Product Growth

Author of 1 newsletter deep dive and 2 podcast episodes a week on how to succeed as a PM, product leader, or aspiring PM.

Lead a team of folks.

I'm the product guy - making sure everything hits our ever increasing quality bar.

Here's a sample of recent content:

Course 1: Mastering the PM Career

Unit 1: The Key Outputs

Product requirements documents
Roadmaps: Advanced techniques
The feature results writeup
The product review bible

Unit 2: Hard Skills

Advanced discovery techniques
How to identify and validate product risk
Advanced customer interview techniques
How to ramp a product team without strategy

Unit 3: Soft Skills

How to say no
Handling conflict as a PM
How to bridge the divide between stakeholders and users

Unit 4: Career Skills

The PM Career Ladder: Your Unofficial Guide
How to get a raise in this market
Why politics isn’t a dirty word

Course 2: Mastering Growth

Unit 1: Lessons From The Greats

How Miro grows
How Canva grows
How Klarna grows
How did Intel do so Badly?
Everything about Midjourney
What you need to know about Temu

Unit 2: Systematizing Our Learnings

Build a detailed growth model
Gaming growth playbook
When to A/B test
Impact Sizing
Growth loops
How to build a flywheel
How to use Code Interpreter

Unit 3: Success in Specific Product Teams

Information Architecture
Product-led sales
Design Systems
Product Copy
Onboarding
Expansion
Activation

Course 3: Product Leadership

Unit 1: How to set up your product team

How to set up your product team
Do you really need a North Star Metric
Pitch a growth role to senior leadership
How founders think differently from PMs

Unit 2: How to scale your team

Billion-Dollar Execution
How to scale a product team from 0 to 15
Reference checks can supercharge your hiring

Unit 3: How to be a great leader

7 currencies of a product leader
The 7 failure patterns of managers
How to Make Your Ideas Stick
Product leadership in India

Newsletter Author, Podcast Host

Apollo.io

Product leader when the company became a unicorn ($750M->$2.5B valuation).

I led several product teams, including the growth team, pricing & packaging, activation, expansion, information architecture, acquisition, and engagement.

Raised at a unicorn valuation while I was there.

Ended up leaving to focus full-time on my newsletter.

VP of Product

Affirm

Member of the senior product leadership team. Led growth team when company revenue grew from $300M to $1.2B/year.

Head of Growth Product

Epic Games

Led data driven growth for Fortnite during some it's best performing years, including the Travis Scott Concert and launch of "Chapter 2."

Lead Product Manager

thredUP

Built and led the team's product growth team when it raised its series D.

We worked on the following key initiatives:

- Pricing optimization: we re-architected the pricing system to optimize for conversion, new customers, and stockthrough levels, driving industry-leading inventory turns
- Conversion rate optimization: we drove 2.5x in first visit to purchase conversion via tools like outfits, dynamic merchandising, ad campaign customization, and the aforementioned pricing system
- Referrals channel: we grew this channel back when it actually worked, with things like $10-$10 and also a famous $0.99 sales
- Paid advertising growth: we built an ad-technology system to handle budgeting and bids cross-channel across Facebook, Pinterest, and Yahoo ads

Overall, I helped the company eventually go public by setting the foundations for its growth, growth marketing, and growth product teams.

Director of Growth

Rap to Beats

Developed iOS app Rap to Beats & scaled to 300K monthly active users (MAU). Led team.

We shipped several game changing features:
- In-app purchases for premier DJ beats
- A leaderboard to showcase your raps by country
- Social sharing to Instagram and Facebook

With premier DJs regularly using the app to sell their work, we were able to scale one of the first consumer apps for rap on the iPhone.

Co-Founder/ Head of Product

Scoutforce Werving & Selectie

ScoutForce was a SaaS for College Athletic Recruiting Teams. 

I joined as one of the first employees, and helped create the initial product: in the cloud recruiting software to enable recruiting teams. I did in depth discovery, wireframing, and iteration on the early features. 

This built my initial skillset in product management.

Product Manager

The Product Growth Guy 🚀 | Helping you land your next job + succeed in your career | Newsletter Writer and Podcast Host

TL;DR: I write a newsletter for product managers, product leaders, and aspiring product managers. I focus on actionable and deep tips to improve your career.

The Longer Version:

After a long career in PM - rising to VP of Product at a Unicorn - I have made the shift to writing about it.

In particular, I write about product growth. That is, the art of growing via your product. 

This means I also talk a lot about product-led growth (PLG), the SaaS B2B motion.

My newsletter doesn't just focus on growth though. 

I also break down technology, product management, product leadership, and how to get a PM job. 

It's all the things that make for a great use of your learning & development budget. 

Or even personal spend. 

The math is pretty great. 
↳ $150 for an annual subscription
↳ $211K average PM salary in the US
↳ 0-10% average range of raises offered

If the newsletter helps you get a 0.07% better raise, it pays itself. 
That's 1/142th of your raise range.

It's a pretty smart investment for every level of PM.

http://www.news.aakashg.com

Aakash Gupta

This is what a Senior AI PM at Google's Github looks like.

It's wild:

Take a look:  https://lnkd.in/e7Jb8kRe

He's made 484 contributions in the last year (>1/day). 

New-age AI PMs don't just write PRDs. They ship:

1. Prototypes
2. Frameworks
3. Perspectives on AI
4. Open source contributions

The bar for technical fluency for AI PMs continues to rise as PMs like Shubham Saboo raise the standard. 

AI PMs don't just have a theoretical understanding of concepts, but a practical knowledge of AI engineering.

Take a look at Shubham's top repos, for inspiration:

1. Collection of LLM Apps: https://lnkd.in/e-Zesb7u
2. MCP Playbook for AI agents: https://lnkd.in/eR5KHvww

These are practical resources that he's collected himself. They aren't necessarily at-scale production apps. They're PM friendly projects. 

He's also built a more-technical open source Python toolkit for building AI agents: https://lnkd.in/eCsAzPtR

When you put these types of work products together, jobs come to you. This is how you break into AI PM. 

If you look at his LinkedIn, most of his career was in dev rel. But a Github speaks louder than titles.

This is what all aspiring AI PMs should do:

1. Start with Prototyping: https://lnkd.in/eJujDhBV
2. Then pick up Cursor: https://lnkd.in/d2pcXD7R
3. Build with Claude Code: https://lnkd.in/eUyPEAma
4. Ship to Github: https://lnkd.in/eVFVT_Yc
5. Create a Portfolio: https://lnkd.in/eT3RvQiM
6. Build a Job Search System: https://lnkd.in/efbppEDj

Then you too can become an AI PM at Google like Shubham. He's created the roadmap. Now follow.

📌 Want my complete guide to the AI PM job search? Comment 'AI job search' + DM Me. Must do both.

➕ Follow Aakash Gupta for daily AI PM tips. 

Proof of work > titles

The AI PM Guy 🚀 | Helping you land your next job + succeed in your career

Linear hit a $1.25B valuation with just 2 PMs.

The way they build product is from the future:

They're contrarian.

They do almost no "growth product" work:

• No A/B tests
• No work on activation
• No growth dashboards
• Zero focus on retention tactics

They also don't have a design system. 

Instead, at the core of the way Linear builds product is "The Linear Method." Many founders I talk to have been religiously copying it. There's three keys, as I see it:

1. Directness
They don't do user stories, they speak clearly

2. No Busy Work
They don't do sprint planning, or OKRs for ICs

3. Momentum
They don't have cycles, scope aggressively, ship fast

Their founders, and CEO Karri Saarinen have operated this way from day 1. They set a very intentional culture. 

Beneath the method, there's tons more texture... 

One of the most unique processes they have is the roast. Before every launch, the entire team spends 30 mins breaking every feature with a massive doc. 

Another one is their zero bugs policy. I heard from multiple people of bugs being solved in hours, not days.

They also don't have a PM on every project. With 2 PMs, small little teams of designers and engineers really think like product people in the work that they do. 

The results speak for themselves.

$1.25B valuation with just 100 employees.
145% net revenue retention. 
No retention team needed.

They've put on a masterclass in building a unique product culture, with lots to learn for others out there.

Want to go deeper?

• My Deep Dive on Linear: https://lnkd.in/e_R9ruDG
• Head of Product Nan Yu: https://lnkd.in/e3WDcETz
• AI Agents Demo: https://lnkd.in/etXnfc2C

📌 Want my breakdown of their PLG iceberg? Comment 'Linear Iceberg' + DM Me and I'll reply to your DM.

I can't help but think most teams will move this direction.

AI + Product Management 🚀 | Helping you land your next job + succeed in your career

Want to pass PM Interviews at OpenAI, xAI, Meta, Google, Airbnb, Dropbox, Palantir?👇 

1. Understand these important concepts:

- Business: P&L, metrics trees
- Technical: APIs, scalability, performance
- Roadmapping: now/next/later, alignment
- AI/ML: prompt eng, RAG, fine-tuning, evals
- Experimentation: when to A/B test, p-values
- Prioritization: RICE, value vs effort, opp cost
- Discovery: customer interviews, user research
- Metrics: north star, guardrail, leading v lagging
- Product strategy: future trends, big tech choices

2. Practice these case interview questions:

- Product sense: https://lnkd.in/eTqEFtPM
- AI product sense: https://lnkd.in/ekWty_bw
- System design: https://lnkd.in/etTmzNzz
- Product design: https://lnkd.in/encHB-k7
- Product execution: https://lnkd.in/e8t8zS9q
- Product estimation: https://lnkd.in/eZvjP4RR
- Product strategy: https://lnkd.in/eqzpahmW
- Success metrics: https://lnkd.in/efdj_QYT
- Vibe coding: https://lnkd.in/e66DrW-h

3. Practice these behavioral questions:

- Tell me about yourself: https://lnkd.in/eYmRYF2Y
- Why want to work here: https://lnkd.in/eeuRsR9M
- What's your current pay: https://lnkd.in/gS-CKH9P
- Improve app speed: https://lnkd.in/dG9EFhiR
- Greatest weakness: https://lnkd.in/ePQ7dBtr
- Were you laid off: https://lnkd.in/e2iTP3xs
- Leadership style: https://lnkd.in/eCPdQVp2
- What level targeting: https://lnkd.in/e2YQ8tK2

4. Study these company specific processes:

- Microsoft:  https://lnkd.in/eXWWYefH
- Amazon: https://lnkd.in/eA_WxXHQ
- Apple: https://lnkd.in/eXWWYefH
- Google: https://lnkd.in/ezAHYXhV
- OpenAI: https://lnkd.in/ebR_Auss
- Meta: https://lnkd.in/evHQ_w-E

Image: Yangshun Tay

———

♻ Repost to help others in your network
📕 Save the post so you can find it in future
📌 Comment 'Interview guide' + DM me for all the links
💡 Follow me Aakash Gupta and my company account Product Growth for 2x daily AI PM insights

🛠️🤖 How to build AI agents from scratch
(Even if you've never done it before.)
𝗧𝗵𝗲𝘀𝗲 𝗮𝗿𝗲 𝘁𝗵𝗲 𝟴 𝘀𝘁𝗲𝗽𝘀 𝘁𝗼 𝘁𝗮𝗸𝗲, 𝗳𝗿𝗼𝗺 𝗽𝘂𝗿𝗽𝗼𝘀𝗲 𝘁𝗼 𝗨𝗜.

𝙁𝙞𝙧𝙨𝙩, 𝙬𝙝𝙖𝙩 𝙞𝙨 𝙖𝙣 𝘼𝙄 𝙖𝙜𝙚𝙣𝙩?

An AI Agent is an LLM that:

• Reasons on its own
• Act (via calling tools)
• Observes & improve itself

This is the core "ReAct" framework Google released all the way back in 2022. It's now a reality. 

---

𝙃𝙚𝙧𝙚'𝙨 𝙝𝙤𝙬 𝙩𝙝𝙞𝙨 𝙩𝙧𝙖𝙣𝙨𝙡𝙖𝙩𝙚𝙨 𝙞𝙣𝙩𝙤 𝟴 𝙠𝙚𝙮 𝙨𝙩𝙚𝙥𝙨:

1. Define purpose & scope

Over-scoping is the killer of agents. You want a single clear use case with success criteria, and constraints. 

2. Build system prompt

This is often the most important step. You want a really good prompt, or the whole thing falls over. 

3. Choose LLM

Don't always go for the best. Balance speed, multi-modality, and what each LLM is best for. 

4. Integrate tools

This is what makes your agent an agent, MCP, APIs, other agents as tools. Create your architecture.

5. Add memory

Don't add memory unless needed. But for support agents that need conversation history, or research agents that build on past findings? Game-changer.

6. Orchestrate things

You want a control flow over routes, workflows, message queues and your agent-to-agent (A2A) coordination.

7. Build a user interface

This is the flashy part we want to jump to. But only it do it now. Figure out how users will interact. 

8. Add testing & evals 

This is the most important step to create a continuous improvement loop. Systematically analyze errors.

Here's guides to help with each step:

1. Purpose ➝‬ https://lnkd.in/eekC6bwT
2. System prompt ➝‬ https://lnkd.in/d_qYCBT7
3. Choose LLM ➝‬ https://lnkd.in/eqRgsMZx
4. Integrate tools ➝‬ https://lnkd.in/ezNsTfbD
5. Add memory ➝‬ https://lnkd.in/eeey5Cxr
6. Orchestrate things ➝‬ https://lnkd.in/eKhmKYNp
7. Build a UI ➝‬ https://lnkd.in/epRC64ku
8. Evals ➝‬ https://lnkd.in/eGbzWMxf

---

𝙏𝙚𝙘𝙝 𝙨𝙩𝙖𝙘𝙠:

Now, what tools should you use? 

For general assistants: ChatGPT, Claude, Perplexity 
For coding projects: Cursor, Windsurf, Claude Code 
For business automation: Lindy, Relay app, n8n 
For complex workflows: LangGraph, CrewAI, LlamaIndex

The best stack is the one that gets you shipping fast.

---

Agents are one of the most powerful skills for PMs and engineers to learn right now. 

I have been studying them deeply.
 These are my core learnings.

📌 Want my 8-layer agent architecture? Comment 'agent architecture' + DM me.

What agents have you been building?

This $4B CPO runs her entire day out of Claude Code + Cursor. And she shared exactly how she does it:

It was a delight to sit down with Rachel Wolan.

She is one of the most AI-forward CPOs I have met, and she dropped all the sauce on her AI workflows.

🎬 Watch Now: https://lnkd.in/es6aQigP

Available Everywhere
Spotify: https://lnkd.in/eyt7agKj
Apple: https://lnkd.in/eAEVwr3u

🏆 Thanks to our sponsor:

Linear: Plan and build product like the best

Use my link! https://lnkd.in/e8rtjVRZ 

✍️ Here were my favorite takeaways:

1. There are two sides to AI product leadership: being a productive AI product leader yourself, and shipping AI native features for your customers. Rachel showed us both in this masterclass.

2. Webflow went from 0% of designers using Cursor to 30% using it weekly after one builder day. That's the power of setting up your org correctly. Champions teach, incentives align, adoption follows.

3. Rachel built an "agentic chief of staff" that analyzes her calendar for delegation opportunities, triages her entire inbox, and queries Snowflake in natural language. She gets answers in seconds without waiting for data scientists.

4. Her calendar agent spots double-bookings, context switching issues, and meetings she should delegate. It recommends what to cut next week. She runs it weekly & shares outputs with her EA.

5. Her email agent removes junk automatically, pins what matters, and drafts replies based on her inbox behavior patterns. It learns what she cares about by watching how she responds.

6. She queries their data warehouse in plain English through Claude Code. "How many sites does this workspace have?" answered instantly. Set up MCP servers for Snowflake & Tableau to enable this.

7. Building custom agents takes minutes. Create a markdown file in your /agents folder, describe what you want, Claude generates it. She built a LinkedIn post generator live on the pod.

8. To enable your team: give them tool access (Cursor, Claude Code), run builder days where everyone demos something new, update career ladders to expect AI usage, and let champions on your team teach others.

9. For shipping AI features, invest heavily in evals. Webflow's code generator broke when they switched models because eval coverage was insufficient. 

10. Choose AI features that leverage your core strengths. Webflow built a code generator using their CMS, design system, and production hosting. That's their differentiation versus every other coding agent.

11. Think distribution first, not last. Answer engine optimization is the new SEO. Feed FAQs to your website, build ChatGPT apps, and make sure product changes get recognized in answer engines from day one.

What's even cooler is she is a paid subscriber to the newsletter! 

Join her: https://lnkd.in/gp2cCv8K

And don't miss the ep for her live demos!

Tag who you think I should have on next 👇

What does a PM building AI features do?

I've been interviewing 2+ weekly for 14 months:

Here's the latest tools, skills, responsibilities, knowledge

𝟭. 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀

1a. Discovery + Research
Finding where AI actually adds value takes research

1b. Execution Delivery
Getting AI into production is harder than it looks

1c. Strategy Planning
You're planning the future of AI at your company

1d. Leadership Impact
The best AI PMs shape company strategy

𝟮. 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲

2a. AI Fundamentals
Understanding what AI can and can't do is critical

2b. Product Patterns
Designing for AI requires different UX patterns

2c. Market GTM
Positioning AI products requires market knowledge

2d. Testing Taxonomy
Testing AI is completely different from testing software

𝟯. 𝗦𝗸𝗶𝗹𝗹𝘀

3a. Context Engineering
Getting AI to understand what you need is half the job

3b. Evaluation Testing
You can't ship without knowing if it actually works

3c. AI Architecture
Choosing the right model & system design matters

3d. Cross-Team Communication
You're the bridge between tech teams & business

𝟰. 𝗧𝗼𝗼𝗹𝘀

4a. Core AI Platforms
Claude, GPT-5, Gemini & NotebookLM are the top tools of the trade

4b. No-Code AI Builders
Zapier, n8n, Lindy, Linear & Replit are the most used

4c. Prototyping/Vibe Coding
Bolt, Cursor, Claude Code & v0 ship prototypes fast

4d. Analytics Monitoring
DataDog, Amplitude & Arize track AI performance

With so many things to do and learn...

PM is really a "do everything" role. It's hard to have work-life balance. Here's resources to stay sane:

𝟭. 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀

1a. Discovery → https://lnkd.in/e9QrMEDw
1b. Execution → https://lnkd.in/eajEfG5R
1c. Strategy → https://lnkd.in/egemMhMF
1d. Leadership Impact → https://lnkd.in/eymXeBmE

𝟮. 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲

2a. Fundamentals → https://lnkd.in/e6zyYugs
2b. Product Patterns → https://lnkd.in/eq8xvCAK
2c. Market GTM → https://lnkd.in/eJj4bx_i
2d. Testing Taxonomy → https://lnkd.in/eKhmKYNp

𝟯. 𝗦𝗸𝗶𝗹𝗹𝘀

3a. Context eng → https://lnkd.in/ebfnDUmi
3b. Prompt eng → https://lnkd.in/d_qYCBT7
3c. Architecture → https://lnkd.in/eeey5Cxr
3d. Communication → https://lnkd.in/eg8anRXa

𝟰. 𝗧𝗼𝗼𝗹𝘀

4a. Claude → https://lnkd.in/eZ6UBbAQ
4b. Prototyping → https://lnkd.in/eJujDhBV
4c. Experimentation → https://lnkd.in/e86mpjGR
4d. No-Code Builders → https://lnkd.in/e_fjvHHN

📌 Want my free 5 day course? Comment EEC + DM me.

Follow Aakash Gupta for daily AI PM tips.

Repost to help others ♻️

Google JUST dropped 70 pgs on context eng and it's 🔥

I summarized it for you:

Stateful, personal AI starts with Context Engineering: assembling the right information at the right time.

There's 7 keys:

—

𝗢𝗡𝗘 - 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 = 𝗦𝗺𝗮𝗿𝘁 𝗔𝘀𝘀𝗲𝗺𝗯𝗹𝘆

Your LLM context window is prime real estate. Context Engineering optimizes what goes in:

→ User intent + conversation history
→ Retrieved facts (RAG for general knowledge)
→ Long-term memory (user preferences, expertise)
→ Tool outputs and grounding data

The right information, assembled at the right moment.

—

𝗧𝗪𝗢 - 𝗦𝗲𝘀𝘀𝗶𝗼𝗻𝘀 = 𝗬𝗼𝘂𝗿 𝗪𝗼𝗿𝗸𝗯𝗲𝗻𝗰𝗵

A session is a single conversation with:

1. Events (user messages, tool calls, observations)
2. State (conversation history, accumulated context)
3. Lifecycle (create, interact, close)

Think: one task, one session. When you close it, the session ends but memories can persist.

—

𝗧𝗛𝗥𝗘𝗘 - 𝗠𝗲𝗺𝗼𝗿𝘆 = 𝗬𝗼𝘂𝗿 𝗙𝗶𝗹𝗶𝗻𝗴 𝗖𝗮𝗯𝗶𝗻𝗲𝘁

Memory persists across sessions for true continuity:

- Declarative (facts, preferences: "I'm vegan")
- Procedural (how you work: "I debug like Sarah does")

RAG retrieves general facts from the internet. Memory captures YOUR specific expertise and preferences.

Big difference.

—

𝗙𝗢𝗨𝗥 - 𝗠𝗲𝗺𝗼𝗿𝘆 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 = 𝗘𝗧𝗟 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲

LLMs themselves drive memory creation:

1. Extract relevant info from session conversations
2. Consolidate with existing memories (dedupe, merge)
3. Load into vector stores for retrieval

An LLM-powered ETL pipeline. Automated intelligence extraction from your interactions.

—

𝗙𝗜𝗩𝗘 - 𝗣𝗿𝗼𝘃𝗲𝗻𝗮𝗻𝗰𝗲 = 𝗧𝗿𝘂𝘀𝘁

Every memory needs metadata for production use:

→ Source (which session created this?)
→ Timestamp (how fresh is this?)
→ Confidence (how certain are we?)

Provenance is critical for debugging, trust, and reliability in production systems.

—

𝗦𝗜𝗫 - 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗲𝘀

Two approaches to memory retrieval:

Proactive: Always include in context (user name, critical preferences)
Reactive: Retrieve on-demand based on query (semantic search, vector similarity)

Smart agents know when to pull vs push. Not everything belongs in every context.

—

𝗦𝗘𝗩𝗘𝗡 - 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗥𝗲𝗮𝗹𝗶𝘁𝘆

Building this at scale requires:

• Privacy: User data isolation, encryption, compliance
• Performance: Caching strategies, batch operations
• Scale: Vector stores for semantic search, not SQL

Google runs this across millions of users. The infrastructure matters.

—

This took me 2 hours.

To go further, you need to learn:

1. RAG vs Finetuning: https://lnkd.in/ebfnDUmi
2. Prompt engineering: https://lnkd.in/d_qYCBT7
3. AI agents: https://lnkd.in/eeey5Cxr

📌 Want me to send you the whole PDF? Comment 'context PDF' + DM me. Repost to cut the line.

Follow Aakash Gupta for daily AI tips.

Context Engineering Masterclass by Google

I literally mapped out the whole agents market. 

These are the top players:

SECTION 1: AI AGENT INFRASTRUCTURE

Development Platforms & Frameworks
• Anthropic, OpenAI, cohere, Stack, Beam, ADEPT, BREV/AN, DeepOpinion, Distyl, E2B, KESTREL AI, Moveworks, Sema4, greptile, lyzr, /dev/agents, itwin, wordware
  
Workflow Automation & Orchestration
• Enterprise automation: Zapier, Airtable, n8n, Relay, Lindy
• Multi-agent systems: fetch, crewAI, Martian, aaru, emergence
  
Agent Infrastructure & Tools
• Web & tool use: composio, Browserbase, exa, tavily
• Data & knowledge: LlamaIndex, vectara, Letta, Across AI, zep
• Authentication: ANON, Keet
• Payments: Skyfire, stripe, paymon, nevermined
  
Evaluation, Observability & Voice
• Eval & monitoring: arize, Langfuse, Patronus AI, COVAL, Agency, Haize Labs, vijil, Vocera, Weights & Biases
• Voice AI: ElevenLabs, Cartesia, Deepgram, Retell AI, VAPI, Bland, Synthflow, Hamming, FIXIE, sarvam, WaveForms

SECTION 2: CORE ENTERPRISE USE CASES

AI Assistants
• OpenAI, Anthropic, Glean, Lindy, HyperWrite, Convergence, DeepSky (Airtable), perplexity, Personal AI, Please
  
Software Development
• Cursor, Cognition, replit, Autify, Magic, lovable, FACTORY, imbue, poolside, Tusk, qodo, Magic Patterns, All Hands, Resolve
  
Customer Service
• Decagon, SIERRA, Voiceflow, COGNIGY, Maven AGI, crescendo, DevRev, parloa, Gradient Labs, yampa
  
Sales & Rev Ops
• 11x, clay, AISDR, ARTISAN, bounti, Agent, DocketAI, flowirks, QUALIFIED, mindy, IOX, tektonic ai
  
Data Analysis
• Talonic AI, Embry, ConnectlyAI, Paradigm
  
People Ops
• Mercor, MERCOR, apriora, Borderless AI, otto, moonhub, Tezi, CONVIN, ToothFairyAI
  
Accounting
• Basis, Hypatos
  
Cybersecurity
• AIRMDR, Bricklayer, Dropzone AI, nullify, prophet, RadiantSecurity, Simbian, torq
  
Marketing 
• ability, firsthand
  
Web Research
• Lutra, Reworkd

SECTION 3: INDUSTRY-SPECIFIC AGENTS

Financial Services
• Concourse, FINNY, Boosted, Brightwave, Greenlite, altiius, Hebbla, Indemn, Powder
  
Legal
• Harvey, &AI, eve, NormAI, Parcha, Spellbook
  
Healthcare
• EliseAI, Anterior, Hippocratic AI, Assort Health, health, Synthpop
  
Supply Chain & Logistics
• DIDERO, FleetWorks, HappyRobot, Naratix, Pixel Robotics
  
E-commerce 
• Naratix, CommerceOS
  
Gaming 
• ALTERA, innovacer, thoughtful
  
Industrials & Infrastructure
• Composable, juno, phaidra, Pixel Robotics

Shoutout to Crunchbase. Used it heavily. 

Want to go further on agents?

1. AI agent building: https://lnkd.in/epRC64ku
2. AI agents for PMs: https://lnkd.in/eeey5Cxr
3. Practical AI agents: https://lnkd.in/eyamsW7a
4. AI agents course: https://lnkd.in/eGw6R5v5
5. Become an AI Agents PM: https://lnkd.in/eekC6bwT
6. Relay app CEO: https://lnkd.in/ed_ji7-W
7. Lindy CEO: https://lnkd.in/eqRgsMZx

Follow Aakash Gupta for more AI

If you want traffic your site in 2025.

Don't use Old SEO.

Millions of queries daily are going to LLMs. 

Weekly users for ChatGPT alone hit 800M+. 

You need to:

1. Get cited by ChatGPT/Claude → GEO
2. Rank in Google AI overviews → AEO
3. Be used by AI agent tools → AIO
4. Convert users upon land → SXO

It's time for companies to embrace the AI search wave.

I'm not saying SEO is dead. In fact, being good at SEO makes you good at all of these things. 

But you need a specific playbook. 

Here's your starting point 👇

🔗 OLD SEO 
↳ We were obsessed with ranking number 1.

S - Search
E - Engine
O - Optimization

The bread and butter here was keywords, programmatic, backlinks, and technical optimization.

The core question behind all work was: "Can we rank higher than competitors?"

It was great for driving high-intent traffic. 

The problems were:

• more traffic without intent
• informational clicks
• algorithm updates

As a result, the funnel looked like:

100 visitors
4% convert
4 signups

💬 NEW SEO
↳ You have to get cited and used by AI platforms. 

You build 4 things:

1. Generative Engine Optimization (GEO)
2. Answer Engine Optimization (AEO)
3. AI Integration Optimization (AIO)
4. Search Experience Optim (SXO)

It's great for durable authority that compounds.

And it can drive:

• Built in trust
• Pre-qualified intent
• Visibility where decisions happen

As a result, the funnel looks like:

50 visitors
24% convert
12 signups

📌 WANT TO MASTER NEW SEO?
↳ I've written a full guide with Josh Grant.

His team at Webflow drive >10% of their signups...
Which convert at 6x the rate via AEO + GEO

Here's the guide: https://lnkd.in/e8X-Qt_C

We cover:

• How to build your team
• How to measure these efforts
• And 3 s-tier tactics you can steal from Webflow

👉 Tag your favorite growth person or SEO agency so they get the goods.

StoryAngled

We help B2B founders build brand stories that resonate — and turn them into content campaigns that drive results.

From positioning to execution, we develop strategic narratives and deliver creative campaigns your audience actually connects with.

Check the Featured section to book a free consultation.

AI Data Management

• Developing communication strategy for enterprise-level AI data management solutions.
• Creation, management, and optimization of the company's content
• Inbound lead generation

Marketing Strategist

HRnest

I was responsible for the strategy, execution, and optimization of HRnest's content across multiple channels:

• Blog
• Social media
• Video
• Email marketing

I built a comprehensive product education experience (HRnest Academy) to support free trial users during product adoption in their company.

I shifted HRnest's positioning and strategy to reach more customers from international markets. Guided the process of adjusting the app's language, voice, and messaging to fit the needs of international customers better.

I co-created multiple lead magnets and materials for the Sales and Customer Care department to support them during discovery calls.

Content Specialist

Acquiring Inbound Leads for B2B Founders with Personal Content Programs • Explaining Content, one Ugly Drawing at a time

Your B2B content marketing should do more than just fill a feed.

It should: 

• Attract the right people to your offer
• Position you as a trusted expert
• Convert attention into pipeline

At StoryAngled, we build custom content programs that deliver:

• Inbound lead generation strategy
• A full-stack content production team
• An always-growing database of proven content systems, frameworks, and resources

We work exclusively with B2B founders and growth-minded teams.

If that’s you, shoot me a DM — I’ll get back to you personally.

Kuba Czubajewski

6 things I’ll never tell a B2B founder to do on LinkedIn:

I help founders build their personal brands. But:

There are some “tactics” I’ll never recommend, no matter how much hype they get:

1. Post photos with their children

Your kids can’t give 100% consent to being online.

It’s weird.

It’s iffy.

You never know who’s looking at those photos, and LinkedIn isn’t the place.

2. Post contrarian takes just to farm engagement

Arguing for attention smells desperate.

People see right through it.

3. Use “proven” formats

If it’s “proven,” it’s probably tired.

Aim to post your original thoughts and processes. Originality gets remembered.

4. Chase every LinkedIn trend

If you’re always chasing, you’re never leading.

5. Share empty “hustle” stories

Nobody cares how early you get up.

They care about results.

6. Fake vulnerability for sympathy

Real leaders don’t perform.

They show up (wins, losses, all of it) no theatrics.

Any other things you see here that I should add to the list?

1 system to consistent inbound for complex B2B offers | 30+ founders using it | Sharing daily content advice for busy B2B leaders

This year forced me to flip StoryAngled upside down – sometimes by choice, sometimes by necessity:

• You’ll see me a LOT more on YouTube soon. I’m tired of chasing LinkedIn’s shifting algo. Time to invest in content that lasts longer than a trending post.

• I’m experimenting with a lighter subscription model. For founders who want  guidance, not a “done-for-you” handoff.

• My business partner and I are parting ways. No drama – just two people choosing their own paths. StoryAngled’s now a solo act.

• And yes, I’m finally building out those client case studies I always said I would. 

(Spoiler: the results are better than I expected.)

I’ve lost sleep over some of these decisions, ngl.

Some days, it’s 90% doubt, 10% stubbornness.

I have no investors. No coach whispering in my ear. 

Just me, a laptop, and a profusely stubborn refusal to quit.

But in 10 years, I want to look back and feel f*cking proud of this chapter.

Not just for the wins, but for the grit it took to keep going.

If you’re also in the middle of a big pivot, or you’ve been there before, I’d love to hear your story.

If your buyer can't use, share or apply the CTA in your content in ~60 seconds, they'll ignore it. I run my CTAs through this filter:

1. Can they use it right now?

A cheat sheet, a checklist, a 2-slide summary – something they can put to work in their next meeting.

2. Can they share it easily?

If your CTA helps them look smart in front of their team, you win.

Think: a quick summary they can forward, a KPI sheet, or a list of questions for their next call.

3. Can they apply it in under a minute?

If it takes more than 60 seconds, it’s too much friction.

Your buyer just scrolls past.

It's about giving your buyer an option as frictionless as possible.

Not because their attention spans suck - but because they don't know you or trust you yet to invest any more time into what you have to offer.

Here's a list of 48 micro-CTA examples for different B2B niches:

Every post I publish here saves €19-49 for my business.

Last week, I checked how much it costs to "boost" my LinkedIn post.

Well, it's kind of a sh!tty offer, tbh.

I mean, 4,300 impressions for €49?!

That’s €0.01–€0.05 per impression.

And that’s just for people seeing it. Not clicking, not engaging, just scrolling by.

I get the same results (for free) for most of the stuff I post.

So here’s how I “save” ~€1200/month (and get way better results):

1. I post 2–5x a week on my company page and personal profile

2. Every post is built around a clear problem my B2B buyers actually care about

3. I use the Demand Packet method:

→ Real trigger
→ Tangible outcome
→ Tiny proof artifact (mini case, checklist, or 2-slide summary)

4. I add a Utility CTA – something genuinely useful, no friction, no forms

5. I repurpose each post for my videos or website.

As a solo operator, I can't afford to pay LinkedIn big bucks for them to show me.

So, irresistible content is my way to go.

If you want to see how I do it, DM me and I’ll send you my template.

I'm building a YT channel for founders tired of B2B content theory. Here's my roadmap:

1. Breakdowns of scrappy B2B teams doing amazing content

↪ GOAL: Catch attention, borrow audience

Every day, I find here another small yet brilliant team creating effective AND creative content here.

I analyze their strategies to get inspired and push my own ideas further.

Got a giant Notion doc with notes – and I want to share it with you.

My hypothesis: this format should bring the exposure both to the brands (they deserve it) and my channel. 

2. Content strategy deep dives

↪ GOAL: Target problem-aware audiences, offer practical solutions

A lot of B2B content strategy videos on YT focus on theory too much.

I want my videos to feel like you're having a 1:1 workshop with me.

You'll get examples, exercises, and supplementary resources you can use to nail each element of a good content strategy.

3. My own case studies

↪ GOAL: Target solution-aware audiences, show – don't tell

Every week, I gather all the wins and losses from my clients' work.

So why shouldn't I turn each one into a separate video, breaking down what worked (or didn't)? 

You'll get really specific breakdowns, from many niches you might call "difficult."

4. Personal content journey

↪ GOAL: Target most aware audiences, build relationship

I share my own journey here – the tests, the lessons, the mistakes.

Here, you'll see the most of my peppy energy.

This format lets me pre-qualify clients who are looking for a creative guy, not just someone who will check boxes for them.

We're in the middle of finalizing the first two videos.

If you're curious how this plan turns out, I put the link to my channel in the first comment.

Pumped to see you there.

How I build B2B inbound flywheels for my clients:

(that attract high-ticket 6-12 leads every month):

1. Demand Packet

Instead, package your expertise as a crisp, self-contained story:

• What real-world pain triggered the search?
• What job does your buyer actually need done?
• What measurable outcome matters?

If you've got proof, show it in 2 slides or a checklist.

You don’t need NDA-breaking data.

You need a story buyers can repeat to their boss.

Example:

“Last quarter, a mid-market ops team cut reporting time by 35% with a single Power BI layer. Here’s the 2-slide brief we gave them.”

That’s a Demand Packet.

2. Utility CTA

Don’t ask for a call.

Offer a micro-win – something useful the buyer can grab right now.

• 2-slide summary
• Risk checklist
• KPI sheet
• Project scoping questions

Zero friction.

Only real prospects bite.

You look helpful, not hungry.

3. Momentum Loop

This is where most founders fall off.

They create content, but never compound it.

How to fix it:

• Pull a Demand Packet from your weekly article
• Pair it with your Utility CTA
• Publish on LinkedIn, send in your newsletter, add to your site
• Engage replies, deliver the asset, gather feedback

Each cycle builds your “library of proof.”

Each asset makes the next easier.

And you don't have to start from scratch.

PS. Which element sounds the most difficult to you right now? Comment below and I'll suggest a fix.

We're currently helping a client get out of the LinkedIn algo slump. Here's what we did to triple his impressions in 2 weeks:

1. Post 5x per week

Consistency matters. The algorithm rewards you for showing up.

2. Engage with top creators in your niche for 1 hour before posting

Leave thoughtful comments to get on their radar. People on LinkedIn are cool and they reciprocate fast.

3. Reply to EVERY comment under your posts

No lazy “thanks.” Real conversations boost your visibility.

4. Second engagement round – 30 more mins on your feed

2 hours after the post goes live, double down. Engage with new faces and support your circle.

5. Send 10 connection requests daily

Target active creators and true pros in your space.

The results are quite decent:

⬆️ +322% impressions

⬆️ +449% people reached

All in a complicated, B2B tech space.

PS. If you're looking for LinkedIn help, click "Book an appointment" below my profile name.

One of my clients recently returned to work with us on his YT. What he said on our first call:

"You're not just creating great stuff, but you're also a great communicator"

That hit me in the feeelzzz...

Look, just like any other content agency, I'm obsessed over deliverables.

I want the work to be top-notch + delivered on time – that's table stakes.

But from Day 1 of StoryAngled, I was also obsessed with giving my clients clarity.

• Translating your expertise into plain English (not jargon soup)

• Asking sharp questions until your real differentiator shows up

• Never “ghosting” – always keeping you in the loop

• Challenging your assumptions when something won’t work

My clients are mostly tired of yet another vendor pushing PDFs over the fence.

They want a partner who listens, gets their world, and closes the loop every step of the way.

Want to see what “content + clarity” feels like?

DM me and I’ll show you how we work – no pitch, just a peek behind the scenes.

PSA: LinkedIn doesn’t need another “innovative” framework that nobody actually uses.

Recently, I noticed a weird trend among content creators.

While they're writing their posts with AI (nothing wrong with that), they let the bot slap a fancy name on a problem they barely understand (everything wrong with that).

Example:

"Data Frankenstein Effect"
"Pipeline Paradox"
"Conversion Chasm"

Sounds cool, right?

But none of these terms actually mean anything in the real world. 

They’re just empty calories for your feed.

And what happens when somebody asks:

“Hey, I’ve never heard of the Pipeline Paradox. How does it show up in your work?”

Now you’re on the spot. 

You either scramble to make something up, or you ghost the thread. 

Both make you look clueless.

Why does this keep happening?

Because AI’s great at stringing together buzzwords. 

It’s easy to let it do the heavy lifting. 

But when you publish jargon you don’t use in real life, you’re burning trust.

I talked about it more in Audrey Chia's podcast that went live this week – and offered a few solutions to this problem (I'm not just bitchin')

You can listen to the whole thing here: https://lnkd.in/dKM4-UUQ

Building Brands That Convert | Copywriting + AI + Content Strategy | Founder of Close with Copy | Your Growth Partner 💛

My friend Lee Densmer recently published her book about B2B Content – and I'm OBSESSED!!

Lee is one of my favorite creators out here. Her expertise shines through every post. 

And not because she's using fancy words or flexes bloated numbers. 

But because she brings simplicity and logic to the world so overcomplicated by many "experts."

If you're looking for a guide to build your B2B content program, this book is exactly what you need.

I also had the honor to provide 2 quotes for the book – one about AI + Human content systems and the other about gated content.

Got a lil' emotional seeing my name in a REAL FREAKING BOOK.

Thank you, Lee, for being so awesome!

3 micro-triggers that make B2B buyers actually reply to your content (tested on 2000+ posts this year):

1/ Use their own complaints - word for word

Don’t guess. Steal the exact line your buyers grumble about to their team.

Example: “We’re drowning in broken dashboards every Monday morning.”

Our client posted this and got 5 DMs from ops leaders - 2 booked calls.

2/ Show proof, don’t just promise

Nobody cares about “great results.” They want to see it.

Drop a real before/after screenshot or a no-BS checklist.

We posted a 2-slide “bottleneck fix” for a client - one prospect sent it straight to his COO.

3/ Tell people who should scroll away

Stop trying to please everyone. Say who your solution isn’t for.

Example: “If you don’t have reporting chaos, keep scrolling.”

Every time, the right people lean in and reply – the rest self-select out.

Want to know which trigger fits your market right now?

DM me or drop a comment, I’ll give you my honest answer.

taplio

The Battle

Aakash Gupta

Kuba Czubajewski

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Performance ScoreAakash Gupta's LinkedIn Performance

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taplio

The Battle

Aakash Gupta

Kuba Czubajewski

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Aakash Gupta's LinkedIn Performance

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Performance ScoreAakash Gupta's LinkedIn Performance