Vera Field

Vera-field.com

We're specialized in Process & AI Automation for solar installation and maintenance companies.
Try our free 60-minute workflow assessment where we:

- Identify which manual processes are consuming 10+ hours of your team's time each week
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AI & automation consultant 

I help product teams move from feature-driven to outcome-driven ways of working.

My methodology in a nutshell:
- Create internal alignment on target audience/ICP
- Align on business & and product goals (OKRs, hierarchy of metrics)
- Set up or improve idea discovery & validation processes (e.g. customer interviews, shadowing, protoyping, usability testing, A/B testing)

Interim Product Lead/ Advisor/ Coach

Wave Terminal

- Definition of ICP & beachhead segment
- Setting up & executing customer discovery and experimentation processes
- Defining a product strategy that helps Wave find a differentiated spot in the market

Interim Product Lead

HiveDesk

HiveDesk offers automatic employee time tracking software with project, task, and cost tracking. I'm advising the HiveDesk team on how to build a product that fits seamlessly to their customers needs. Setting up robust product analytics and continuous product discovery to help improve the HiveDesk onboarding flow - from 'aha' to 'habit' - and corresponding metrics.

Product Advisor

Rodeo Software

- Improving the Rodeo New User Experience (setup & activation)
- Helping the Product team move to outcome-driven ways of working
- Setting up & executing discovery & experimentation processes

Interim Sr. Product Manager

Datawallet

Head of Product

Bridgemaker GmbH

Senior Venture Architect

CrefoPayment GmbH & Co. KG

Head of Product and QA

Hungr

Operations Manager

payleven

Project Manager Operations

Team Leader Operations

Product Leader | I help SaaS startups build products that customers love | sonderhouse.io

Read my Idea Discovery & Validation guide here: https://eu1.hubs.ly/H0dfJkm0

What I do
I help B2B SaaS and service companies move from feature-driven to outcome-driven ways of working.
More recently, I also help teams become AI-fluent and build AI-driven products.

How I do it
- Align leadership on the #1 ICP, business, and product goals
- Set up or strengthen discovery & validation practices (continuous discovery, product analytics, rapid testing)
- Coach teams on integrating AI into product strategy and workflows

My belief
Great products come from:
- Sharp focus on the right target audience
- Continuous discovery and rapid validation
- Teams empowered to drive business outcomes, not just ship features

Background
15+ years in product and strategy roles across startups and scaleups in Berlin. I’ve seen successes—and just as many hard lessons.

Work with me
I work as a coach, advisor, or interim product lead. More of my thinking at elsevanderberg.substack.com

Dr. Else van der Berg

New adventure alert: I've joined SwitchUp as a Product Consultant 🍾 

To the outside world, Switchup is a service that monitors energy contracts in Germany - making sure customers always get a fair deal.

Internally, we're rebuilding the entire company as an AI-first subscription agent.

The goal isn't to automate human customer support out. It's to automate the noise around them, so they can focus on offering top-notch service where it's needed. 

𝗪𝗵𝘆 𝗱𝗶𝗱 𝗜 𝗷𝗼𝗶𝗻?

🔹  A small nimble team of very smart, curious, and humble people. I'm not just saying that to stroke their egos  Arik Meyer Maren Hinzmann Inna Makoterska

🔹  Very fun project, and the stuff of the future! Automation workflows & AI where it actually makes sense, building an internal tool where AI agents and humans can collaborate. Lots of space to play and learn. 

🔹 Arik Meyer puts his money where his mouth is. No "blah blah we're gonna change the world" - besides the for-profit business Switchup he founded a not-for-profit sister company that helps consumers that have been screwed over get justice. 

We're looking for M-shaped people with an engineering and/or product background to join un (Product engineer; Technical product manager; Data architect). Hit me up if you'd like to work with me!

Product management for AI-native startups │ Interim, advisor, coach

I built an AI agent that finds customer quotes for opportunities (pain points, wishes, desires). Here's how it works - and why I still manually compile the end-report:

𝗧𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺: Teams enthusiastically jump to solutions without really understanding the opportunity.

So before ideation sessions, I send participants a pre-read with:
👉 Opportunity description
👉 Evidence why it matters
👉 Direct quotes from customer interviews
In the pre-AI era, manually hunting through interview transcripts took hours. Thank god for LLMs.  I built an agent (using windsurf + Claude Code) that:

- Analyzes all interview transcripts for relevant quotes
- Optionally searches subreddits where your ICP hangs out

𝗖𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗻𝗼𝘁𝗲𝘀:

1. Interview quotes >>> forum posts (you know the context and ICP fit). Forums are full of noise, BUT still nice to get a feel.

2. Your transcripts need proper structure/format for the agent to work!

3. I NEVER send AI reports directly to my team. The agent does heavy lifting. I verify every quote, check for hallucinations, and craft the final document.

Result: Better ideation built on genuine customer understanding, not assumptions.

AI amplifies research. Human judgment ensures quality. That's the balance.

PS. this video is cut after 5 minutes, find the full video on Youtube.
PPS. You can fork my agent from Github. I would suggest tailoring it so it can make sense of YOUR interview transcripts, and follows your own process. You can also just start with my prompt (Notion URL) and build your own

Yes, GPT 5.1 and Gemini 3 are AMAZING, I can ship good-looking stuff even faster now. But they're still not helping me decide *what* to build in the first place. 

It feels like the age-old problem of "getting value out of qualitative customer feedback scattered across sources" is still unsolved.

We've got interview transcripts, we've got sales calls in Gong, we've got survey responses in Pendo, etc. etc. but how can we make sense of it all?

Where do we centralize it and structure it in a way that LLMs can work with it? 

I'm imagining:

👉  Feed an opportunity (customer pain point, desire, wish) to the AI agent of my choosing. Output: every relevant customer quote, plus counter-evidence and competitive analysis; OR

👉 Have AI agent proactively surface patterns and opportunities across all qualitative data sources.

What am I missing? Who's solving this? What's the most difficult part?
Help me out here guys.

Specialists built the last generation of tech companies. Generalists will build the next.

Last week at @producttank someone asked the question "How do AI-native companies  build products differently - compared to "legacy" tech scale ups?"

The question often gets narrowed down to "will PMs survive?" or "are engineers replaceable?" That misses the point.

What's actually shifting is 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲.

AI-native companies are smaller. Small and nimble is an asset.

They're hiring what I call natural convergers - M-shaped people who cross domains naturally, without friction. Engineers who ask "what evidence do we have that this matters?" PMs who learn technical concepts by prompting their way through problems.

When one person can run a full build-measure-learn cycle, you don't need handoff managers. You don't need as many layers.

👉  𝗧𝗵𝗲 𝗹𝗲𝗴𝗮𝗰𝘆 𝗺𝗼𝗱𝗲𝗹: specialists in silos, product trios trying to bridge gaps, feedback loops spanning multiple roles.

👉  𝗧𝗵𝗲 𝗔𝗜-𝗻𝗮𝘁𝗶𝘃𝗲 𝗺𝗼𝗱𝗲𝗹: generalists using AI to constantly upskill, zero handoffs, everyone spotting problems and shipping solutions.

𝗧𝗵𝗲 𝗿𝗲𝘀𝘂𝗹𝘁? 
1. More eyes on problem discovery, more diverse ideas, therefore better ideas.
2. Much faster build-measure-learn feedback cycles. Learning velocity is the moat. 

I joined SwitchUp a month ago, and I love it. We have a small team of people of convergent thinkers who can't stay in their lane, love to try new things, share learnings, and solve problems.  I'm looking for more of those!

Are you a:
👉  𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿/𝗽𝗿𝗼𝗱𝘂𝗰𝘁-𝗺𝗶𝗻𝗱𝗲𝗱 𝗳𝘂𝗹𝗹-𝘀𝘁𝗮𝗰𝗸 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿 (you'd be owning a problem,  without a PM by your side)
👉 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗣𝗠 (having owned a technical product before, e.g. API or payment gateway; loving BPMN/state machines/workflow orchestration)
👉 𝗗𝗮𝘁𝗮 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁

Hit me up!

I built an ideation agent, and you can fork it.
If you throw a problem at an LLM and let it ideate from scratch, you cut off your own creativity. You anchor on its output. You stop thinking.

So I built an agent that forces ME to go first.

It gathers context. It asks what "good" looks like (weighted criteria). It makes me input my own ideas before the LLM generates anything.

The result: a sparring partner that helps me get unstuck - not an outsourced brain.

I love vibe coding these agents with Claude Code. It forces me to think through and lay down my process. It's codified "Else".

Walkthrough in the video. GitHub repo + initial prompt linked in comments - fork it, make it yours.

I've spent years preaching "validate before you build."

Now I'm working on a product where we basically just… build things and see what happens.

𝗧𝗵𝗲 𝗼𝗹𝗱 𝗮𝗿𝗴𝘂𝗺𝗲𝗻𝘁𝘀 𝗳𝗼𝗿 "𝘃𝗮𝗹𝗶𝗱𝗮𝘁𝗲 𝗳𝗶𝗿𝘀𝘁" 𝗵𝗮𝘃𝗲 𝘄𝗲𝗮𝗸𝗲𝗻𝗲𝗱.

👉  𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝘄𝗮𝘀 𝗲𝘅𝗽𝗲𝗻𝘀𝗶𝘃𝗲. Not anymore. Features that took months ship in a week with AI-assisted coding.

👉 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗺𝗲𝗮𝗻𝘁 𝘀𝗹𝗼𝘄 𝗳𝗲𝗲𝗱𝗯𝗮𝗰𝗸 𝗹𝗼𝗼𝗽𝘀. Building is much, much faster thanks to robust AI assisted coding workflows (don't worry, it's not me vibe coding this ;) )

👉 𝗙𝗲𝗮𝘁𝘂𝗿𝗲 𝗯𝗹𝗼𝗮𝘁 𝗺𝗮𝗱𝗲 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝘀 𝘂𝗻𝘂𝘀𝗮𝗯𝗹𝗲. With SaaS products, users had to dig through menus and toggles. But Wave has an integrated AI agent - you just tell it what you want. The surface area problem is different now.

At the same time, pre-build validation hasn't gotten us far. 
Sure, it has helped us get inside users' heads, and make sure we don't ship anything completely incomprehensible/unusable, but it hasn't helped us *validate*. 

I've been running 1:1 shadowing sessions (where new users try Wave), and landing page tests (comparing a variety of different value props and ideas). 
These have been useful for "do people understand this" , but not for "𝘄𝗵𝗮𝘁'𝘀 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁 𝗺𝗮𝗴𝗶𝗰𝗮𝗹 𝗶𝗱𝗲𝗮."

Our ideas about 'how we can frame Wave' change weekly because the landscape moves so fast. No stable baseline to compare against, small sample sizes -> no patterns. 

And with LLM-powered products, so much is in the execution. Does the AI actually deliver? You can't know until you build it.

The most reliable signal is shipping. Put it in the world. Watch what happens.

Join me at the live Product Engineers podcast today at 17.00 where I'll be chatting with my friend Peppe Silletti about product/dev roles converging.

Engineers are getting involved in product decisions that would have traditionally belonged to PMs. Product managers are shipping code. Designers are ditching Figma for vibe-coded prototypes that ship faster than polished mockups ever could.

Everyone's getting accused of shiny new object syndrome. 
Everyone stepping on each other's toes.

But what about cognitive load? Can one person really be an expert on multiple domains (e.g. both Product AND Engineering), or are we creating "masters of none"?

What has AI changed?

Let's dive in!

PS Peppe - thanks for the artwork. 

Posting the link in the comment section.

"𝘛𝘩𝘦 [𝘱𝘳𝘰𝘥𝘶𝘤𝘵 𝘥𝘦𝘷𝘦𝘭𝘰𝘱𝘮𝘦𝘯𝘵] 𝘸𝘰𝘳𝘬 𝘪𝘴𝘯’𝘵 𝘤𝘰𝘮𝘱𝘭𝘦𝘹 - 𝘵𝘩𝘦 𝘱𝘳𝘰𝘤𝘦𝘴𝘴 𝘩𝘢𝘴 𝘮𝘢𝘥𝘦 𝘪𝘵 𝘤𝘰𝘮𝘱𝘭𝘦𝘹. 𝘗𝘳𝘰𝘥𝘶𝘤𝘵 𝘥𝘦𝘷𝘦𝘭𝘰𝘱𝘮𝘦𝘯𝘵 𝘪𝘵𝘴𝘦𝘭𝘧 𝘪𝘴 𝘴𝘪𝘮𝘱𝘭𝘦: 𝘳𝘦𝘴𝘦𝘢𝘳𝘤𝘩 𝘢 𝘱𝘳𝘰𝘣𝘭𝘦𝘮, 𝘥𝘦𝘴𝘪𝘨𝘯 𝘪𝘵, 𝘤𝘰𝘥𝘦 𝘪𝘵, 𝘭𝘢𝘶𝘯𝘤𝘩 𝘪𝘵, 𝘢𝘯𝘥 𝘪𝘵𝘦𝘳𝘢𝘵𝘦. 𝘉𝘶𝘵 𝘰𝘷𝘦𝘳 𝘵𝘪𝘮𝘦, 𝘤𝘰𝘮𝘱𝘢𝘯𝘪𝘦𝘴 𝘵𝘶𝘳𝘯𝘦𝘥 𝘦𝘢𝘤𝘩 𝘴𝘵𝘦𝘱 𝘪𝘯𝘵𝘰 𝘥𝘰𝘻𝘦𝘯𝘴 𝘰𝘧 𝘴𝘶𝘣-𝘴𝘵𝘦𝘱𝘴 𝘳𝘦𝘲𝘶𝘪𝘳𝘪𝘯𝘨 𝘮𝘶𝘭𝘵𝘪𝘱𝘭𝘦 𝘵𝘦𝘢𝘮𝘴, 𝘳𝘦𝘷𝘪𝘦𝘸𝘴, 𝘢𝘯𝘥 𝘧𝘶𝘯𝘤𝘵𝘪𝘰𝘯𝘴. 𝘞𝘩𝘢𝘵 𝘶𝘴𝘦𝘥 𝘵𝘰 𝘳𝘦𝘲𝘶𝘪𝘳𝘦 𝘰𝘯𝘦 𝘣𝘶𝘪𝘭𝘥𝘦𝘳 𝘯𝘰𝘸 𝘵𝘢𝘬𝘦𝘴 𝘴𝘪𝘹 𝘮𝘰𝘯𝘵𝘩𝘴 𝘢𝘯𝘥 𝟣𝟢 𝘵𝘰 𝟣𝟧 𝘥𝘪𝘧𝘧𝘦𝘳𝘦𝘯𝘵 𝘵𝘦𝘢𝘮𝘴 𝘫𝘶𝘴𝘵 𝘵𝘰 𝘴𝘩𝘪𝘱 𝘢 𝘴𝘮𝘢𝘭𝘭 𝘧𝘦𝘢𝘵𝘶𝘳𝘦."

Just had a listen to Lenny Rachitsky's conversation with Tomer Cohen, CPO @ LinkedIn (link to podcast in comments). Tomer explains his new "Full Stack Builder" program, that "teaches coding, design, and PM skills together." The idea is to enable anyone to single-handedly go from idea to launch. 

Very much in line with the role convergence I've been seeing, especially in AI-native companies (think Lovable, Perplexity, Linear, Cursor, and Elevenlabs) (see link to my latest Substack article "Why Your Best Engineers Have Product Sense and Your Best PMs Ship Code" in the comment).

Companies that want to *drive* - not follow - change in the AI era are making drastic org. chart changes to kill the "handover tax". Flat hierarchies. Small teams. M-shaped people that can identify and tackle problems single-handedly.

Everyone's trying to buy word of mouth right now.

I get it. AI-native tools need an extremely powerful WOM machine just to get picked up once by early adopters. Eeeveryone is suffering from AI tool fatigue. 

People will only give you a try if you've been recommended by MULTIPLE people they trust.
So naturally, everyone's trying to buy their way in. 

As a "mini influencer" I get the pitch regularly: cash and "advisory council" spots to plug products.

I don't think it works.

A couple of paid influencer posts aren't enough to create the omnipresence an AI startup needs to cut through the noise.

I say this from experience.  I've taken the "advisory council for a post" offer twice - only for products I genuinely believed in. Both posts performed terribly. I'm probably not doing it again. It costs authenticity. Not worth it.

But when I write about Vistaly or Claude Code? Those posts fly. Because I'm a genuine power user sharing how I actually work. They're chockfull of"in the trenches" authenticity.

So if you can't buy WOM, what's the answer?

𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝗽𝗲𝗼𝗽𝗹𝗲 𝗴𝗲𝗻𝘂𝗶𝗻𝗲𝗹𝘆 𝘄𝗮𝗻𝘁 𝘁𝗼 𝘁𝗮𝗹𝗸 𝗮𝗯𝗼𝘂𝘁.

We're trying hard Wave Terminal. Last week a fan posted about us in China. 155K views. Got picked up by the GitHub community. 60K more views. A wave of installs.

We couldn't have bought that. It only happened because someone found it remarkable enough to share unprompted.

The toughest part: "remarkable" keeps shifting. AI capabilities upgrade constantly. Today's magic is tomorrow's baseline.

So you ship fast. You find the wow before the window closes.

We're going with: 𝗦𝗽𝗲𝗲𝗱 𝗮𝗻𝗱 𝗰𝗼𝗻𝘃𝗶𝗰𝘁𝗶𝗼𝗻. 

(PS I described my experiences GTM & Product discovery at Wave Terminal in my latest Substack article, link in comment)

Emilia Korczynska

Userpilot

VP of Marketing

Doing all it takes to get more Product People over the code barrier with our code-free Product Adoption, Marketing & Experimentation Platform:  
Designing, developing and implementing a marketing strategy that ensures higher visibility 
Leading our stellar content team 
Implementing and driving a paid ads strategy to diversify customer acquisition. 
Driving funnel growth
Implementing an email marketing strategy 
Identifing and testing new acquisition channels
Overseeing, training, and coaching team members

Head Of Marketing

Managing content operations for a fast-growing B2B SaaS company - Product Experimentation and Marketing Tool for Product Teams: 
- Content planning, SOP development, SEO keyword research and topic ideation 
- Content editing and creation (blogs, website copy, social media content, ebooks, landing pages) 
- Community building (esp. Facebook - growing Product Growth & Retention Group, and LinkedIn) 
- Partnership management (guest posting, co-promotion)
- Writing weekly newsletters and developing email marketing workflows
- Organizing Product Drive - an annual online conference for Product People  (first edition: 2200+ participants)
- Data Analysis and Reporting (Google Analytics)

Marketing Manager

Wisemont Language Services

Boutique language agency helping SMEs sell more through great content on international markets

- Content marketing: translating, localisation and copywriting of SEO blog content, articles, website copy, newsletters etc. 
- International Social Media management 

Responsibilities:
- Developing and marketing new service packages and new in-formation products 
- Supervising development of content marketing strategies and SEO content for our clients that bring results – e.g.  ranking on 1st page in Google for competitive keywords, growing Twitter following to 3500 in 4 months

Owner

Postfity.com

- Helping more startups and small businesses hear about the most affordable social media scheduler designed specially for SMBs through: 
- creating a documented content marketing strategy, planning paid and organic marketing activities (content resharing, social media listening using Brand24, email marketing), setting and monitoring KPIs, measuring results using Google Analytics and Social Media Insights 
- hiring and managing marketing professionals: Social Media Managers, Copywriters, Facebook Ads Specialists, Google Ads Experts, Graphic Designers
- setting up and optimising email marketing drip campaigns
- doing Competition and Keyword Research, optimising blog content for search engines, creating new blog content optimised for low-difficulty keywords
- A/B testing Facebook ad campaigns
-  managing the marketing budget

Marketing Strategist

Find in China

Find in China is an online directory of local services, venues and events on a map in English designed for the expat population in China. Together with other local websites for expats we are creating the largest database of information and socialising opportunities for foreigners in China, as well as  a nationwide discount card. [Acquired October 2018] 
Responsibilities:
- Designing a web-app - map-based directory of venues, ser-vices and events in China
- Front-end project management – liaising with the front-end developer to produce the desired results in terms of design, functionality and user-experience, and with the back-end pro-ject manager 
- Business development and general management -  searching for joint ventures and collaborations to grow our database of point of sales and events quickly (we launched with over 1000 POSs across China), social media marketing

Co-Founder and CEO

Birmingham City University

Leading an in-country presessional course for students of Nanjing University of Science and Technology 
Teaching Academic Study Skills

ICP Visiting Lecturer

Swansea University

Teaching (Polish) Translation and Interpreting MA students:
- Module: Advanced Translation) 
- Module: Public Service Interpreting: Local Government Option
Supervision: Translator's Tools 
Material, test and examinations development

Part-time Translation and Interpreting Tutor

Runner's Delight

Runner's Delight was an innovative brand of functional porridge designed especially for runners. 
Responsibilities: 
- Designing and launching a sports nutrition product for runners
- Assisting in branding, social media and influencer marketing

Co-Founder and product manager

PayPal

EMEA Collections Specialist

Stream Universe TV

- managing relations with contributors: 
- contacting influential bloggers attracting large numbers of followers with commissions for film / TV series reviews and content writing;
- providing writers with updates on new releases, writing opportunities, etc.
- keeping  submission deadlines

Account Manager

The Cambridge Student

- writing a weekly series of satirical columns

Columnist

Passionate about SaaS product growth, and both the pre-sign up and post-sign up marketing. Talk to me about improving your acquisition, activation and retention strategy. 


Every marketer will tell you the same thing “We have enough data. We don’t have enough insights.” Especially at the end of the year, when we’re all going into “reporting mode” - we’re drowning in data and desperately trying to make sense of it, to plan our 2026 budgets. 

AI should change that. 

This is why I’m so proud that Michal Jackowski is launching Zena - LinkedIn Ads AI Analyst today on Product Hunt - please check out the launch here: https://zenabm.com/ph

Zena answers all your questions about your LinkedIn Ads performance, your ABM campaigns, your target companies’ engagements with your ads *AND* the impact of your campaigns on revenue and pipeline. 

TL;DR - my husband has been working very hard on making it happen for almost a year, and I’ve been the harshest critic ;D I rarely like anything he does that doesn’t involve pasta - and I wouldn’t be sharing this launch with you if I didn’t think this is a game changer for reporting on ABM Campaign performance through LinkedIn ads. I’ve been feeling all the pain of doing this manually myself and this product is made of my tears (proverbially, of course :D) 

How does it work? Zena combines data from 30+ LinkedIn ads API endpoints with data from your CRM, and processed data from ZenABM (that already combines all the above data sources into one single source of truth, and calculates account engagement scores, ABM stages etc.) 

Here are the types of questions you can ask Zena about your LinkedIn ad and ABM performance data: 

 🟢 Ask Zena about your top performing ads, and ad formats - which had the highest number of clicks & CTR. 
🟢  Ask Zena to get you a list of your most engaged companies in different timeframes by clicks, impressions etc. AND by inventory type (image, TLA, chat).
🟢 Ask Zena which of your ad campaigns are driving pipeline, and which are only wasting budget. 
🟢  Ask Zena about the impact of your ABM campaigns on your funnel and TAM - how companies you’re targetting moved stages month over month, how much you’ve spent on them etc.
🟢  Ask Zena which of your ABM campaigns (and LinkedIn Campaigns) had the highest impact on revenue e.g. this vs. last month. 
🟢  Ask Zena about your ICP’s engagements - which job titles engaged most with your campaigns - month by month.

Getting all these questions answered just by looking at LinkedIn Campaign’s Manager or my Hubspot dashboards would take me ages - now I can get them answered in seconds, with beautiful reports generated by Zena.  

P.S. You can try Zena for free - you get 10 chats with Zena in ZenABM’s free trial - perfect for your end of the year reporting.

VP of Marketing @Userpilot. Author @ Product Rantz.

Someone (from the tech industry) asked me where I worked and what Userpilot was this weekend. And for the first time (hold my coffee), without thinking much, I responded: it’s a “Lovable for Product Adoption”. I know it’s a bold statement…and a complement for Lovable for becoming a household name for the category of no-code software in such a short time. And I know - sadly, no matter how much I bend myself over backwards here - it will never be as popular - because product adoption, unlike acquisition (which I have a hunch Lovable is mostly used for) is still “Cinderealla’s ugly cousin”. 

But here’s the irony - as the entry barriers to shipping software are getting lower and lower with Lovables of the world (and the competition is getting more and more cutthroat) ease of use and Time to Value are the strongest factors in determining whether someone will continue using your product, or start shopping around again at the slightest hint of friction. Nobody’s reading help docs anymore. You either provide instant answers in-app, or the users leave.

The irony why perhaps product adoption software hasn’t been that popular is also because the legacy solutions in the industry were notoriously difficult to use (iykyk).

The popularity of Lovable lies in a) how easy it is to use b) how fast it allows non-technical users to ship market-acceptable assets they could never dream of producing without a designer and a developer. “Acceptable” is better than “perfect” - because the difference between acceptable and perfect, in my experience, is exactly the same as “done” vs. “Not done”. 

👉 Yes, you could hard-code your onboarding experiences. But you know you won’t.
👉 Yes, you can use the legacy product adoption platforms…but that’s the modality of the word ‘can’. If you can’t ship what you need in < a few hours without developers’ / designers’ help - you won’t.
👉 You could buy 5 different solutions for lifecycle email, in-app communications, and product analytics - but you know the data will be falling through the cracks and you don’t use it consistently between the different tools. Your use communication will be broken. 

So give Userpilot a try for 30 days - we’ll support you with our new “Product Growth Jumpstart 2026” program (Chat to our product Growth Expert: https://lnkd.in/duKmW2hY to participate) to help you make most out of your free trial, and demonstrate to you how much more product-led growth (not only in terms of new acquisition, but also expansion) your team can produce if it’s empowered to engage users and build in-app product onboarding & adoption experiences truly on their own, with data available on their fingertips.

Open article: 15 Minute Meeting - Kelli Truelove by calendly.com

I saw this post about 2026 predictions by George Chasiotis in my inbox the other day and nodded vigorously at the first point: 

"1) Consolidation of SaaS:

I expect 2026 to be a strong year for SaaS M&A.
Some of it will be necessary. Some opportunistic. Some both.
SaaS entered a consolidation phase when AI went mainstream three years ago. While part of the activity is obviously driven by AI disruption, a big chunk comes from companies that raised heavily during the ZIRP era—at valuations that no longer make sense.
Now, they consolidate to stay afloat and create enterprise value—enough to give their investors a shot at liquidity."

This dovetails with what I wrote in my previous emails - AI has made the SaaS landscape even more competitive. First - because there are so many new solutions floating on the market every week. Second - because teams are getting more and more empowered by tools like Lovable to build their own, bespoke solutions. 

I didn't believe this would happen just a few months ago, but now I'm seeing this shift happen in my team.

Six figure price tag for a point solution is not defensible anymore. And in niche B2B SaaS - a ACV below $5000 is a death sentence. You can almost never grow beyond $10m with such low ACV. 

So expensive platforms need to quickly justify their price tag by offering significantly more value.

Being a one-trick pony for one team is not enough. 

You need to go cross-functional, become the go-to platform that can be used by several teams for several use cases, and that provides so much value for so many people that it's essentially impossible to rip-and-replace. 

That's one reason to consolidate. Another is the security risks.

Integration surfaces are being increasingly seen not only as a nuisance, but also - a huge security risk. Nick Malekos recently wrote about it in his newsletter as well.

Every other month we hear about some significant security risk. Recent breaches illustrate this clearly: both Drift and Mixpanel were compromised involving third party integrations.

So now, back to the "Build vs Buy" debate - the idea of each team member being able to build their own stack sounds great in theory. 

But in practice - the hackers are just waiting for your "Rosie from HR"  to upload half of your CRM to chatGPT. Creating "shaddow stack" is a massive security risk that is being exploited more and more. 

Security is the price your team may pay for the "DIY" stack. 

So maybe don't. 

Don't risk it. Choose a platform that caters well to the use cases you need, for a reasonable price. I may know one 😉 

Read more about the shift to consolidated platforms in SaaS in 2026 below 👇

Someone asked me for my projections for 2026 - "Consolidation" is the first word that springs to my mind. I saw this post about 2026 predictions by Ge

Open article: 🟣 The circle of life in SaaS is closing: Watch out for slippery surfaces  by Emilia Korczynska • 4 min read

🟣 The circle of life in SaaS is closing: Watch out for slippery surfaces

If you’re rethinking security of your data with your vendors, you’re not alone. First Drift, now Mixpanel. In the last few months, some of the biggest, most enterprise ready SaaS companies have been in the news for serious security breaches, compromising PIIS. Despite “enterprise ready” security. Despite SOC 2 Type II, ISOs and HIPAA. How??

The latest one was a “smishing” attempt (sms phising - yeah I had to ‘google it’). The previous one was OAuth token theft attack - which investigators believed was caused by either phishing stealing API keys/internal tokens/ or compromised internal systems.

Now - SOC II or ISO couldn’t have prevent any of that. Security certifications indicate the implemented standards (in terms of governance, control, encryption, training, risk assessments), but don’t (and can’t) prevent human error, theft, or impose design and architecture choices like per-tenant OAuth separation or short-lived access tokens.

So - these security can happen. SOC II does not make you immune - and if you think larger players are necessarily more immune to attacks - think twice. 

They are more likely to get attacked in the first place.

So if your procurement is pushing you to choose/ stay with a legacy solution that you don’t really like just because it appears more secure - say ‘no thank you’.

Userpilot has been SOC II Type II, ISO & HIPAA compliant for years too. We’re not claiming we have better security than Mixpanel (you can compare the tools here, including security: https://lnkd.in/dzd_KcKr). But we do offer better value for money:

- We combine analytics + action, so you can immediately trigger in-app onboarding, tooltips, and feature prompts based on user behavior.

- We offer built-in in-app user engagement tools (tours, checklists, spotlights, modals) and email -  something analytics tools alone don’t offer.

- We provide native user feedback collection tools via in-app surveys, NPS, and microsurveys alongside analytics.

- Userpilot is more accessible for product managers and marketers, with a simpler UI and less data-model complexity.

- It offers faster time-to-value, since teams don’t need to manually instrument events or maintain a tracking plan.

- It's designed specifically for product adoption, activation, and onboarding use cases - not just data analysis.

- It offers lower implementation and maintenance overhead, especially for small or mid-sized SaaS teams.

- Userpilot allows immediate experimentation (A/B for in-app flows) without relying on dev resources.

- It's better for driving outcomes, not only measuring them - helping teams improve activation, retention, and feature usage directly.

Meanwhile - are you overpaying for ‘enterprise security’ that doesn’t in fact offer neither a guarantee of security, nor extra functionality in return?

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