Forem: edperlman

We Asked ~1,000 Simulated SaaS Professionals About Vibe Coding. The Data Challenges a Few Assumptions.

edperlman — Wed, 08 Apr 2026 09:30:34 +0000

Vibe coding keeps showing up in every feed, every newsletter, every conference agenda. We wanted to move past the takes and look at what the market actually thinks.

We ran an AI-powered survey using Inqvey - ~1,000 simulated B2B SaaS respondents across 5 roles: VP of Product, CTO, Director of Customer Success, SaaS Sales Manager, and Implementation Specialist. No human panel. Validated against Ipsos human panel data with ±2-5pp accuracy.

A few things stood out.

The interest is real but cautious

52.9% say they're likely to implement vibe coding. But only 19.7% say very likely. The rest are somewhat likely (33.2%) or sitting on the fence (24.2% neutral). This isn't a stampede. It's a market watching closely and moving carefully.

Integration is the blocker, not price

We asked about the primary barrier:

Technical integration challenges - 31.1%
Uncertain ROI - 22.2%
Lack of skilled personnel - 21.8%
Cost - 20.6%

Developers building for this space should pay attention. The people you're selling to aren't worried about what it costs. They're worried about how it fits into what they already have and whether it actually delivers.

UX first, infrastructure later

What's most appealing about vibe coding?

User experience enhancement - 32.6%
Data-driven customization - 29.1%
Flexibility - 16.6%
Scalability - 15.5%

The market sees vibe coding as a product experience layer. Not a performance optimization. Not a scalability solution. If you're building here, lead with the user experience story.

Nobody has a process for evaluating this

This is the quiet finding that matters most. Only 31.9% do regular reviews of emerging tech like vibe coding. 35.9% say occasional. Almost 20% say ad-hoc.

The interest is ahead of the evaluation capability. That means early movers who make adoption easy - good docs, clear integration path, low switching cost - will win disproportionately. The market wants to try this but doesn't have a structured way to assess it yet.

Full data

Full survey results with all 6 questions and methodology:
https://inqvey.com/data/vibe-coding-2026

Browse all trends and research: https://inqvey.com/trends

Is anyone here building with vibe coding in production? Curious what the integration experience actually looks like.

We Surveyed 300 AI-Generated Respondents on AI in Retail - Here's Where the Market Actually Wants AI

edperlman — Fri, 27 Mar 2026 23:45:27 +0000

If you're building AI products for retail, the question isn't whether the market wants AI. It's where.

We ran an AI-powered survey with 300 AI-generated respondents across 4 AI personas matching B2B retail professionals - CTOs, heads of operations, AI solutions architects, and retail data analysts. No human panel. Validated against Ipsos human panel data with ±2-5pp accuracy.

Here's what the data says.

67.7% say they'll adopt AI within 12 months
27.7% very likely. 40% somewhat likely. The adoption intent is clear. But intent without understanding the barriers is useless if you're building for this market.

The top barrier isn't cost
This is the part most people get wrong. When we asked about the primary concern:

Data security - 31%
Integration complexity - 28%
Cost - 21%
Lack of expertise - 17%
No concerns - 3%

If you're building AI for retail and your pitch leads with ROI and cost savings, you're answering a question that isn't top of mind. The buyers are worried about security and integration first. Price is third.

Inventory management wins by a wide margin
When asked where AI would help most:

Inventory management - 38%
Sales forecasting - 26.3%
Customer service - 20%
Marketing - 13%
None - 2.7%

Retail wants AI in the back end. Inventory, demand forecasting, supply chain. Not chatbots. Not personalization. Not marketing automation. The operational pain is louder than the customer-facing opportunity.

For developers - this is useful signal. The highest-demand use cases are the ones that touch operations, not the ones that touch the customer.

Interest is growing, and so is budget
66% say their interest in AI for retail increased over the past year. 68.3% say they're willing to allocate budget. That's not vague optimism - that's purchase intent.

But only 3% say they have no concerns about implementation. Nearly everyone wants it. Nearly everyone is nervous about something.

What this means if you're building
The market is telling you three things:

Build for the back end first. Inventory and forecasting, not marketing.
Lead with security and integration, not price. Those are the real objections.
The buyers are ready. Budget is allocated. But trust and implementation are the bottlenecks.

Full data
Full survey results with all the questions, persona breakdown, and methodology:
https://inqvey.com/data/ai-retail-2026
We track 20 technology trends and run market research across them:
https://inqvey.com/trends
If you're building for retail - what are you hearing from buyers? Does this match?

YC Funded 8 Workflow Automation Startups in 4 Batches. We Dug Into What GitHub, SEC Filings, and Academic Research Show.

edperlman — Tue, 24 Mar 2026 03:38:37 +0000

Workflow Automation is one of the quietest strong signals in our trend tracker right now. No hype cycle. No headline wars. Just real activity from developers, investors, researchers, and enterprises - all moving at the same time.

We built a trend tracking engine at Inqvey that monitors real-time activity across GitHub, YC, academic research, and SEC filings. We pointed it at Workflow Automation - and the data is worth a look.

YC is funding this heavily

8 startups across the last 4 batches. That's one of the highest counts we're seeing across the 20 trends we track right now. YC doesn't repeat-fund a category unless they see a big market with room for new entrants. 8 companies across 4 consecutive batches is sustained conviction, not a one-off bet.

698 new GitHub repos in 30 days

Developers are building. But here's the thing - only 792 stars across all of them. That's a lot of new tooling with not much traction yet. Most of these projects are early. The space is still wide open for someone to build the thing that gets real adoption.

7 SEC filings

Public companies are disclosing workflow automation as material to their business in regulatory filings. Nobody puts something in a 10-K unless their legal team considers it significant enough to affect financial performance. This has moved past IT budgets into board-level conversations.

183 papers, 97 citations

Moderate academic output compared to something like cybersecurity (396 papers, 9,400 citations). The applied side is ahead of the research side here. This is a practitioner-driven space - people are building and shipping, not waiting for the theory to catch up.

Hacker News: 14 stories, 36 points

Low community buzz relative to the investor and developer activity. Workflow automation doesn't spark the same debates as AI agents or security breaches. But the fact that VCs and developers are active while the community is quiet is actually a useful signal. Less noise, less competition.

What this pattern tells you

High investor conviction. High developer activity. Low community hype. That combination usually means a "boring but big" market. The buyers have real pain, the VCs see it, but there's no media circus driving up competition.

For anyone thinking about building in this space - pain-driven markets with low noise tend to convert faster because the buyer already knows they have a problem.

Full data

We track workflow automation alongside 19 other technology trends, updated regularly. Each one gets a full signal breakdown with sources and evidence.

Browse all current trends: inqvey.com/trends

Full Workflow Automation breakdown: inqvey.com/trends/workflow-automation-2026

What's the most underrated space you're watching right now?

We Tracked 20 Tech Trends Across Real Data Sources. Here's What's Actually Hot Right Now.

edperlman — Sat, 21 Mar 2026 22:00:55 +0000

AI Agents is the strongest signal in our trend tracker right now. Not because someone wrote a hot take about it. Because the data says so.

We built a trend tracking engine at Inqvey that scans real-time data sources to identify what's actually trending in technology. Not opinions. Not vibes. Real, verifiable activity from developers, investors, researchers, and enterprises.

Here's what we found for AI Agents.

Hacker News: 674 stories, 3,678 points

Hacker News is where the tech community discusses what matters. 674 stories about AI Agents in the last 14 days, with 3,678 total upvotes. That's a massive amount of attention from developers and technical founders. HN activity tends to precede mainstream adoption by 1-3 months.

GitHub: 791 new repos, 150,300 stars

791 new repositories created in the last 30 days. Developers aren't just talking about AI Agents, they're building. 150,300 stars across those repos means the projects are getting real traction. GitHub creation velocity is typically a 3-12 month leading indicator of market adoption.

Y Combinator: 25 startups across 4 batches

25 YC-backed companies working on AI Agents, spread across 4 recent batches. When Y Combinator funds 25 startups in a single category, that's serious conviction from the most influential startup accelerator in the world.

Stack Overflow: 8 questions

Relatively low compared to other sources, which tells us something important: developers are building AI Agents but the tooling ecosystem is still maturing. Stack Overflow questions typically pick up as technology moves from experimentation to production deployment.

Academic Research: 291 papers, 2,800 citations

291 papers published on AI Agents recently, with 2,800 citations. Academic research is usually the earliest signal. The fact that researchers are publishing heavily means the theoretical foundation is solid and applied work is accelerating.

SEC Corporate Filings: 3 disclosures

3 mentions in SEC 10-K/10-Q filings. This is the newest signal and the most significant. When public companies disclose a technology to regulators, they consider it material to their business. This number is small now but it's a strong validation signal. For comparison, Generative AI already has hundreds of SEC mentions, and AI Agents is following the same early pattern.

What this convergence means

When developers are building, the community is discussing, investors are betting, researchers are publishing, and enterprises are disclosing all at the same time, that's real market movement, not hype.

This level of convergence historically precedes mainstream adoption within 3-6 months.

The gap that tells a story

The interesting gap is between GitHub activity (791 repos) and SEC filings (3). Developer tooling is way ahead of enterprise adoption. That gap usually closes as the tooling matures. If you're building in the AI Agents space, you're early, and that's a good position.

Compare this to Generative AI, which has the opposite pattern: heavy SEC disclosure but relatively fewer new GitHub repos. Generative AI is enterprise-driven. AI Agents is developer-driven. Both are real, but they'll play out differently.

Full data

We publish the complete source-by-source breakdown for AI Agents and 19 other tech topics, updated regularly.

Browse all current trends: inqvey.com/trends

Full AI Agents breakdown: inqvey.com/trends/ai-agents-2026

What trend are you watching right now?