Aakash Gupta's LinkedIn Strategy, AI +…

Here's everything you need to do to become an AI PM in 2026 (and potentially get an OpenAI $500K+ job): People are still sharing my plan from Mar 2024. Here's the actual up to date version: Step 1…

LinkedIn post image: Here's everything you need to do to become an AI PM in 2026 (and potentially get an OpenAI $500K+ job):

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Career Advice8 months ago

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The CEO of a $3 trillion company just made himself a product manager. Microsoft CEO Satya Nadella has assumed a hands-on product management role to urgently accelerate Copilot improvements, driven by…

LinkedIn post image: The CEO of a $3 trillion company just made himself a product manager.

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AI Product Management8 months ago

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Over the past 3 months, I’ve used one AI prototyping tool the most: Here’s why I use Figma Make: 1. Easiest for design to pick up With other AI prototyping tools, there’s a step of lossiness from t…

LinkedIn post image: Over the past 3 months, I’ve used one AI prototyping tool the most:

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AI8 months ago

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People keep asking me: how do I get started with AI? Here's a complete tool stack: I've made all the AI products I recommend free with an annual subscription to my newsletter: https://lnkd.in/enqdsj…

LinkedIn post image: People keep asking me: how do I get started with AI?

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AI Product Management8 months ago

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Cursor’s visual editor promises a future where front end eng and design merge. But there’s still a gap. Let’s start with the editing. One of the interesting things about Cursor’s visual editor is…

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AI8 months ago

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We’re spending $200B+ a year on data centers to power AI. One company raised $11M, grew human brain cells on a chip, and the cells taught themselves to play a 3D shooter in a week. Cortical Labs grew…

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6 months ago

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Topics & Content Focus

Primary Topics

AI-native product management and strategy (how to design, ship, and scale AI products beyond simple model integration)AI-first UX and workflow design (high-density AI interactions, Copilot-style integrations, and product ‘baked-in’ intelligence)AI prototyping and design systems (Figma Make, visual editors, bridging exploratory design with production-ready code)AI PM career pathways and upskilling (roadmaps to become AI PMs, breaking into top-comp roles like OpenAI, skill stacks and portfolios)

Secondary Themes

Developer and builder tooling for AI (Cursor, Relay, agents, evals, observability, research and intelligence platforms)Evaluation, observability, and context engineering for AI products (e.g., Arize AI, context selection, AI performance loops)Executive behavior in the AI era (CEOs acting as PMs, organizational breakdowns, product versus infra misalignment)Cross-functional collaboration between design, engineering, and PM in AI workflows

Industry Focus

AI product management in B2B SaaS and developer toolsUX and design for AI-first enterprise and productivity softwareCareers and hiring in AI product roles at frontier labs and large tech (e.g., OpenAI, Microsoft)

Content Categories

Playbooks and roadmaps (stepwise guides like ‘7 steps to become an AI PM’)Tool stacks and curated ecosystems (complete AI toolchains for PMs and builders)Product teardown and strategic commentary (Copilot vs Cursor, ChatGPT vs Office Copilot)Hands-on implementation guides (how to prototype, go to production, ship with AI coding tools)Career and professional development content (portfolios, networking, interview prep for AI PMs)

Performance Insights

7.5%

Avg Engagement Rate

STABLE

Performance Trend

Best Performing Topics

Executive-level AI product strategy failures and competitive gaps (e.g., Microsoft Copilot vs Cursor, ChatGPT vs Office bundling)Comprehensive career roadmaps for AI PM roles (multi-step, end-to-end plans with resources)Concrete, opinionated recommendations on specific AI design/prototyping tools with clear criteria (e.g., Figma Make rationale)

Virality Signals

Using marquee names and numbers (Microsoft, OpenAI, $3T valuation, $80B infra, $500K+ compensation) to anchor stakes and urgencyPackaging advice as complete systems (e.g., ‘everything you need to do’, ‘complete tool stack’) rather than isolated tipsAttaching tactical resource bundles (guides, tutorials, courses, bootcamps, newsletters) behind each framework or planComment-gated assets (high-res diagrams, step-by-step workflows) that stimulate both comments and repostsClear contrast setups (startup vs incumbent, baked-in AI vs bolt-on features, exploration vs production) that spark debate

Structure & Quality

500

Avg Length (Words)

HIGH

Depth Level

ADVANCED

Expertise Level

8.5/10

Uniqueness Score

Common Hooks

Authority + surprise hooks referencing major companies or outcomes (e.g., a $3T CEO acting as a PM, $500K+ jobs at OpenAI)Personal experience hooks (‘Over the past 3 months, I’ve used…’, ‘People keep asking me…’)Direct promise hooks (‘Here’s everything you need to do to become an AI PM…’, ‘Here’s a complete tool stack…’)Problem-first hooks that set up a gap or failure (‘Cursor won the developer market’, ‘there’s still a gap’)

Common Endings

Explicit CTAs to comment specific keywords to receive resources or templatesFollow-CTA positioning the creator as a daily AI PM/AI tips sourceFinal punchline that reframes urgency or timing (‘The best time was 2023. The second best time is now.’)Occasional open-ended questions to invite discussion around tools or workflows

Value Delivery Methods

Actionable, stepwise frameworks that translate abstract AI hype into concrete PM behaviors and habitsCurated toolchains with clear mapping from problem → tool → outcome for AI builders and PMsNuanced product and UX analysis emphasizing integration layers, context engineering, and density of AI valueCareer acceleration guidance tailored specifically to AI PM roles, including content diet, courses, projects, and networking

Formatting Style

Short paragraphs with frequent line breaks for skimmabilityNumbered lists for steps, tools, or frameworksBulleted sublists under each tool/step clarifying use cases and benefitsOccasional emojis and symbols (📌, ➕) as visual anchors rather than decorationSparse, targeted hashtags aligned to product/UX rather than generic AI hashtag dumps

Audience & Tone

YES

Question Usage

0.4%

Response Rate

Detected Tone

AI-native product strategistSmart-casual operator with teacherly clarityDecisive and opinionated, but pragmaticResource-heavy, playbook-oriented expertsemi-formalsecond-person

Interaction Style

Instructional mentor tone that positions the author as a guide for AI PMs and buildersPrompt-based engagement (ask for comments, tools people use, questions about workflows)Value-first posting where CTAs are embedded after substantial information has been deliveredUse of repeatable engagement patterns (comment keywords, follow prompts, repost incentives) to build ongoing interaction

Community Building Signals

Creating a shared identity around ‘modern AI PM’ and ‘AI builders’ through repeated language and expectationsDriving readers into an owned ecosystem (newsletter, courses, bootcamps) for deeper engagement beyond LinkedInEncouraging user participation via comment-keyword systems that create mini-events around specific postsReferencing other creators and communities (YouTube, Twitter, conferences) to position followers inside a broader AI network

Writing Style Patterns

Content Strategy

Hook: Authority + surprise hooks referencing major companies or ouTone: semi-formalCTA: Directive keyword comments (‘Comment “figma make t

Writing style breakdown

- Core characteristics

Highly professional but plainly spoken and accessible.

Analytical, product-focused, and information-dense.

Conversational without being chatty; no fluff or filler.

Persuasive through logic and clarity, not hype.

Tone is confident, expert, and slightly urgent when needed (e.g., AI race, career urgency).

- Sits between professional and casual

Uses correct grammar and clear structure.

Mixes in everyday phrasing: “You need to ship something”, “Try it yourself (free)”.

No slang beyond common tech/product jargon.

- Emotional tone and energy

Medium-to-high energy, but controlled.

Pace is brisk and focused; the writer gets to the point quickly.

Emotion is used to underline stakes (AI race, career opportunities, product failures), not to dramatize.

Urgency often appears in closing lines: “The second best time is now.” / “Don’t let that be you!”

- Frequent use of

Rhetorical questions: “What happened?”, “How do you build AI product like copilot right?”

Contrast and comparison: “One reimagined the workflow. One added a feature.”

Parallelism: repeating similar sentence structures for emphasis.

Short, standalone punchlines: “Some fragmentation is OK.” / “Then what you see is what you get.”

Framing with “Here’s…”: “Here’s a complete tool stack:”, “Here’s why I use Figma Make:”, “Here’s the actual up to date version:”.

Implicit social proof: references to OpenAI, Microsoft, Figma, high-paying roles.

Explanations are concrete and example-heavy, centered on specific tools, steps, or product decisions.

- Primarily second-person “you” when instructing or advising

You don't need to be an engineer. You need to ship something.

Don’t let that be you!

- First-person “I” used sparingly and purposefully

To give credibility: “Over the past 3 months, I’ve used one AI prototyping tool the most:”

To justify recommendations: “Here’s why I use Figma Make:”

Third-person used to describe companies, teams, and markets: Microsoft, Cursor, Satya Nadella, design team, hiring managers.

- Direct commands are frequent and clear

Use Reforge Build to create prototypes…

Set up Cursor…”, “Build a basic app…”, “Integrate Stripe…

- Suggestions are framed as logical next steps, not tentative

You need to balance both.

If different tools are required, use different tools.

CTAs are directive: comment, follow, join, build, use, try.

Aakash Gupta

Warm Analysis

Performance Overview

Top Posts by Engagement

Posting Patterns & Frequency

Best Performing Days

Best Performing Times To Post