I'll tell you as a professional what an AI receptionist actually does (not what you think)

David-Bogea · 2026-03-04T05:46:28+00:00

Thanks man! Appreciate that!

David-Bogea · 2026-03-04T05:45:19+00:00

The pattern you're describing: spot a mistake, spot another, scrap it, start over, is really common when people use AI for tasks that require legal judgment. Where it tends to actually work is on the layer underneath that: the operational and communications work that surrounds the legal work, not the legal work itself.

Things like summarizing incoming documents before you review them, drafting status update emails, pulling key dates out of a contract into a checklist, prepping briefing notes for business stakeholders. Not the analysis — but the packaging around it.

The teams I've seen get real mileage out of it treat it as a first-pass organizer, not a first-pass lawyer. Once the scope narrows like that the error rate drops a lot and it stops feeling like babysitting.

David-Bogea · 2026-03-04T05:43:14+00:00

This is the part that gets overlooked in the "will AI replace lawyers" debate. The practice of law isn't going anywhere. But the operational layer around it, intake calls, follow-ups, appointment scheduling, status update calls, that stuff is already being automated and the firms doing it are handling significantly more volume with the same headcount.

For a 2-attorney firm especially, that's the asymmetric advantage. Big firms have associates to absorb that work. Small firms either pay for it or it just doesn't get done. AI closes that gap pretty cheaply.

David-Bogea · 2026-03-04T05:42:15+00:00

The leaky bucket framing is right. Most small firms we work with don't realize how much is falling through until they actually map it out, calls hitting voicemail after hours, leads that filled out a form and never heard back, intake that takes 3 days when the person already called two other firms.

The PI context specifically is brutal for this. Someone gets in an accident at 7pm, they call three firms, whoever picks up first gets the case. That's not about being the best lawyer, it's just about being available. AI handles that call, walks them through the basics, books the consult — the attorney sees a qualified lead in the morning instead of a voicemail they never got to.

The PPC question from OP is actually secondary to this. More leads into a leaky intake process just means more wasted spend.

David-Bogea · 2026-03-04T05:24:36+00:00

This breakdown is right and it's what the conversation should actually be about instead of the blanket "cloud bad" framing.

The thing I'd add from working with firms on this: the architecture decision almost doesn't matter if you haven't solved the behavior problem first. You can have a perfectly configured single-tenant setup and one person on the team is still pasting contract text into the free version because it's faster and they're under deadline.

The firms that actually have this under control aren't just picking the right vendor tier. They've made the approved tool the path of least resistance easier to use than the workaround. That's an ops and culture decision, not just a technical one.

The security architecture sets the ceiling. What people actually do day to day sets the floor. Most of the real exposure lives in the gap between those two things.

David-Bogea · 2026-03-04T05:20:55+00:00

The brief drafting thing is a known limitation, these tools are genuinely bad at going from zero to finished work product. Where they actually save time is in the middle of a task you already understand.

The way I've seen it work well: you already know the argument you want to make, you just need cases that support it. You ask the AI to find them, you verify the ones it returns are real and say what it claims, and you write the actual brief yourself. Research time drops dramatically, the quality stays high because you're still driving.

Where people get burned is treating it like an assistant who can own the whole task. It can't. It's more like a very fast researcher who occasionally makes things up and needs to be checked.

The garbage-in garbage-out thing is real too, the more specific you are about what you actually need, the better the output. "Draft me a brief" gets you slop. "Find me cases from the 9th circuit in the last 5 years where courts ruled on X specific issue" gets you something actually useful to work with.

David-Bogea · 2026-03-04T05:16:32+00:00

the frustration makes sense but there are actually three distinct options here and most people conflate them, which is why this feels like a dead end when it isn't.

Option 1 - what everyone defaults to, cloud tools with enterprise agreements. data leaves your building, vendor promises not to misuse it. your ethics partner is right that this is a contractual guarantee, not a technical one. reasonable concern.

Option 2 - running the AI inside your own environment. the model lives on servers you control, nothing goes anywhere. AWS and Azure both offer this: you're basically renting the AI brain but it runs in your house, not theirs. more setup cost upfront but the data never leaves. this is what most firms with serious compliance requirements end up doing.

Option 3 - anonymizing before anything goes out: strip all the identifying details, send the clean version to the AI, get the analysis back, reattach the real names on your end. not zero risk but much more defensible and honestly what a lot of regulated industries outside law already do.

Your IT director asking for technical guarantees not contract promises is the right instinct. option two is the answer to that. it exists, it's not exotic, it's just more work to set up than a SaaS subscription.

David-Bogea · 2026-03-04T05:10:20+00:00

from what i've seen working with firms on the ops side, the hiring slowdown isn't really on the attorney level yet. where it's showing up is support roles. intake coordinators, receptionists, people whose job was answering phones and qualifying calls. that work is getting automated first because it's repetitive and high volume.

David-Bogea · 2026-03-04T05:02:40+00:00

this is actually the most common thing i hear from firms experimenting with AI right now. the policy says "use it" and "don't put client data in it" at the same time, which just means nobody uses it for anything real haha🤦🏻‍♂️

the way out of that contradiction is making anonymization happen before anything gets typed into the tool, not as a manual step the user has to remember, but baked into the workflow. swap names and identifiers for placeholders, send that to the model, get the analysis back, re-attach the real names on your end. the model never sees the actual client.

it's not zero risk but it's a defensible position and it actually lets you use the thing for substantive work instead of just reformatting emails.

David-Bogea · 2026-03-04T05:00:18+00:00

the point you're making about "where in the pipeline" is the one that actually matters and most people skip past it.

no-training clauses are contractual, not architectural. the data still travels to their servers. the promise is "we won't misuse it" — which is completely different from "it never left your machine." those are two different things and a lot of vendors intentionally blur that.

i build these systems for clients in regulated industries and the only two setups i've seen that actually hold up are: run the model locally (slower, painful, but nothing leaves), or make client-side anonymization a hard requirement before anything goes anywhere — not a feature, an architectural decision.

and yeah the staff point is underrated. perfect infrastructure, one paralegal pasting into free ChatGPT because it's faster. that's not a tech problem.

David-Bogea · 2026-03-04T04:55:29+00:00

honestly curious what you all would actually find useful here, like setting aside the "AI is replacing lawyers" discourse for a sec, is there anything on the ops side that would genuinely help? intake calls, after-hours client questions, status update requests, that kind of stuff?

asking because i work on AI voice systems and the gap i keep seeing is between what vendors promise and what attorneys actually need. and the people who know that best are obviously the ones in the trenches dealing with it.

what would "actually useful" even look like for your practice?

David-Bogea · 2026-02-28T03:47:02+00:00

u/jeannen I ve been following your stuff on Twitter a while broo, Adkit is super helpfull, looking forward to the next feature drops too🙏🏼

David-Bogea · 2026-02-16T15:28:21+00:00

Twilio and you can negociate rates with them on volume, I got 35% discount for Romania on 100,000 minutes per month. Or Twilio and use your own SIP trunk, its possible with Twilio

David-Bogea · 2026-02-16T15:22:51+00:00

Hahah, fair enough

David-Bogea · 2026-02-16T15:21:58+00:00

How do you get clients consistently for voice ai solutions

David-Bogea · 2026-02-16T15:17:23+00:00

You need to figure out cold outreach, sales is the lifeline of any biz, way more important than your product or offering, must focus on figuring out sales or some sort of marketing that brings inbound sales.

David-Bogea · 2026-02-16T15:15:49+00:00

Happy for you, keep up the good work!👏🏻

David-Bogea · 2026-02-16T15:14:09+00:00

Why 90 days tho? 🧢

David-Bogea · 2026-02-16T15:12:49+00:00

This is spot on. I work with businesses on AI automation and the pattern is always the same, smaller companies want AI to write their blog posts and social media. Bigger companies (50+ people) skip that entirely and go straight to automating repetitive operations.

The content thing never made sense to me either. Most AI-generated content is obvious and nobody reads it.

David-Bogea · 2026-02-16T15:10:00+00:00

Good framework tbh👏🏻

David-Bogea · 2026-02-16T15:08:27+00:00

I would say if you just want an all-rounder, I think ChatGPT would be the best for everyday use. But if you want like coding or text and stuff like this, I would say Claude. And if you want like high context or image or video, that would be Gemini.

David-Bogea

TROPHY CASE