Directing Intelligence Digest | October 15, 2026
Yesterday’s news had one through-line...a human one. AI can sit in the interview and draft the tutoring message. What remains ours is the design of the handoff: who judges, who edits, and whether “access” is mistaken for learning.
The short version
Meta scaled back AI-driven cuts. Walmart workers fought AI schedules.
McKinsey’s AI client interviews: humans still score.
Target says its myDay app saves 2 million hours a year (company figures).
A Wyoming naturopath cut weekly posting from up to 15 hours to two.
Maryland’s AI tutor offer lowered grades. Supervised LearnLM matched humans.
Principals build their own tools. Falls Church parents want data answers.
WORK
The rush to AI... and the quiet walk back
Meta, per Reuters, scaled back plans to cut staff and lean on AI agents after employees spent more and more time cleaning up technical and security errors. At Walmart, Business Insider found store workers fighting AI tools that plotted nonsensical routes and impossible schedules.
Microsoft’s Kathleen Hogan: “access and usage do not equal transformation.” Mentoring helped.
Meanwhile Airtable, after its Bending Spoons acquisition, is parting with a large share of its team, citing smaller, faster teams. Zoho’s Sridhar Vembu says he refuses that path and will retrain instead. “We will see in 2030.”
What to watch: Who rehires judgment... and who keeps paying people to clean up after the bot.
Read it: The Guardian · Airtable: Back to bases
On X: Sridhar Vembu
Ten minutes with an AI client... scored by people
McKinsey is testing a new step for some undergraduate business-analyst candidates in North America this fall: about ten minutes talking with an AI simulation of a client. The simulation aims to cover about 80% of everyday client scenarios. The AI does not score anyone. Humans do.
Derek Thompson notes AI is remaking the application funnel faster than the job. Here the machine plays the other side of the table. People keep the judgment.
What to watch: Whether the pilot predicts on-the-job performance, and whether copycats keep human scoring.
Read it: The Verge
On X: Derek Thompson
Who’s Directing? We built machines to screen people out. Now we build machines for people to talk to... and still need a human to say yes. If no one can override the scorecard, you did not automate judgment.
Target says myDay gave 2 million hours back (self-reported)
Target says its store app, myDay, merges trucks, orders, schedules and inventory into one prioritized task list for more than 350,000 team members. By the company’s own count, that saves more than 2 million hours a year, plus $25 million in value from “Scan to Divert.”
It started with more than 50 store leaders and workers telling engineers what hurt. Built with the floor, not dropped on it.
What to watch: Whether saved hours become guest time and development... or fewer shifts.
Read it: Target newsroom (self-reported)
Who’s Directing? Two million hours is a big number. What a company does with them is a value. If you can’t tell your people where the saved time is going, the value does not get realized.
A one-and-a-half-person clinic in Rawlins gets its weekends back
April Martinez, a holistic health educator and naturopath in Rawlins, Wyoming, calls her shop “a one and a half man show.” Posting to eight platforms ate 10 to 15 hours a week. Now it takes about two.
She built her own AI agent loaded with her market profile, a style guide and her own material. Claude handles strategy. “It’s my business partner,” she says. But she reads every post before it goes out. “AI lies.”
What to watch: Whether small owners keep their own voice... or all start sounding the same.
Read it: Saratoga Sun via Wyoming News Exchange
Who’s Directing? She gave the machine her voice and kept the final read for herself. Plenty of companies with a thousand times her budget can’t say the same.
LEARNING
Same tech, opposite results: access vs. a supervised tutor
A University of Maryland RCT offered 2,379 undergraduates a course AI tutor. Students offered it finished about four points lower. Only about 15% used it, and nearly 74% of requests sought information or solutions. Fewer than 1% asked for feedback. Access alone is not a learning intervention.
In five UK schools, expert tutors approved, edited or rewrote every LearnLM draft for 165 math students. Remediation: LearnLM 93.0%, human tutors 91.2%, static hints 65.4%. Transfer: 66.2% vs 60.7%.
What to watch: Adoption metrics before grade claims, and bots sold without the supervisor.
Read it: Maryland EDSI · arXiv: LearnLM
On X: Kevin Bryan
Who’s Directing? You cannot call it tutoring if three-quarters of the clicks are “give me the answer.” Access without pedagogy is a polite way to lose the room.
A Virginia principal’s motto: people over paperwork
Derek Cantrell, principal of Allegheny High School in Covington, Virginia, once lasted one day in a computer science class. Now he builds his own AI tools. One tracks absences, tardies and referrals, warns students early and lets them earn back standing.
EdWeek found others. In Wilmington, Delaware, principal Sterling Seeman wrote prompts that help teachers draft yearly goals. In Idaho, Rachel Jensen’s trackers help teachers overseeing 90-plus online students each. Cantrell’s warning: keep student data out of the public domain.
What to watch: Whether districts back principal-builders with data guardrails.
Read it: Education Week
Who’s Directing? The best AI strategy here didn’t come from a vendor. It came from a principal who wanted to be in the hallway more. Part of your plan should give educators time back with students. You have to be able to measure that.
Falls Church wrote the rules. Now parents want the receipts.
Falls Church City Public Schools in Virginia laid out its classroom AI. Teachers get four tools: Gemini, SchoolAI, Diffit and Canva. Students get SchoolAI in grades 6 to 12 and Gemini in 9 to 12. No ChatGPT or Copilot. AI is not used for grading, discipline, special education or placement.
The News-Press pushed further: what does it cost, and what student data do vendors see? Answers are pending.
What to watch: The cost figures and data answers in the follow-up.
Read it: Falls Church News-Press
Who’s Directing? Naming your tools is the easy part. If you can’t tell a parent what their child’s data costs and where it goes, you haven’t earned their trust.
Quick hits from X
Agent identity at work. Ethan Mollick gave his agent its own email so it cannot draft as him. Mollick on X
Orgs as messy intelligence. Alex Imas: messy human variety makes organizations a collective superintelligence. Imas on X
Proofs vs understanding. Stefania Druga: AI can flood math with proofs. Understanding is still scarce. Druga on X
See you tomorrow.
Todd McLees · Directing Intelligence Digest