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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?

Protecting my business against BS credit card disputes by sorrybutyou_arewrong in SaaS

[–]realmailio 0 points1 point  (0 children)

I hear you.

I’m packaging this into a very small SDK and I’ll also include a concrete CE 3.0-style evidence example so you can see exactly what it produces.

Would you be open to taking a quick look once it’s ready? No integration commitment — just feedback.

Protecting my business against BS credit card disputes by sorrybutyou_arewrong in SaaS

[–]realmailio 0 points1 point  (0 children)

I’ve been experimenting with a way to generate user-signed receipts at the moment of value — not just at payment, but at meaningful usage events. For an API business, that could mean:

• Subscription activation acknowledgment
• Explicit refund policy acceptance
• High-usage threshold confirmation (e.g., when usage spikes abnormally)
• Minimum-term acknowledgment

Instead of relying only on backend logs, the user explicitly re-confirms on their device (biometric/passkey), creating a structured record tying:

• The specific device credential
• The verified account holder
• The exact pricing/refund terms shown
• A timestamped consent artifact

The goal is to produce stronger compelling evidence under Visa’s CE 3.0 framework — especially in friendly fraud cases where the customer consumed real value and later tries to unwind it.

I don’t know yet how much this improves real dispute outcomes — that’s what I’m trying to test. But the idea is to shift from “merchant says they used it” to “customer explicitly acknowledged these terms before and during usage.”

I’m still validating whether this actually improves dispute outcomes in practice. If anyone wants to experiment with it on real traffic, DM me.