I had a look at getting same agent up in WhatsApp but it seems to need FB business acc to even start process, to get FB business you need an FB personal etc. ... looked like too much effort

Because MCPs solve the exact issue the whole post is about

It's easy to forget the product Anthropic are selling here, and throttling, is based on data they mostly pay little or no content fee for

6 months ago, "what temp is pork safe at?" was a few clicks, long SEO optimised blog post answers and usually all in F not C ... despite Google knowing location ... I used it as an example at the time of 'how hard can this be?'

First sentance of Google AI response right now: "Pork is safe to eat when cooked to an internal temperature of 145°F (63°C)"

How is it not the responsibility of senior management at a major retailer to ensure an exploit at a vendor can't take the whole house of cards down?

Many other major enterprise clients out there are all over vendor security/compliance ... auditing and reauditing vendors to minimise chance of this happening or worst-case, if does happen, containing it and recoverying quickly

But this particular project is not like a standard site and the CSS is in small fragments across 100s files and uses constants for some things like color values in places too

In that Loopple example you can see the conversion uses the Tailwind arbitrary value notation, the -[], so background-color:#afa8af gets converted to bg-[#afa8af], but I wanted nearest pure tailwind class bg-zinc-400, the agent seems to work out color distance fine so does all that in one-shot too

That was gemini-cli, I could see some mistakes on trial run so created a GEMINI.md with system prompt and project description (about 50 lines) which clarified some tricky source layout situations

Second run it was fine, ran for about an hour or so -- I had attempted to do it manually a while back but it started to look like it would take a week or two

Much of the criticism of AI on HN feels driven by devs who have not fully ingested what is going with MCP, tools etc. right now as not looked deeper than making API calls to an LLM

https://elevenlabs.io/

https://layercode.com/ (https://x.com/uselayercode has demos)

Have you used the live mode on the Gemini App (or stream on AI Studio)?

What blocked me initially was watching NDA'd demos a year or two back from a couple of big software vendors on how Agents were going to transform enterprise ... what they were showing was a complete non-starter to anyone who had worked in a corporate because of security, compliance, HR, silos etc. so I dismissed it

This MCP stuff solves that, it gives you (the enterprise) control in your own walled garden, whilst getting the gains from LLMs, voice etc. ... the sum of the parts is massive

It more likely wraps existing apps than integrates directly with them, the legacy systems becoming data or function providers (I know you've heard that before ... but so far this feels different when you work with it)

I had similar skepticism initially, but I would recommend you dip toe in water on it before making judgement

The conversational/voice AI tech now dropping + the current LLMs + MCP/tools/functions to mix in vendor APIs and private data/services etc. really feels like a new frontier

It's not 100% but it's close enough for a lot of usecases now and going to change a lot of ways we build apps going forward

I'm not seeing anything like the same level of heads or stack complexity in this wave (Vercel, Firebase etc.), and the vendors involved get cheaper every day ... along with increasing ability to run models locally with no metered costs at all

You could have two different packages in a build doing similar things -- one uses less memory but is slower to compute than the other -- so used selectively by scenario from previous experience in production

If someone unfamiliar with the build makes a change and the assistant swaps the package used in the change -- which goes unnoticed as the package itself is already visible and the naming is only slightly different, it's easy to see how surprises can happen

(I've seen o3 do this every time the prompt was re-run in this situation)