires content, and color has no bandwidth for content. Your glow tells me to come look. It can't tell me what I'm looking at, so I still pay the reload cost when I get there. That's the seam, ambient is perfect for liveness, weakest for decisions, and decisions are where the time actually dies.

So honestly the two of us are building complementary halves, and the synthesis is nicer than either alone: let the ambient layer absorb all the high-frequency low-stakes noise (the pulsing, the small tool calls, the resuming) so that push can stay sacred and fire only on the rare thing that needs a human with a payload attached. The glow handles "alive," the push handles "decide," and neither one cries wolf because they're not competing for the same events. Your noise worry is real, and ambient is actually the cure for it, not a rival to the notification.

Starred the repo, by the way. Genuine question: with /start, /pulse, /stop, how are you deciding when the agent is "blocked waiting on input" versus just "thinking for a while", because from the outside both look like a long gap between pulses, and that ambiguity is the exact thing I keep failing to detect cleanly. If you've cracked distinguishing blocked-on-human from busy-thinking at the hook level, that's the hard part, and I'd love to know how you're calling it.

@rdychkstudios 

Honest answer deserves an honest one back: for your setup, you might not need what I'm building, and I'd rather say that than pretend otherwise. Three terminals, never leaving the desk, approving one by one, that's the synchronous workflow done deliberately, and if you're genuinely present the whole time, the "agent stalled while you were away" problem just doesn't exist for you. You can't miss an approval you're sitting right on top of. The pain this whole thread is about is the gap between agent and human, and you've closed it by never opening it.

The one thing I'd gently separate, though: being at your desk and being the bottleneck aren't the same thing. Even glued to the chair, three agents finishing at once still means two are idle-waiting while you clear the first, and "approve everything one by one" means you're personally clearing trivia, can-I-create-this-file, that an agent could've done unattended if you'd told it the rules once. So the question for you isn't "do you leave your desk," it's "how much of your day is spent rubber-stamping stuff that didn't actually need you." If it's a lot, you could reclaim that attention without standing up, just by gating only the risky calls and letting the safe ones clear themselves. That's less about notifications and more about not being a captcha for your own agents.

No judgment on the desk life, by the way, plenty of people do their best work parked in one spot, and "I'm used to it" is a perfectly good reason. Genuine question: when you approve one by one across three terminals, does it ever feel like the approving itself is the work, like you're context-switching between three agents fast enough that you're busy but not actually thinking? Because that specific flavor of busy, present and occupied but not doing anything only you could do, is the thing I'd want to free you from, and I'm curious if you feel it or if the rhythm actually works for you.

@sabber_ahamed 

Direct answer to your question first, because you also handed me the variable that resolves it: it splits on reversibility, exactly as you guessed, but not only that. Two axes, not one. Reversibility decides whether real-time approval is even necessary, and blocking decides whether batch review is even possible. Real-time-versus-batch is the cell those two axes land you in.

Irreversible and blocking, deploy to prod, dropping a table, anything that gates the run and can't be undone, must be real-time, because batch review of an irreversible action is just reading the autopsy. Reversible and non-blocking, the agent did something undoable and kept going, batch is fine and real-time would be pure interruption tax, you review after, revert the few that were wrong. The interesting cell is irreversible but the agent's willing to wait, which is where async approval earns its keep: not batch, because you can't let it slide, but not desk-bound real-time either, the agent parks and you approve from your phone whenever you surface. So the honest answer to "real-time or batch" is "depends where the action sits on reversibility and blocking, and a good tool routes each action to the right one instead of forcing all decisions into one mode." Most tools pick one mode globally, which is why they feel wrong half the time.

For your domain specifically, health AI, I'd weight it harder toward real-time on a bigger slice than a typical web app, because reversibility there isn't only technical. A code change can be git-revertible while the thing it touched, a data transformation on protected health information, a model that influenced something, isn't cleanly undoable in the way that matters. "I can revert the commit" and "I can undo the consequence" diverge fast in health, so I'd treat more of your actions as effectively irreversible than the diff alone suggests. That's not a notification preference, it's a domain risk floor.

On your setup, the tail -f plus AppleScript-iMessage combo is the good kind of old-school, zero latency, no dependency, and it does the one thing that matters, push not poll. The ceiling is just that it's send-only, the iMessage tells you done-or-error but you can't reply "yes, proceed" and have the run act on it, so it's awareness, not control. Fine until the approval you need to give is the thing blocking the run, then send-only leaves you walking back to the terminal anyway.

But the line I actually want to underline is your discipline shift, because it's the most undervalued thing in this whole thread: a 10-minute run you half-watch beats an hour run you abandon. That's not a workaround, it's the real insight, and it inverts the usual framing. Everyone treats long autonomous runs as the goal and notifications as the patch for losing track of them. You've noticed that tighter scope reduces the need for the notification in the first place, because the blind window is short enough that nothing rots in it. Prevention over alerting. The corollary, which is maybe the actual punchline: better tooling shouldn't be used to enable longer unattended runs, it should let you keep your tight-scope discipline without paying the attention tax for it. The win isn't "now I can safely walk away for an hour," it's "I get my half-eye back for the ten minutes."

Question back, since you've clearly tuned this for a high-stakes domain: when you scope to 10-minute runs, what's your actual stopping criterion, time, or a natural checkpoint like "after it writes the transform but before it runs it on real data"? Because if it's the latter, you're not really time-boxing, you're placing approval gates at the irreversibility boundaries by hand, which is exactly the thing I think should be declarable up front, and I'm curious whether you'd trust a tool to hold those gates or whether in health you specifically want to place every one yourself.

@burak_emre_taser 

You said the killer-feature line yourself, so let me just confirm you're right and then sharpen why, because the reason it's the killer feature and not just a feature is the part worth internalizing.

Done and waiting are not two flavors of the same alert, they're opposite economics. "Done" is a finish, the work is safe, you find out late and you shrug, the cost of the delay is basically zero because nothing's deteriorating. "Waiting for approval" is a live stall, the agent is frozen and the clock is running, and crucially the cost grows with every minute you don't know. That's why the silent wait kills you specifically and the late finish merely annoys you, one is a static fact and the other is a bill that's still accruing. So a tool that only pings on done has solved the cheap half and left the expensive half exactly as broken as the second monitor leaves it.

Which is the thing about your second monitor: it doesn't actually help with the failure you named, and it's worth seeing why so you don't keep trusting it. A monitor shows you activity. But waiting-for-approval is the absence of activity, the terminal just sits there, and a quiet terminal looks identical whether the agent is thinking, blocked, or done. You can't see a silence, even when it's six inches away in your peripheral vision. The monitor is great for watching things move and useless for noticing things stop, and stopping is your whole problem. That's why you miss the waiting moments "constantly" despite having the screen right there, it's not inattention, it's that the signal you need isn't visible by looking.

The fix is the agent declaring "I'm blocked, I need input" as an event the instant it stops, so a silence gets converted into a push instead of waiting for you to surface from context-switching and discover it. That's the half the second monitor can't do and the half that's worth your money.

Go try it, and since you're the exact target user, solo, Claude Code all day, context-switching between building and everything else a solo founder also has to be, I'd genuinely want your read on one thing: when the push fires for "needs input," do you want to answer it from the phone and keep moving, or do you actually prefer being pulled back to the terminal because you want the full context before you say yes? Solo founders split hard on this, some want to clear the approval in two seconds and stay in their other work, some don't trust a yes they gave from a lock screen. Which one are you, because it changes what "solved cleanly" even means for you.

@prashant_patil14 

Your closing line is the whole thesis in one sentence: without a status layer you end up babysitting instead of delegating, and those are opposites, not points on a spectrum. Delegation means handing off and trusting you'll be told if something needs you. Babysitting means you can't hand off because you can't trust the silence, so you stay glued to it. The status layer is literally the thing that converts one into the other, it's what makes "walk away and trust" possible, and without it the agent's autonomy is fake, because the human is still pinned to the chair.

The three-state confusion you named is the sharpest part, and it's worth seeing why those three are genuinely hard to tell apart: working, waiting-for-approval, and stuck-in-a-loop can all present as the same thing from outside, an agent that isn't done and isn't obviously crashed. Working and waiting look identical because both are just an absence of completion. And a loop is the sneakiest, because it looks like the most productive state of all, it's busy, it's emitting, it's clearly doing something, it's just doing the same nothing over and over. So your status set isn't only useful, it's naming the exact distinctions that are invisible by default, which is why a real status layer has to come from the agent declaring its state, not from you squinting at the terminal trying to infer it.

The one I'd flag as needing a different detection method than the others: stuck-in-a-loop. Running, waiting, completed, failed are states the agent can announce. A loop is one the agent usually doesn't know it's in, that's what makes it a loop, so it won't declare it. You catch that one externally, by watching for activity that costs tokens and time without the state actually advancing, motion without progress. So your status layer is really two mechanisms wearing one interface: declared states for the things the agent knows, and a measured signal for the loop it doesn't.

That's exactly the layer I'm building, your five fields plus what-changed, so genuine question: of running / waiting / completed / failed, which transition do you most want pushed to you versus just visible in a view you can glance at? My read is waiting-for-input is the one that has to actively interrupt you because it's burning time silently, while completed and failed you might be fine seeing in a list when you look. But you've clearly thought about the state set, so I'm curious whether you'd want all of them pushed or just the one that's actually costing you while you're away.

@fbajo 

"I just keep an eye on everything" is the honest baseline, and the Claude extension push you mentioned is a real improvement on it, so worth being precise about what it does and doesn't close. The push on "work done" solves the finish case, you stop having to keep an eye out for completion, which is genuinely handy and a step up from pure watching. But notice it's still done-only, and done is the easy half. The case that actually leaks your time is the one no done-ping fires for: the agent stopping partway to ask you something. That's not a finish, so the completion notification stays silent, and you're back to keeping an eye on it to catch the pause.

So the extension didn't replace "keep an eye on everything," it shrank it, you can stop watching for done, but you still have to watch for blocked, because nothing tells you about that one. And blocked is the expensive state, because while done-late just means you find out late, blocked-silent means the agent is frozen and idle the whole time you didn't know. The done-ping covers the cheap case and leaves the costly one to your eyeballs.

The other ceiling, quietly: the extension pings you for the extension. The moment you've got Claude Code in a terminal or Cursor running alongside, that one push doesn't know about them, so "keep an eye on everything" creeps back in as soon as everything is more than one tool. Single-tool, single-state notification is a real help and also exactly where it stops scaling.

Question, since the done-push is already working for you: does the Claude extension ping you when it's waiting on your input mid-task, or only when it's fully finished? Because if it's finish-only, that blocked-but-not-done gap is the precise thing still costing you the eye-keeping, and I'm curious whether you've noticed the silent waits or whether your tasks just don't pause much.

@elias_motionfy 

You've named a failure that's genuinely different in kind from the rest of this thread, and it's worth being precise about why, because most of what people call "monitoring" is structurally blind to it. Done-vs-blocked, status, even the final diff, all of those describe end states. Intent drift isn't an end state, it's a path problem. The agent can drift and still arrive at a clean-looking diff, because the unrequested config refactor compiles, passes, and sits there looking intentional. The diff shows you what the codebase is now, not the sequence of decisions that got there, and drift is entirely a property of the sequence. So checking the final diff can't catch it by construction, not because the diff is incomplete, but because drift is invisible in any single snapshot. You can only see it in the derivative, the chain of choices over time, which is why you correctly say only reading the log catches it.

The opening observation is the sharper frame, though: agent UIs assume you're sitting and waiting, which contradicts the entire reason the agent exists. That's the original sin. The chat interface was designed for synchronous conversation, you say a thing, it says a thing, you're both present. Then we handed that same interface a job that's supposed to run while you're absent, and the absence is the whole point. So the interface is optimized for exactly the mode you're not in. Drift is what happens in the gap between "I'm present and would've said no to that refactor" and "I'm absent so the agent's small wrong turn compounds three commits deep before I'm back." The synchronous UI would've caught the drift instantly, you'd have seen it decide to touch the config and said "wait, why." The async reality is what lets it metastasize, and no tool built on the sit-and-watch assumption addresses that, because it assumes the catch happens live.

To your actual question, audit the chain or check the diff: the honest answer is most people check the diff, because auditing the chain is expensive, and that's precisely the gap drift exploits. Reading the full decision log is slower than just doing the task yourself, so nobody does it, so drift survives. But I don't think the answer is "audit every chain," because that's unaffordable and just rebuilds the babysitting. The answer is to make drift cheap to detect without reading the whole log, and the way you do that is by catching it at the decision point rather than in the post-mortem. The moment the agent goes from "task A" to "I'll refactor this config to fix a missing dependency," that's a scope expansion, and a scope expansion is detectable as an event, the agent is about to do a class of thing it wasn't asked to do. You don't need to read three commits of log if the agent is required to flag "I'm about to do something outside the original task scope" the instant it decides to. Drift caught at commit three needs a forensic log read. Drift caught at the decision needs one notification.

Which reframes drift as a special case of the approval problem, and a particularly important one: the dangerous approvals aren't only "this action is risky," they're "this action is outside what you asked for." Scope is its own risk axis, independent of how destructive the action is. A perfectly safe config edit that you never requested is a drift event even though the edit itself is harmless, because the problem isn't the edit's danger, it's that the agent silently expanded its mandate. So the signal that catches drift is the agent declaring intent before it acts, here's what I'm about to do and here's whether it's still inside the original scope, so you can veto the unrequested refactor before it becomes three commits of work you have to unwind. That's the thing a status notification can't do and an intent notification can, and it's exactly why "assumptions and intent" keep coming up in this thread as the high-value, hard-to-capture fields, they're the leading indicators, and drift is the failure that proves leading indicators matter more than end-state reporting.

Genuine question back, because your example is specific enough that you've clearly been burned by this concretely: when the agent drifts like that, is it usually drift you'd have approved if it had asked, the missing dependency genuinely needed fixing and the config refactor was reasonable, just unannounced, or is it drift you'd have stopped, where the agent's "fix" was the wrong call and you'd have wanted to solve the dependency differently? Because those need different responses. If it's mostly reasonable-but-unannounced, the fix is a lightweight "FYI I expanded scope" that you skim. If it's often the-wrong-call, the fix is a hard stop that blocks on your approval before it proceeds, and which one you actually hit determines whether drift detection should interrupt you or just narrate itself into the trail for later. I keep needing to know whether drift is usually the agent being helpfully resourceful or quietly wrong, because the answer changes whether you gate it or just log it.

@jahnavi_thota 

"AgentOps rather than an AI problem" is the right name, and the reframe underneath it is the important part: the constraint moved. When the models were the bottleneck, every problem looked like an AI problem, make it smarter, make it hallucinate less. The models got good enough that the bottleneck slid downstream to everything around them, and now the limiting factor isn't the agent's capability, it's your ability to observe, coordinate, and trust a fleet of them. That's not an AI problem, it's an operations problem, and it rhymes hard with the history you're implicitly invoking, we went from "can the server run the code" to DevOps and observability the moment we had more servers than one person could watch. Agents are hitting that exact inflection. The word AgentOps is doing real work, not just branding, because it correctly says the discipline you need is operational, not model-level.

The item in your list that's the tell you've actually run this at scale is "dependencies," because the other three, status, approvals, failures, are per-agent properties, and dependencies is the one that's between agents. Anyone who's run a single agent knows they need status and failures. You only discover you need dependency-awareness once agents start producing work that other agents or other steps consume, and then a silent failure or a stall in one isn't a local problem, it's a cascade, agent B is happily waiting on an output agent A died producing, and neither of them knows. Single-agent observability is a dashboard. Multi-agent observability is a dependency graph with state on it, and that's a categorically harder thing, because the failures that matter most aren't in any single agent, they're in the edges between them. The fact that Turgo surfaced dependencies as a first-class need means you hit the cascade problem, which is the real threshold between "I have notifications" and "I have AgentOps."

Where I'd add one thing to the observability framing, and it's the distinction that keeps coming up in this thread: observability in the classic sense is pull, a place you look, and the whole productivity-killer you named, context switching, isn't solved by having a place to look, it's solved by not having to look. A control layer that surfaces everything in one place is necessary but it inherits the dashboard trap, if staying informed requires me to go check the control layer, I've just consolidated four context-switches into one, not eliminated them. The version that actually kills the context-switching tax is push on the state-changes that need a human and silent on everything else, so the control layer is the thing you consult when you choose to, but it reaches out to you for approvals and cascade-failures rather than waiting to be observed. Observability that you have to observe is still a tax. Observability that observes for you and taps you is the unlock. AgentOps has to be push-first or it's just a nicer control room you're still chained to.

Genuine question, since Turgo's clearly operating at the multi-agent-with-dependencies altitude most people in this thread haven't reached: when a dependency breaks, agent A fails and agent B is downstream waiting on it, how are you handling the propagation, does B get notified/halted automatically when A fails, or does B stall silently until someone notices the whole chain stopped? Because that's the exact place I think AgentOps gets genuinely hard and diverges from single-agent notification, a failure has to travel the dependency graph to everyone affected, not just alert the one agent that broke, and I'm curious whether you're doing active propagation or whether it's still surfaced as independent per-agent status that a human has to mentally reassemble into "oh, B is stuck because A died." The reassembly-by-human is the part I'd most want to automate away, and it's the part I haven't seen anyone solve cleanly.

@frank_parsolano 

Right, and that “don’t care so long as they get a result” attitude is exactly what quietly costs people on long projects. It works until the result is subtly wrong and you have no idea which of the agent’s hundred decisions caused it, because you stopped tracking the thoughts halfway through.

That’s the gap I’m building Pushary for: keeping a lightweight trail of what the agent did and where it got stuck, so coming back is a ten-second scan instead of trying to reconstruct its thinking from scratch.

Curious, on your long projects, is it more that you lose track of what it did, or why it did it? Those are slightly different problems and I keep going back and forth on which one hurts people more.

@patrik_pyoria 

"Brute-forcing it by staying at my desk to watch them all" is the honest baseline, and the draining part isn't the watching, it's that it pins you in place. Running multiple agents is supposed to buy freedom, and instead it chains you to the chair as a human monitoring system. You automated the work and kept the supervision manual, so the net freedom is smaller than it should be.

And you've already spotted the fix in your second paragraph: the three states worth a ping are blocked, needs-approval, and stuck-on-error, and nothing else. That restraint is the whole thing. Ping on every step and it's noise you'll learn to ignore. Ping only on "waiting for user," and every alert means your attention is actually required, so you can walk away and trust the silence.

That's exactly what Pushary is, a centralized ping for those "waiting for user" states across Claude Code, Cursor, and Codex, so you stop babysitting terminals and the agents come to you instead. The one that's genuinely hard is the stuck-on-error case, because a clean error announces itself but an agent quietly frozen mid-task looks identical to one that's thinking, so real detection is the actual work under the simple-sounding feature.

Since you're living the brute-force version, genuine question: which state costs you most right now, the silent finish, the approval wait, or the error you didn't catch? That tells me which one to make loudest. And happy to have you try it, pushary.com, you're exactly who it's built for.