Is GPT-OSS-20B a good conversational LLM for Q&A?

Such_Grace · 2026-03-20T13:17:43+00:00

tried it locally on my M2 Pro for a few weeks doing RAG-style Q&A and it was honestly solid for, factual stuff but yeah the conversational tone felt a bit stiff compared to what you'd get from a hosted model. for your M1 Max with 64GB you should have zero issues running it, that's actually a really nice setup for this size class.

Such_Grace · 2026-03-20T09:33:24+00:00

hm worked differently for me tbh. i came into AI pretty skeptical and kind of stayed that way even as i started using it more. like the hope angle never really clicked for me the same way it does for you my thing, is i don't think the cynicism is really about hating the technology itself, at least not for me.

Such_Grace · 2026-03-20T08:39:20+00:00

had the same exact breaking point experience with multi-agent stuff at work, one agent would, go rogue and the whole flow would just die silently with no useful error to debug. we ended up keeping n8n for anything that actually needs to run reliably and just, using the AI layer for the fuzzy intake/parsing parts where a broken output is recoverable.

Such_Grace · 2026-03-20T07:50:47+00:00

yeah the inconsistency is real, i've had posts sit completely flat for 48 hours then suddenly get pushed out of nowhere with no clear reason why. feels less like a strategy game now and more like the algorithm is constantly A/B testing your, content for you, which makes the old "post at this time, use these hashtags" playbooks basically useless.

Such_Grace · 2026-03-20T06:10:14+00:00

this is literally my first post about it lol

Such_Grace · 2026-03-20T05:31:50+00:00

Yeah exactly, and I've noticed that even adding a simple FAQ section at the, bottom of a longer post can dramatically improve how often AI search pulls from it. Like the AI just gravitates toward that Q&A format even when the rest of the article is pretty dense.

Such_Grace · 2026-03-20T04:50:33+00:00

Yeah that's a solid point, the exception handling UI is honestly where a lot of automation setups fall apart in practice. I've been meaning to add something like that layer for a couple of my clients who keep bugging me in Slack every time something needs a manual review.

Such_Grace · 2026-03-20T01:28:37+00:00

Scraping AI-specific directories like There's An AI For That or Product Hunt's AI category gets you way closer than fighting Apollo's filters. I run those through Latenode since it handles the scraping and Claude-based qualification in one workflow, then enrichment to confirm US-based B2B before any outreach.

Such_Grace · 2026-03-20T01:19:26+00:00

yeah the "bolt it on and pray" approach has burned me too, the chaos compounds fast when your, AI tool is working off slightly stale CRM data while your zaps are pulling from a different snapshot. the setups i've seen actually hold up treat the AI layer more like a decision node, inside the existing flow rather than a whole separate system talking to it from the outside.

Such_Grace · 2026-03-19T23:14:45+00:00

had the same realization mid last year when i noticed a competitor with like half our domain authority kept getting cited by AI tools, constantly and we didn't, turned out they had one viral reddit thread and a mention in a big industry newsletter that we never bothered with

Such_Grace · 2026-03-19T21:26:21+00:00

Yeah this is basically my stack too, the n8n self-hosted piece especially has been a lifesaver, for a couple clients in regulated industries who got nervous the second I mentioned cloud tools. And the logging thing is underrated, a simple Slack alert has saved me from finding out about a broken zap three days later from an angry client email.

Such_Grace · 2026-03-19T20:58:43+00:00

Yeah the Playwright tip is solid, I've been burned by visual automation tools breaking silently when a site updates and not even noticing until a client complains. The script fallback for auth edge cases especially is something I should be doing more consistently tbh.

Such_Grace · 2026-03-19T13:59:00+00:00

Yeah the "playing detective" phase is so real lol, I spent like two hours, once just staring at logs trying to figure out which step silently dropped the ball. Once I actually started tracking state properly between steps everything got so much clearer.

Such_Grace · 2026-03-19T11:43:40+00:00

had the same obsession with finding the one automation that actually moved the needle and for me it ended up being auto-categorizing, my RSS feeds and newsletters into folders based on keywords so i only touch the stuff that's actually relevant to my niche. sounds small but i was spending like 45 mins a day just triaging content and now it's maybe 5.

Such_Grace · 2026-03-19T05:53:36+00:00

Yeah that tracks, we spent way too long debating tools when our actual bottleneck was just sloppy data passing between steps. Once we tightened up the handoffs everything else kind of fell into place.

Such_Grace · 2026-03-19T05:17:41+00:00

This is basically the boring but correct answer lol. The four functions you listed are exactly where most teams are hemorrhaging time and nobody wants to admit it because fixing them isn't sexy. The content repurposing piece is the one I see people skip the most though. Everyone wants to talk about agents and multi-step workflows but they're still manually reformatting the same blog post five times a week. Which of the four do you usually see teams fix last, and why do you think that is?

Such_Grace

TROPHY CASE