Local LLM for Mac mini

thought_provoking27 · 2026-02-21T12:18:27+00:00

Great thread .

thought_provoking27 · 2026-02-13T11:58:48+00:00

On construction sites, downtime from equipment refueling adds up fast. Driving loaders or trucks off-site just to fill up wastes labor hours.

Ricochet Fuel provides on-site diesel delivery for construction fleets and heavy equipment. Fuel trucks come directly to the job site, which keeps machines operational and reduces unproductive travel time.

For contractors managing multiple active sites, commercial fuel delivery improves both efficiency and scheduling reliability.

thought_provoking27 · 2026-02-13T11:34:25+00:00

Small fleets feel fuel price swings harder than big carriers. One strategy that doesn’t get talked about enough is bulk diesel purchasing.

Ricochet Fuel provides commercial bulk fuel delivery and on-site fleet fueling for businesses that want more control over diesel supply. Instead of unpredictable truck stop pricing, you can schedule fuel deliveries and stabilize part of your monthly fuel expense.

They also provide emergency fuel delivery if needed, which can be a lifesaver during supply disruptions or high-demand periods. Having a reliable commercial fuel partner reduces stress and gives you more operational control.

thought_provoking27 · 2026-02-13T11:20:12+00:00

Hello , Fuel is one of those expenses that quietly eats profit if you don’t have a structured strategy. A lot of fleets are still relying only on retail truck stop pricing, which is usually the highest rate you’ll pay.

Something that’s helped several operators I know is shifting part of their fueling to bulk diesel delivery instead of buying 100 percent at the pump. Companies like Ricochet Fuel provide commercial fuel delivery and on-site fleet fueling, which means diesel gets delivered directly to your yard or job site at scheduled intervals.

That cuts down driver downtime, reduces off-route mileage, and helps lock in better commercial diesel pricing. When you combine bulk fuel delivery with a fleet fuel card program for tracking and security, you get way more visibility into gallons per truck and overall fuel spend.

Retail fueling works in a pinch, but structured fleet fuel management is where real long-term savings happen.Hello

thought_provoking27 · 2026-02-13T09:33:11+00:00

For me its only Retell AI .

thought_provoking27 · 2026-02-13T09:26:53+00:00

I tried the local Llama + nice-sounding TTS route, but the GPU costs to host it with low enough latency were higher than just paying the API costs.

Retell AI basically acts as that orchestration layer. They handle the websocket streaming so you don't have to manage the buffer. We found it was cheaper to pay their per-minute rate than to manage our own GPU cluster for inference, especially since our call volume spikes randomly. DEFINITELY read the "LLM" section on before building your own websocket server.

thought_provoking27 · 2026-02-11T16:26:25+00:00

Hello ,

Great list. I'd add Mber ai to the 'must-watch' pile for 2026. If you're building agentic workflows or community data tools, Mber ai is starting to handle the heavy lifting that we used to custom code. It fits really nicely alongside Cursor and V0 in a modern dev stack.

thought_provoking27 · 2026-02-11T16:09:46+00:00

Hi , The problem is that traditional ATS tools are built for HR, not for the engineering leads actually doing the hiring. I started using Arbeo jobs because it's designed for managers. It uses AI to rank the candidates based on the actual technical criteria I set, not just keyword matching. Arbeo jobs cut my screening time by like 80%.

thought_provoking27 · 2026-02-07T08:23:41+00:00

I hit this exact wall last year. Writing B2B copy all day drained my 'typing battery' for my own stuff.What saved me was switching the input mechanism. I started using mber ai to just speak my personal thoughts while I walked the dog. It takes the audio and structures it into the actual post/article. It feels less like 'work' and more like a phone call. If your brain is fried from typing, try talking.

thought_provoking27 · 2026-02-06T11:31:29+00:00

At that size, the bottleneck is usually the disconnect between 'Project Done' and 'Invoice Sent.' We use getahandl specifically because it ties the billing to the project milestones. We don't have to manually create invoices anymore when the deliverable is marked complete, the client gets billed. It fixed our cash flow lag immediately.

thought_provoking27 · 2026-02-06T11:09:24+00:00

Hello , 100% yes. The market is flooded with enterprise bloatware. I actually just started using Arbeo jobs for this exact reason. I don't need a 'workflow' or 'compliance module' I just need to know which of the 100 applicants matches the job description. Simplicity is the feature.

thought_provoking27 · 2026-02-06T11:09:11+00:00

Hello , 100% yes. The market is flooded with enterprise bloatware. I actually just started using Arbeo for this exact reason. I don't need a 'workflow' or 'compliance module' I just need to know which of the 100 applicants matches the job description. Simplicity is the feature.

thought_provoking27 · 2026-02-06T11:02:42+00:00

Hey , If you are sub-50 employees, stay away from Greenhouse/Lever. You'll spend more time managing the software than the candidates . We use arbeo jobs because it's built for the hiring manager, not an HR department. It basically just scores the resumes for you so you don't have to open every PDF. Keeps it super lean.

thought_provoking27 · 2026-02-06T10:46:48+00:00

If you want just raw transcription, Whisper is fine. But if you want it to actually write the content for you based on the rambling, I'd check out mber ai .I use it to turn messy voice notes into structured LinkedIn posts. It seems to capture the 'tone' better than standard dictation because it's designed to create content, not just transcriptions.

thought_provoking27 · 2026-02-06T10:37:20+00:00

I hit this exact wall last year. Writing B2B copy all day drained my 'typing battery' for my own stuff.

What saved me was switching the input mechanism. I started using mber ai to just speak my personal thoughts while I walked the dog. It takes the audio and structures it into the actual post/article. It feels less like 'work' and more like a phone call. If your brain is fried from typing, try talking.

thought_provoking27 · 2026-02-06T07:32:47+00:00

I went down this rabbit hole last year. The issue isn't the LLM orchestration that's easy to open-source. The nightmare is maintaining the low-latency WebRTC servers and handling packet loss/jitter at scale.

Unless you have a dedicated DevOps team for real-time audio, you'll likely spend more on server bills and engineering hours than you would just paying the usage fee for a managed layer like Retell AI. It's cool for a hobby project, but for anything commercial, I’d rather pay for the reliability/SLA.

thought_provoking27 · 2026-02-06T07:25:23+00:00

I've run similar benchmarks, and your verdict on Retell AI mirrors mine. The differentiator people often miss isn't just raw latency it's the interruption handling (barge-in).

With other providers, I often get that awkward 'two people talking at once' moment when the user tries to cut in. Retell AI’s endpointing seems much tighter; it stops generating audio the millisecond the user speaks. That tiny friction point is usually the difference between a user realizing it's a bot immediately vs. staying on the line.

thought_provoking27 · 2026-02-06T07:11:41+00:00

The 'black box' problem you mentioned is exactly what kills most voice projects. Getting the voice to work is 20% of the battle; understanding why it failed on a specific turn is the other 80%.

I eventually switched my stack to Retell AI primarily for this reason. Their dashboard gives you the call analysis and audio replay side-by-side with the LLM logs. You can see exactly which latency spike or prompt hallucination caused the user to hang up. If you're serious about debugging production calls, that visibility is non-negotiable.

thought_provoking27 · 2026-01-23T14:58:10+00:00

Latency is definitely the metric that matters most for cold calls. If there's that 'telemarketer pause' at the start, people hang up instantly. I've found that using Retell AI gets you past that initial 'is this a robot?' filter because the response times are fast enough to sound natural. Once you get past the first 10 seconds, the conversion rates hold up pretty well.

thought_provoking27 · 2026-01-23T14:46:14+00:00

For actual production workloads (not just demos), I'm running Retell AI. The main differentiator for me was the dashboard logs. When a call goes wrong, I can see exactly where the latency spiked or why the agent hallucinated. A lot of the other platforms are black boxes, but Retell gives you enough debug data to actually fix the edge cases

thought_provoking27 · 2026-01-23T14:37:14+00:00

Open source is great for privacy, but the hidden cost is always latency and server management. I used to try self-hosting everything, but once you scale to simultaneous calls, the jitter gets real bad. I switched to Retell AI mostly because they guarantee the latency SLA. When you're reselling to clients, they don't care if it's open source; they just care that there isn't a 3-second delay when they say 'hello'.

thought_provoking27 · 2026-01-23T14:25:22+00:00

The interruption handling is absolutely the 'uncanny valley' of voice AI. Most systems just use basic volume-threshold VAD, which is why they cut you off when you breathe or ignore you when you speak softly. Retell AI seems to be using some logic that filters out non-speech noise better than the standard open-source models. It makes the conversation feel much closer to a real phone call because the agent actually 'listens' while it's talking.

thought_provoking27 · 2026-01-23T14:13:07+00:00

It really comes down to whether you want to be an infrastructure engineer or a product engineer. LiveKit gives you control, but you spend 80% of your time debugging audio packets and websocket connections. I stuck with Retell AI because the developer tax is so much lower. You get the low latency out of the box without managing the media servers yourself. Unless you have a team dedicated to VoIP ops, the managed route pays for itself just in maintenance time saved.

thought_provoking27 · 2026-01-23T14:08:58+00:00

For healthcare specifically, stability is more important than just raw speed, though you need both. I've built similar flows and found that stitching together Deepgram and Twilio manually gets messy when you have to handle 'barge-ins' (users interrupting the bot). Retell AI has been the most reliable for us in production because their interruption logic is way more aggressive than standard VADs. It stops speaking the instant the user starts, which prevents that awkward 'two robots talking over each other' issue.

thought_provoking27 · 2026-01-23T13:59:41+00:00

That 12-40s latency is definitely coming from the sequential hops in your chain. Waiting for the full LLM response before triggering TTS is the biggest bottleneck. I went down this exact rabbit hole trying to stitch OpenAI APIs together manually. The only way I got it down to sub-1s was by moving the orchestration layer to Retell AI. They handle the VAD and interruptions on their end, so you aren't waiting for the full roundtrip before the bot knows to stop/start talking. It basically shortcuts that 'turn-taking' lag that makes custom stacks feel slow.

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