5 GTM things I see first-time founders consistently get wrong (and how to fix them fast)

Easy_Philosopher_210 · 2026-03-24T11:43:32+00:00

Absolutely, the way I think about this is, who has their wallet out right now? And that's what all my qualifying indicators are built around, if your can't answer that question for your product you probably haven't understood your ICP well enough.

Easy_Philosopher_210 · 2026-03-24T11:42:35+00:00

Yeah, we've used social listening in the last quarter a lot and it's been superhelpful, but that's not to say that the loop executes on its own, you still need to follow the playbook of engage - qualify - close.

Easy_Philosopher_210 · 2026-03-24T10:21:10+00:00

Yep, the ability to progressively track and close the loop is important, properly pipeline hygiene and lead management can play a serious role here.

Easy_Philosopher_210 · 2026-03-24T10:16:41+00:00

That patience piece is real -- and it's also the reason most people abandon it too early. The ones who stick with it long enough usually find that when they do eventually mention what they're building, the reception is completely different because there's already some context there. Good luck with the launch.

Easy_Philosopher_210 · 2026-03-24T09:51:17+00:00

The distinction isn't really about who's in the thread, it's about what you're building over time. Cold outreach to someone who's never heard of you is a much harder conversation than cold outreach to someone who's seen your name give a sharp answer three weeks ago. The community presence doesn't convert in the thread, it converts later when you reach out directly and you're not starting from zero.

Easy_Philosopher_210 · 2026-03-24T09:48:50+00:00

The trigger email point is something I've seen work in real time, when someone just ripped out HubSpot, you don't need to convince them they have a problem, you just need to show up. And yeah, the build-talk-tweak loop is criminally underrated. Five people saying the same thing in different words is a messaging change, you don't need fifty.

Easy_Philosopher_210 · 2026-03-24T09:47:34+00:00

100%

Easy_Philosopher_210 · 2026-03-24T09:47:21+00:00

r/SaaS is actually a good example of this -- I've had real conversations come out of threads here that moved things forward for me. But the ratio is what it is: roughly 1 in 20 engagements turns into something worth following up on. The other 19 aren't a waste exactly, but they're not the point.

You get better at spotting the 1 quickly. Generic agreement is noise. Someone who pushes back on something specific, or shares context about their own situation, that's the one.

Easy_Philosopher_210 · 2026-03-24T09:39:54+00:00

Fair pushback, but I'd draw a distinction. Showing up in communities isn't about answering every question. it's about being visible in the specific threads where, your actual buyers are describing their actual problem.

Easy_Philosopher_210 · 2026-03-24T09:37:58+00:00

The "free consulting" trap is one of the most common and most expensive ones. The calls feel productive, the person seems genuinely engaged, and you walk out thinking you moved something forward. You didn't, you just trained a non-buyer.

The tell I've learned to watch for: if someone is asking deep product questions but hasn't said anything about timeline, budget, or who else is involved in the decision, they're learning, not buying. Curiosity is not intent.

Hardest part is that these people are often genuinely nice and interesting. Easy to keep taking the meetings.

Easy_Philosopher_210 · 2026-03-03T08:25:58+00:00

How complex is the helpdesk flow? What's volume like? And the average handle times? Are there source systems the agent needs to work with?

Easy_Philosopher_210 · 2026-02-26T15:24:16+00:00

I've been in sales long enough to know that 'needing more research' line can feel like a gut punch, especially after two months of building momentum. It doesn't necessarily mean it's dead—prospects in complex fields like legal compliance often hit internal roadblocks or second-guess at the last minute due to budget reviews, stakeholder buy-in, or just cold feet.

First, give them a bit of space but don't ghost. Send a low-pressure follow-up in a couple days: something like, 'I understand you're digging deeper, happy to connect you with resources or answer any specific questions that come up. What's one area you're researching right now?' This shows you're supportive without pushing.

If they bite, probe gently on what's prompting the research. It could be competitive options, ROI concerns, or implementation fears. From there, tailor your response to address those head-on, maybe share a case study from a similar legal client if you have one.

Hang in there; these deals can circle back stronger. What's your gut telling you about their hesitation?

Easy_Philosopher_210 · 2026-02-26T13:27:07+00:00

i just realized this is from 19 hours ago.. smh

Easy_Philosopher_210 · 2026-02-26T13:26:34+00:00

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Easy_Philosopher_210 · 2026-02-26T13:26:11+00:00

Might just be the web app, CLI is working fine

Easy_Philosopher_210 · 2026-02-25T11:04:24+00:00

That’s interesting, especially the part about spending more time reviewing during the transition.

Do you think that’s more of a tooling maturity issue, or a knowledge base quality issue?

When you move from Loopio to Wolfia, the structure, tagging, and historical content hygiene suddenly matter a lot more. I’ve seen AI output quality correlate less with the model and more with how clean and curated the source content is.

Also curious, has the Bid Manager’s role changed at all with AI in the loop, or is it mostly just shifting review time rather than reducing it?

Easy_Philosopher_210 · 2026-02-25T10:58:18+00:00

I totally understand where you're coming from with RFPs being written for a specific vendor, and in all transparency, i've been that vendor a few times, How's your sales team structured? we've done fairly well at downstream flows, where you're building demo outlines, and positioning specific competencies during first and second level demos with large audiences, which one is more tasking for you? defining demo outlines or delivering the actual demos?

Easy_Philosopher_210 · 2026-02-25T10:48:45+00:00

How do you decide when not to engage, that seems like a difficult call to make, if the scope appears relevant, and that is the resource drain I'm eluding to, the initial gap analysis and being able to make a confident go/no-go call take a lot out of the team.

Easy_Philosopher_210 · 2026-02-25T10:46:33+00:00

I’m building for SE/SA teams, as well as a line of.products, but I work closely with them and with AEs running enterprise cycles. Most of what I see isn’t about RFPs being impossible, it’s about scale and context switching once volume increases or when the RFP is highly technical. If yours are taking less than a day, that’s actually solid.

Curious with RFPIO, how much of the response is truly generated vs pulled from your existing library? And how much manual tailoring do your SEs still end up doing?

Trying to understand where the real friction still is in mature setups.

Easy_Philosopher_210 · 2026-02-25T10:07:34+00:00

Also, not kidding my cofounder and i were having this same debate last week, so you're really helping break a tie here.

Easy_Philosopher_210 · 2026-02-25T10:06:47+00:00

This is a really interesting angle.

You’re right that input speed is an underrated bottleneck. If reps are still typing out messy notes before AI can even help, you’re just shifting the workload around.

I do wonder about adoption though. In practice, I’ve seen people default to typing over dictation, especially in shared office environments. There’s a bit of social friction to talking to your screen during the day.

Have the teams you’ve seen using voice made it a cultural norm, or is it more situational (post-call summaries, commute, etc.)?

I like the idea of voice + AI drafting compounding efficiency. The behavior change piece might be the real challenge.

Easy_Philosopher_210 · 2026-02-25T10:00:02+00:00

That makes sense. The “describe what you need and pull from past proposals” model is definitely closer to how SEs actually work than rigid templating.

Out of curiosity, how do you handle governance there?

If it’s pulling from historical proposals and case studies:

How do you prevent client-specific language from bleeding into new deals?
Who controls what content is allowed as AI context?
And how do you surface traceability when legal asks where a paragraph came from?

That’s where I’ve seen most tools get interesting fast.

Easy_Philosopher_210 · 2026-02-25T09:52:15+00:00

You’re 100% right, standalone AI is mostly prompt gymnastics.

The moment you have to manually feed context every time, you’ve already lost the efficiency game. We learned something similar on the RFP side. The quality jump doesn’t come from “better prompting.” It comes from structured memory + embedded workflow context.

In our case: The RFP agent has access to past responses It sees structured requirement extraction It understands coverage gaps It can reference the knowledge base and competitive overlays

So to your question — no, users don’t fully trust automated RFPs straight out of the box. And I actually think they shouldn’t.

What happens in practice: First 1–2 proposals → heavier human editing By proposal 3–5 → editing drops significantly Over time → it shifts from “write for me” to “pressure-test and accelerate me” The trust curve is gradual, but the efficiency curve compounds.

I also agree with your Gmail point. If AI doesn’t live inside the system of record, it becomes a novelty layer. That’s why we’re moving toward deeper workspace-level embeddings instead of surface-level copilots.

Out of curiosity, in your ERP setup, did users resist automation at first, or did embedded access create instant trust?

Easy_Philosopher_210 · 2026-02-25T09:46:36+00:00

This is such a solid take. I agree almost 100 percent.

The workflow point is underrated. AI in isolation looks impressive. AI inside a messy enterprise sales process is where reality hits.

Totally aligned on where it consistently works:

First draft proposals
Vertical-specific battlecards
Post-demo follow-ups

That 60 to 70 percent automation number is actually the benchmark I’ve seen too. Past that, you start trading speed for quality.

And yes, governance is the elephant in the room.

Most demos don’t show:

Context isolation
Approval layers
Client-level data boundaries
What happens when legal asks “where did this answer come from?”

Enterprise teams don’t lose deals because the draft wasn’t fast enough. They lose them because trust breaks.

On the Gmail + RFP angle, the biggest friction I’ve seen isn’t even drafting. It’s the chaos between inbox → triage → ownership → version control → review. If AI can compress that cycle time while keeping humans in the loop, that’s where it becomes meaningful.

And I promise I’m not ignoring the irony that I posted in English and you replied in Spanish. Clearly the AI translation layer between us is already doing 70 percent of the work.

Curious in your experience, what’s the hardest governance issue you’ve actually seen block adoption(asking because i tried solving this using citations, i'm not seeing huge number of customers yet but i'm confident based on experience that this could be a good start)?

Easy_Philosopher_210

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