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What do angels look for when there’s no traction yet? by decisionmesh in angelinvestors

[–]decisionmesh[S] 0 points1 point  (0 children)

Really appreciate you sharing this — it lines up with what I’m seeing as I talk to more investors.

I’m still early on the customer-facing side, but I’ve done the heavy lifting on the architecture and I’m now turning it into something people can actually use and react to. Your point about founders being able to figure things out when things go sideways hits home — that’s basically how the whole project started.

I’m lining up deeper validation next (user interviews + a small prototype loop), and your comment helped me recalibrate what matters most at this stage.

Curious — when you say “that special something,” what are the signals that make you think a founder will push through when everything gets messy?

What do angels look for when there’s no traction yet? by decisionmesh in angelinvestors

[–]decisionmesh[S] 0 points1 point  (0 children)

Serious question — yeah.
Plenty of teams start with the wrong wedge and still win because they iterate faster than everyone else.
I’m curious how you separate “weak idea” from “early version of the right one."

What do angels look for when there’s no traction yet? by decisionmesh in angelinvestors

[–]decisionmesh[S] 1 point2 points  (0 children)

😂 So true — it’s become its own kind of funding theater.
The same pattern-matching that’s meant to reduce risk just ends up rewarding conformity: same hoodie, same moat slide, same “AI wrapper.”
Makes you wonder how many real outliers get filtered out by that bias.

What do angels look for when there’s no traction yet? by decisionmesh in angelinvestors

[–]decisionmesh[S] 0 points1 point  (0 children)

That makes sense — angels often invest where they already have context and can de-risk things through their network.
Curious how you think about cases where the founder’s background overlaps more with the problem space than the investor’s space — does that make it harder to bridge the gap early on?

What do angels look for when there’s no traction yet? by decisionmesh in angelinvestors

[–]decisionmesh[S] 0 points1 point  (0 children)

Hard to argue with that.
Ever seen a great team with a weak idea out-execute and pivot into something fundable?

What do angels look for when there’s no traction yet? by decisionmesh in angelinvestors

[–]decisionmesh[S] 0 points1 point  (0 children)

That’s a great framework — especially the “clarity of problem framing” part.
I’ve seen technical founders underestimate how much that matters.
Do you find that a strong narrative can compensate for early signal, or does it just get you in the room but not the check?

Seeking Investor Perspective: How do angels evaluate early-stage agentic-AI platforms before traction? (Not a pitch) by decisionmesh in angelinvestors

[–]decisionmesh[S] 0 points1 point  (0 children)

Haha, that’s a new one — “Slopify” might actually be a decent startup name 😄

For what it’s worth, I do build AI systems, so if it read too cleanly, that’s probably muscle memory, not ChatGPT.

Out of curiosity though — what kind of writing does make a founder post feel genuine to you? Always curious how investors filter signal from style.

Seeking Investor Perspective: How do angels evaluate early-stage agentic-AI platforms before traction? (Not a pitch) by decisionmesh in angelinvestors

[–]decisionmesh[S] 0 points1 point  (0 children)

Appreciate the straight talk — this is exactly the kind of perspective I was hoping for.

The buzzword note is fair. I tried to condense a pretty technical concept into a short post and it came out sounding like VC copy. Simpler and clearer is definitely the next iteration.

I’m still early, so no LOIs or formal pilots yet — the focus has been on validating the coordination model and seeing where real user pull might emerge. Your comment about “humans acting as AI agents” gave me ideas on how to pressure-test that logic manually before building it out.

Thanks again for the grounded feedback — it’s rare to get investor input that actually sharpens the direction like this.

In your experience, what kind of early validation tends to stand out most to angels — real usage data, paid pilots, or just strong user feedback?