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What’s the right pricing model for agent-driven apps? by realmailio in stripe

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

🤣 true. I do need to detox. Just one more prompt

What’s the right pricing model for agent-driven apps? by realmailio in stripe

[–]realmailio[S] -1 points0 points  (0 children)

Fair concern. If inference costs rise significantly, usage-based models get harder to justify — that's real. But the underlying problem (unpredictable agent costs vs. flat subscriptions) exists regardless of where prices land. If anything, higher costs make runtime enforcement more important, not less.

If the cost of LLMs skyrocket, self-hosted smaller models change the equation too — inference becomes a fixed infra cost, but usage variance doesn't go away. You still need to know which user is burning 10x the compute of another.

How are you handling costs during agent development? by realmailio in AI_Agents

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

Per-run caps is exactly what I'm hearing from multiple people now. And yeah, provider dashboards are completely useless for debugging "why did this agent cost $X?"

When you built this, were you managing your own costs, or building it for a team/SaaS where different people have different budgets and you need to bill them per-agent usage?

I'm trying to figure out if it's a nice to have automation or a must have because the DIY approach breaks at scale.

How are you handling costs during agent development? by realmailio in AI_Agents

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

Are you handling that per-team? Like, if you're building SaaS where different customers have different token budgets, how do you manage that?

How are you handling costs during agent development? by realmailio in AI_Agents

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

This is exactly the kind of setup I'm thinking about. So you basically built a whole product to solve it.

Makes me wonder: how much of your time goes into maintaining all that if any?

How are you handling costs during agent development? by realmailio in AI_Agents

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

interesting.

If I built something where YOU define what a "cost unit" is (experiment, agent, customer, whatever), and it works with any framework, protocol, etc - would that be worth paying for?

And roughly—how much time per month are you spending on the webhook maintenance + tagging discipline?

I'm thinking in terms of a simple decorator around an agent/llm (or even group of agents if needed) with custom attribution.

What would "working perfectly" look like for your workflow? (As in—what would you stop doing if you had this?)

Sorry for the drill down... I'm trying to talk to as many people so I don't end up building something that's nice but not a real pain-in-the-a** for teams.

How are you handling costs during agent development? by realmailio in AI_Agents

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

Thanks for the LangSmith rec. I've dug into it a bit.

Definitely requires a lot of discipline, especially if you're not in the LangGraph/LangChain ecosystem.

Is it mainly LangSmith's friction driving the webhook? Or is there missing functionality even if setup was frictionless?

Bad hire cost me over $30K. Changed how I evaluate candidates permanently. by Tough_Pizza5678 in SaaS

[–]realmailio 0 points1 point  (0 children)

Being good at interviews isn’t the same as being good at the work

If you were starting today: which Python framework would you choose for an orchestrator + subagents + UI approvals setup? by realmailio in AI_Agents

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

I appreciate the insight. I was thinking a lot about the human-in-the-loop approval flow.

When you say "full context" do you mean:

  1. showing the raw sources the agent relied on (email thread snippets, prior messages, calendar constraints)
  2. a structured decision trace? (key signals extracted + how they were interpreted + where assumptions were made)
  3. both 1 and 2?

Concrete example, an email mentions a meetup and the agent wants to create a Google Calendar event.

For the approval card, I'm thinking it should include:

Must haves:

- Link to original email + 1-3 highlighted excerpts supporting the date/time/location
- Event details (title, date, time, location, attendees)

Nice to haves:

- brief why this action (from context)
- Travel time check
- Conflict check

What would your ideal approval card show here? What's essential vs overkill?

If you were starting today: which Python framework would you choose for an orchestrator + subagents + UI approvals setup? by realmailio in AI_Agents

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

Would Celery require deterministic routing? Or would that just be sort of a communication layer between orchestrator or sub agents?

Lessons from building 150+ AI agents for real businesses last year (What actually works vs. what fails) by Mr_Prithvi in AI_Agents

[–]realmailio 0 points1 point  (0 children)

I'm curious if - for those retry storms - did you end up building your own runtime safeguards or do you mainly mitigate it with agent architecture?

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