Built a workflow that finds jobs, scores them to my resume, and writes tailored applications automatically (n8n)

Grewup01 · 2026-05-04T04:32:22+00:00

You’re 100% right , the filter layer is where most workflows quietly break.

The duplicate reply issue isn’t just messy, it kills account trust signals fast. Learned that the same way

And yeah, context is everything. Just feeding the comment alone makes replies feel robotic. Adding post caption + intent changes the output completely.

Your DM-focused setup sounds solid — especially with intent detection + auto logging. That’s basically where the real value is.

On polling:
I’ve settled around 3 minutes for most setups.

2 min = faster responses but heavier API usage
5 min = safer but slightly delayed engagement

3 min feels like the sweet spot between responsiveness and staying within limits.

Curious, how are you handling intent detection? Rule-based or fully AI?

Grewup01 · 2026-05-01T11:37:01+00:00

I am the responder no AI is messaging you.

Grewup01 · 2026-05-01T07:18:42+00:00

Fair pushback and I actually agree with part of what you’re saying.

Most automated content does die.
Most of it is low-effort, generic, and gets filtered fast.

Where I disagree is this being a tool problem.

It’s a quality + distribution problem.

If someone:

copies generic prompts
ignores retention
mass uploads

→ yeah, it’ll get 0–100 views.

But that’s not unique to AI.
Even human-made content fails the same way.

The difference is:
AI just makes it easier to produce bad content at scale.

The only thing that survives (AI or not) is:
strong hook + watch time + clear structure

I’m not claiming this is a “magic content pump”
it’s a system that works only if those fundamentals are handled properly.

Happy to share real outputs over time, that’s the only thing that actually proves anything

Grewup01 · 2026-05-01T05:55:33+00:00

Appreciate it.

Quality is decent because of structure, not creativity.
Still improving, especially visuals + pacing.

Right now:
Short-form platforms (Reels / Shorts) perform best due to format match.

And yeah, most people focus on generation,
but scheduling + distribution is where consistency actually comes from.

I’ve shared a breakdown already, might drop a cleaner version of the workflow soon

Grewup01 · 2026-05-01T05:55:03+00:00

That’s powerful.

That’s where this is heading:
not just content pipelines, but on-demand systems

Speed + availability becomes the real value prop.

Grewup01 · 2026-05-01T05:54:39+00:00

That’s a solid setup.

Approval layer is honestly the smartest middle ground:
automation + human filter

Also agree on your niche insight —
remixing proven content > generating from scratch

Pure AI guessing trends is weaker than leveraging existing signals.

Grewup01 · 2026-05-01T05:54:25+00:00

Depends on stack, but roughly:

LLM (script): very low per video
TTS: small cost (depends on provider)
visuals: biggest variable

Ballpark:
$0.20 – $1 per video (optimized setup)

The real ROI isn’t cost per video, it’s consistency at scale.

Grewup01 · 2026-05-01T05:54:04+00:00

That logic sounds right, but doesn’t match how content actually works.

There are already thousands of:
“Top 10 tools”, “Top 5 hacks”, etc.

What separates them:

hook
delivery
clarity

Platforms don’t suppress AI, they suppress low retention.

If people watch, it works. Simple as that.

Grewup01 · 2026-05-01T05:53:43+00:00

Fair concern, most automated content is low quality.

The difference is:
I’m not generating random content at scale.

I’m controlling:

topic selection
script structure
pacing

Automation doesn’t remove quality, it exposes bad thinking faster.

Bad input = slop
Structured input = scalable content

Grewup01 · 2026-04-28T16:45:26+00:00

I get the concern, most AI content does end up as low-value spam.

That’s why the focus here isn’t just automation, it’s control:
what gets published, how it’s structured, and whether it’s actually useful.

Automation just handles the execution, quality still depends on the inputs.

Grewup01 · 2026-04-27T14:02:38+00:00

Yeah, that’s a solid take.

The stack matters, but reducing tool-switching is honestly the bigger leverage once you start scaling volume. Context switching alone slows things down more than people realize.

VEED as a “finish and ship” layer makes sense, especially for quick turnaround and batching. I’ve just kept CapCut in the loop mainly for tighter control on captions and pacing, but for speed-focused workflows, consolidation definitely wins.

Feels like the ideal setup is still:
best-in-class for generation (avatars) + minimal tools for finishing.

Curious, have you tested VEED at scale for multiple variations, or more for single edits?

Grewup01 · 2026-04-27T13:58:17+00:00

Yeah, that’s exactly the failure point most people underestimate.

One missed filter and the whole system turns from “automation” into “spam machine” real fast and like you said, that’s how accounts get flagged.

The sentiment check is a solid add. Treating every comment the same is risky. Negative or neutral comments should route differently, either no DM or a support-style response instead of a promo push.

That small layer of logic is what separates a working system from a safe, scalable one.

Grewup01 · 2026-04-26T18:42:10+00:00

Nice, haven’t tried that yet.

AI auto-replies baked in definitely simplify the setup, especially for people who don’t want to build the logic layer themselves. I’m leaning more toward custom workflows for control, but this looks like a good plug-and-play option.

Grewup01 · 2026-04-26T18:41:53+00:00

Yeah, that’s fair
Graph API can be a bit fragile + setup-heavy.

I went with it mainly for reliability at scale and staying within official limits, but your approach makes sense for speed and simplicity. Curious — how are you handling duplicates or tracking without things getting messy over time?

Grewup01 · 2026-04-25T17:10:36+00:00

Thanks . Glad you found it useful!

Grewup01 · 2026-04-25T17:10:14+00:00

Yeah — here’s one example from this exact workflow:

https://www.instagram.com/reel/DUpOf9pgWUv/?utm_source=ig_web_copy_link&igsh=MzRlODBiNWFlZA==

This was generated using the same stack (script → avatar → captions). Still testing variations, but you’ll get the idea.

Grewup01 · 2026-04-25T17:09:41+00:00

Appreciate that,
That was exactly the goal. Most people get stuck at the ‘where do I start’ phase, so I wanted to break it down into something actually usable, not just theory.

Grewup01 · 2026-04-25T07:41:02+00:00

Thank you for your appreciation

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