Almost Timely News

Almost Timely News

Team Pick
AI & Agents
By
Christopher S. Penn
One of the longest-running AI newsletters for marketers, and the one that shows the working instead of the takeaway.
SUBSCRIBERS
293,000+
HOW OFTEN
Weekly
ACCESS
Free
WRITER
Christopher S. Penn
Last updated
August 5, 2026

Preview

Almost Timely News

What it is.

Christopher S. Penn has written Almost Timely weekly for years, on AI, data science, and analytics for marketers.

Each issue takes one problem and works it through: connecting an agent to a data source, doing feature engineering with AI, demonstrating AI skills in a job hunt. The prompts and the reasoning are both shown.

It's free, the archive is open, and he surveys readers to set the agenda.

What you get.

  • A weekly deep dive on one AI marketing or analytics problem
  • Prompts and the reasoning behind them, so you can adapt instead of copy
  • Data science technique explained for people who aren't data scientists
  • Reader-requested topics, which keeps it close to live problems
  • Free access with a long open archive
OUR PICKS

Editions we'd start with.

How to Connect an AI Agent to a Data Source ↗

A reader request, worked end to end. The clearest sample of what he does.

How To Do Feature Engineering with AI ↗

Data science made usable for a marketer. Read it before your next analysis.

The Biggest Problem with AI Today ↗

His argument about where AI adoption keeps failing, and it isn't the models.

How to Demonstrate Your AI Chops in Job Hunting ↗

July 2026, and the practical one to forward to anyone job hunting.

Almost Timely Reader Survey Summer 2026 ↗

How he sets the agenda, which tells you what the next few months will cover.

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Goes straight to Christopher S. Penn.
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Questions about Almost Timely News

Can I adapt what it shows?
Is every issue relevant to marketing?

Questions about AI & Agents

What separates a useful AI workflow from a demo?
Do marketers need to understand data science?
How do you keep up with AI without drowning?
Strengths
  • Shows the prompts and the reasoning, so you can adapt the method.
  • Years of consistent weekly publishing, with no gaps in the archive.
  • Brings actual data science to marketing questions, which is rare.
  • Free, with no paywall over the archive.
Limitations
  • Broad AI and analytics coverage, so not every issue lands on a GTM problem.
  • Long and technical in places. Set aside proper time.
  • Some issues are pitches for his own courses and books.
  • Little here on B2B pipeline specifically.
Skip this if
  • Skip it if you already have a weekly AI read you finish.
Ideal for
  • Marketers building AI workflows
  • Analytics and data-minded marketers
  • Anyone learning to prompt properly
  • Stage: Any stage

Reading is the cheap part.

TripleDart runs organic, paid, and GTM engineering for 300+ B2B tech companies. Bring us the number you have to hit.