Greg Isenberg

Greg Isenberg

US
@gregisenberg
Science & Technology
761
Video Count
28.8M
Video View
587.0K
Subscriber
#15,664
United States Rank
#70,813
Global Rank
Greg Isenberg YouTube channel subscribers:587,000- Seelive statisticsand growth insights below.

Greg Isenberg YouTube Statistics & Analytics

Subscribers
587.0K
Total Views
28.8M
Videos
761
Activity
Unknown

Greg Isenberg Content Analysis

Content Type Distribution

Long videosLong
82%
102 videos
ShortsShorts
18%
23 videos

📽️ This channel specializes in long-form videos. Deep dives and comprehensive content perform well here.

Content Categories

Primary CategoryScience & Technology
59%
Science & Technology
74(59%)
People & Blogs
51(41%)

🎯 Primary focus: Science & Technology with 74 videos (59% of categorized content).

Latest Video

Long video
FDE: The $1M/Year AI Job Explained
51:34
New

FDE: The $1M/Year AI Job Explained

15.7K
Views
656
Likes
3 days ago
Published

I sit down with Vas from Varick Agents to map out exactly how to break into AI forward deployed engineering — and how to grow into a sharper FDE — in thirty days. We start from a single premise: every company can now buy the same frontier intelligence, so the real advantage moves to deployment. Vas traces the role back to Palantir, explains the judgment that decides where AI belongs, and lays out the audit → evals → deployment loop that turns raw models into measurable business value. He then hands over a full 30-day plan to build, harden, measure, and defend a production-grade agent, so you can do the job before you hold the title. The whole conversation stays tactical and grounded, with clear examples I can apply today. The FDE Blueprint: https://startup-ideas-pod.link/fde-starter Timestamps 00:00 – Intro 02:03 – What is an FDE 04:09 – How Palantir Popularized FDEs 06:16 – Deciding Where Intelligence Belongs 11:26 – What FDEs Earn 14:59 – Two Kinds of Judgment: Communication and Engineering 17:38 – How the Work Really Gets Done 20:40 – Audit, Evaluation, Deployment 22:56 – Which LLM to Choose 27:36 – Audit: Finding the Workflow Worth Rebuilding 31:47 – Evals: Turn non-determinism into evidence 32:57 – Deployment: Build on Existing Systems 38:59 – The 30-Day Plan Begins 49:13 – Final Thoughts Key Points * Intelligence is now commoditized, so the real edge lives in deployment — the job of the AI forward deployed engineer. * Vas traces the FDE role to Palantir, where engineers embed on-site, learn workflows, and customize the ontology per client. * The strongest FDEs blend deep technical skill with consulting-grade communication — the rare "art plus science" combination worth up to a million dollars a year. * The FDE loop runs audit → evals → deployment, and each improved workflow makes the next one clearer. * Vas condenses a year of learning into a 30-day plan: build an agent, harden it, make it measurable, then defend it like an FDE Numbered Section Summaries 1. Intelligence on Tap Vas opens by showing me that every company can now buy the same frontier intelligence, from Claude Code to Codex to Cursor, which turns the raw model into a commodity. Because everyone taps the same stack, the advantage shifts to where, how, and why a business applies it — the exact territory of the forward deployed engineer. 2. The Palantir Blueprint Vas draws on friends who worked as Palantir FDEs to explain the origin of the role. Palantir built a customizable ontology, sent engineers on-site to learn each client's workflows, and spun up dashboards and agents tuned to that specific business — essentially consulting for the software age. 3. Where Intelligence Belongs We dig into FDE judgment: choosing which steps of a workflow deserve an LLM and which stay as deterministic software or simple if-then logic. Vas cites the MIT figure that 95% of generative AI pilots fail, and credits selective design plus deep on-site observation as the fix. 4. The Million-Dollar Combination Vas frames the FDE as the best of two worlds — a fluent communicator who reads business reality and a strong engineer who ships production systems. I compare it to someone who speaks both art and science, and Vas confirms that this rarity is exactly why roles reach up to a million dollars a year. 5. Audit, Evals, De**ployment** Vas cements the core loop: audit the real workflow, build evals that turn fuzzy tasks into evidence, then deploy on top of existing systems like NetSuite, Salesforce, and SAP. He stresses full audit trails and human-in-the-loop approval so clients trust what the agent does. 6. Selling and De-Risking the Work We talk pricing and trust. Vas suggests running the first audits free to prove measurable value, and I share how my agency LCA rebranded the word "audit" as a "sprint" so it lands more smoothly with clients. 7. The 30-Day Plan Vas splits a year of learning into four weeks: week one builds an agent that completes a real loop; week two hardens it with schemas, failure modes, and exception handling; week three makes it measurable across revenue, risk, and cost; week four defends it like both an engineer and a VP. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND VAS ON SOCIAL Varick Agents: https://www.varickagents.com/#hero-section X/Twitter: https://x.com/vasuman AI Forward Deployed Engineers: https://learn.varickagents.com/fde-in-30-days

See Top Science & Technology YouTube Channels in United States

Compare this channel with the leading Science & Technology creators in United States.

Ranking: United StatesCategory: Science & TechnologyCategory Focus: 59%
Open ranking

Greg Isenberg Channel Snapshot

Score: 5.8/10

A high-level snapshot of content cadence, library size, and consistency derived from this channel's recent uploads.

Overall Score
5.8
Consistency
95%
Cadence
2-3/wk
Library
50

Growth Potential

6.6/10

Library of 50 videos with ~49.8K avg views per upload. Combined size + reach signal suggests steady building.

Audience Engagement

6.2/10

Avg engagement rate of 3.74% (likes + comments / views) across 48 videos. Healthy — at or above the ~3% baseline.

Niche Specialization

4.5/10

48% of recent videos cluster in Knowledge. Generalist mix — niche consolidation often unlocks growth at this stage.

Suggested Actions

Recommendations grouped by typical impact for channels at this stage

  1. 1
    Increase upload frequency to 2-3 videos per week
    High ImpactCadence
  2. 2
    Focus on SEO optimization for better discoverability
    High ImpactSEO
  3. 3
    Analyze top-performing content for pattern replication
    MediumStrategy
  4. 4
    Increase community engagement through comments and polls
    MediumEngagement

Frequently Asked Questions About Greg Isenberg

Data Source & Accuracy

Source: YouTube Data API v3
Accuracy: Real-time statistics from official YouTube API
Data is updated hourly and sourced directly from official APIs to ensure accuracy and reliability.

Data from YouTube Data API v3 • Updated hourly • Last updated: 08:42 PM